import { Knex } from 'knex';
import { db } from '../database';

export class ReturnEffectivenessService {
  /**
   * 分析退货效果
   * @param params 分析参数
   * @param traceInfo 追踪信息
   * @returns 分析结果
   */
  public static async analyzeReturnEffectiveness(
    params: {
      timeRange: { start: string; end: string };
      skuIds?: string[];
      metrics?: string[];
    },
    traceInfo: {
      tenantId: string;
      shopId: string;
      taskId: string;
      traceId: string;
      businessType: 'TOC' | 'TOB';
    }
  ): Promise<{
    timestamp: string;
    timeRange: { start: string; end: string };
    metrics: {
      totalReturns: number;
      returnRate: number;
      averageReturnTime: number;
      returnCost: number;
      salesImpact: number;
      customerRetentionRate: number;
      skuPerformance: Array<{
        skuId: string;
        returnRate: number;
        salesBeforeReturn: number;
        salesAfterReturn: number;
        impact: number;
      }>;
    };
    insights: string[];
  }> {
    try {
      const timestamp = new Date().toISOString();
      
      // 模拟分析数据
      const metrics = {
        totalReturns: Math.floor(Math.random() * 500) + 100,
        returnRate: (Math.random() * 15 + 2).toFixed(2),
        averageReturnTime: Math.floor(Math.random() * 10) + 3,
        returnCost: (Math.random() * 50000 + 10000).toFixed(2),
        salesImpact: (Math.random() * 20 + 5).toFixed(2),
        customerRetentionRate: (Math.random() * 30 + 60).toFixed(2),
        skuPerformance: Array.from({ length: 10 }, (_, index) => ({
          skuId: `SKU-${index + 1}`,
          returnRate: (Math.random() * 20 + 1).toFixed(2),
          salesBeforeReturn: Math.random() * 100000 + 10000,
          salesAfterReturn: Math.random() * 80000 + 8000,
          impact: (Math.random() * 30 + 5).toFixed(2),
        })),
      };
      
      // 生成洞察
      const insights = [
        `期间总退货数为 ${metrics.totalReturns}，退货率为 ${metrics.returnRate}%`,
        `平均退货处理时间为 ${metrics.averageReturnTime} 天`,
        `退货成本为 ¥${metrics.returnCost}，对销售的影响为 ${metrics.salesImpact}%`,
        `客户 retention 率为 ${metrics.customerRetentionRate}%`,
        `表现最差的 SKU 退货率为 ${Math.max(...metrics.skuPerformance.map(s => parseFloat(s.returnRate))).toFixed(2)}%`,
      ];
      
      return {
        timestamp,
        timeRange: params.timeRange,
        metrics,
        insights,
      };
    } catch (error) {
      console.error('Error analyzing return effectiveness:', error);
      throw new Error('Failed to analyze return effectiveness');
    }
  }

  /**
   * 生成退货效果分析报告
   * @param params 报告参数
   * @param traceInfo 追踪信息
   * @returns 分析报告
   */
  public static async generateEffectivenessReport(
    params: {
      timeRange: { start: string; end: string };
      reportType: 'weekly' | 'monthly' | 'quarterly' | 'yearly';
      includeRecommendations?: boolean;
    },
    traceInfo: {
      tenantId: string;
      shopId: string;
      taskId: string;
      traceId: string;
      businessType: 'TOC' | 'TOB';
    }
  ): Promise<{
    reportId: string;
    timestamp: string;
    timeRange: { start: string; end: string };
    reportType: string;
    summary: string;
    metrics: {
      totalReturns: number;
      returnRate: number;
      averageReturnTime: number;
      returnCost: number;
      salesImpact: number;
      customerRetentionRate: number;
    };
    trends: Array<{
      metric: string;
      currentValue: number;
      previousValue: number;
      change: number;
      trend: 'up' | 'down' | 'stable';
    }>;
    recommendations: string[];
  }> {
    try {
      const reportId = `RETURN-EFFECTIVENESS-REPORT-${Date.now()}`;
      const timestamp = new Date().toISOString();
      
