212 lines
7.2 KiB
TypeScript
212 lines
7.2 KiB
TypeScript
import { NextRequest, NextResponse } from "next/server"
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import { DatabaseService } from "@/lib/services/database-service"
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const dbService = new DatabaseService()
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export async function GET(request: NextRequest) {
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try {
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// 獲取總用戶數
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const totalUsersResult = await dbService.query(`
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SELECT COUNT(*) as total FROM users WHERE is_active = TRUE
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`)
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const totalUsers = totalUsersResult[0]?.total || 0
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// 獲取今日活躍用戶數（今日有登入記錄的用戶）
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const today = new Date().toISOString().split('T')[0]
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const todayActiveUsersResult = await dbService.query(`
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SELECT COUNT(DISTINCT user_id) as count
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FROM activity_logs
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WHERE DATE(created_at) = ? AND action = 'login'
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`, [today])
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const todayActiveUsers = todayActiveUsersResult[0]?