      // 分析退货效果
      const analysis = await this.analyzeReturnEffectiveness(params, traceInfo);
      
      // 生成摘要
      const summary = `退货效果分析报告 (${params.reportType}) - ${params.timeRange.start} 至 ${params.timeRange.end}`;
      
      // 生成趋势数据
      const trends = [
        {
          metric: '退货率',
          currentValue: parseFloat(analysis.metrics.returnRate),
          previousValue: parseFloat((Math.random() * 5 + parseFloat(analysis.metrics.returnRate) - 2.5).toFixed(2)),
          change: 0,
          trend: 'stable' as 'up' | 'down' | 'stable',
        },
        {
          metric: '退货成本',
          currentValue: parseFloat(analysis.metrics.returnCost),
          previousValue: parseFloat((Math.random() * 10000 + parseFloat(analysis.metrics.returnCost) - 5000).toFixed(2)),
          change: 0,
          trend: 'stable' as 'up' | 'down' | 'stable',
        },
        {
          metric: '销售影响',
          currentValue: parseFloat(analysis.metrics.salesImpact),
          previousValue: parseFloat((Math.random() * 5 + parseFloat(analysis.metrics.salesImpact) - 2.5).toFixed(2)),
          change: 0,
          trend: 'stable' as 'up' | 'down' | 'stable',
        },
        {
          metric: '客户保留率',
          currentValue: parseFloat(analysis.metrics.customerRetentionRate),
          previousValue: parseFloat((Math.random() * 5 + parseFloat(analysis.metrics.customerRetentionRate) - 2.5).toFixed(2)),
          change: 0,
          trend: 'stable' as 'up' | 'down' | 'stable',
        },
      ];
      
      // 计算趋势变化
      trends.forEach(trend => {
        trend.change = parseFloat((trend.currentValue - trend.previousValue).toFixed(2));
        if (trend.change > 0.5) {
          trend.trend = 'up';
        } else if (trend.change < -0.5) {
          trend.trend = 'down';
        } else {
          trend.trend = 'stable';
        }
      });
      
      // 生成建议
      const recommendations = [
        '建议优化产品描述，减少因描述不符导致的退货',
        '建议加强质量控制，降低因质量问题导致的退货',
        '建议优化退货流程，提高处理效率，减少平均退货时间',
        '建议分析高退货率SKU，找出根本原因并进行改进',
        '建议加强客户沟通，提高客户满意度，降低退货率',
        '建议制定退货预防策略，如提供更详细的产品信息和使用指南',
      ];
      
      return {
        reportId,
        timestamp,
        timeRange: params.timeRange,
        reportType: params.reportType,
        summary,
        metrics: {
          totalReturns: analysis.metrics.totalReturns,
          returnRate: parseFloat(analysis.metrics.returnRate),
          averageReturnTime: analysis.metrics.averageReturnTime,
          returnCost: parseFloat(analysis.metrics.returnCost),
          salesImpact: parseFloat(analysis.metrics.salesImpact),
          customerRetentionRate: parseFloat(analysis.metrics.customerRetentionRate),
        },
        trends,
        recommendations,
      };
    } catch (error) {
      console.error('Error generating effectiveness report:', error);
      throw new Error('Failed to generate effectiveness report');
    }
  }

  /**
   * 评估退货对销售的影响
   * @param params 评估参数
   * @param traceInfo 追踪信息
   * @returns 影响评估结果
   */
  public static async evaluateSalesImpact(
    params: {
      timeRange: { start: string; end: string };
      skuIds?: string[];
    },
    traceInfo: {
      tenantId: string;
      shopId: string;
      taskId: string;
      traceId: string;
      businessType: 'TOC' | 'TOB';
    }
  ): Promise<{
    timestamp: string;
    timeRange: { start: string; end: string };
    overallImpact: number;
    skuImpacts: Array<{
      skuId: string;
      salesBeforeReturn: number;
      salesAfterReturn: number;
      impact: number;
      returnRate: number;
    }>;
    recommendations: string[];
  }> {
    try {
      const timestamp = new Date().toISOString();
      
      // 模拟销售影响数据
      const skuImpacts = Array.from({ length: 15 }, (_, index) => ({
        skuId: `SKU-${index + 1}`,
        salesBeforeReturn: Math.random() * 100000 + 10000,
        salesAfterReturn: Math.random() * 80000 + 8000,
        impact: (Math.random() * 30 + 5).toFixed(2),
        returnRate: (Math.random() * 20 + 1).toFixed(2),
      }));
      
      const overallImpact = parseFloat((skuImpacts.reduce((sum, sku) => sum + parseFloat(sku.impact), 0) / skuImpacts.length).toFixed(2));
      
      const recommendations = [
        '建议对高影响SKU进行重点分析和改进',
        '建议优化产品质量和描述，减少退货率',
        '建议加强售后服务，提高客户满意度',
        '建议制定销售策略，减轻退货对销售的影响',
      ];
      
      return {
        timestamp,
        timeRange: params.timeRange,
        overallImpact,
        skuImpacts: skuImpacts.map(sku => ({
          ...sku,
          impact: parseFloat(sku.impact),
          returnRate: parseFloat(sku.returnRate),
        })),
        recommendations,
      };
    } catch (error) {
      console.error('Error evaluating sales impact:', error);
      throw new Error('Failed to evaluate sales impact');
    }
  }

  /**
   * 获取退货趋势分析
   * @param params 趋势分析参数
   * @param traceInfo 追踪信息
   * @returns 趋势分析结果
   */
  public static async getReturnTrends(
    params: {
      timeRange: { start: string; end: string };
      interval: 'daily' | 'weekly' | 'monthly';
      metrics: string[];
    },
    traceInfo: {
      tenantId: string;
      shopId: string;
      taskId: string;
      traceId: string;
      businessType: 'TOC' | 'TOB';
    }
  ): Promise<{
    timestamp: string;
    timeRange: { start: string; end: string };
    interval: string;
    trends: Array<{
      date: string;
      metrics: Record<string, number>;
    }>;
  }> {
    try {
      const timestamp = new Date().toISOString();
      const trends = [];
      
      // 生成趋势数据
      const startDate = new Date(params.timeRange.start);
      const endDate = new Date(params.timeRange.end);
      const currentDate = new Date(startDate);
      
      while (currentDate <= endDate) {
        const dateStr = currentDate.toISOString().split('T')[0];
        
        const metrics: Record<string, number> = {};
        if (params.metrics.includes('returnRate')) {
          metrics.returnRate = parseFloat((Math.random() * 10 + 2).toFixed(2));
        }
        if (params.metrics.includes('returnCount')) {
          metrics.returnCount = Math.floor(Math.random() * 50) + 5;
        }
        if (params.metrics.includes('returnCost')) {
          metrics.returnCost = parseFloat((Math.random() * 5000 + 1000).toFixed(2));
        }
        if (params.metrics.includes('salesImpact')) {
          metrics.salesImpact = parseFloat((Math.random() * 15 + 3).toFixed(2));
        }
        
        trends.push({
          date: dateStr,
          metrics,
        });
        
        // 增加时间间隔
        if (params.interval === 'daily') {
          currentDate.setDate(currentDate.getDate() + 1);
        } else if (params.interval === 'weekly') {
          currentDate.setDate(currentDate.getDate() + 7);
        } else if (params.interval === 'monthly') {
          currentDate.setMonth(currentDate.getMonth() + 1);
        }
      }
      
      return {
        timestamp,
        timeRange: params.timeRange,
        interval: params.interval,
        trends,
      };
    } catch (error) {
      console.error('Error getting return trends:', error);
      throw new Error('Failed to get return trends');
    }
  }
}
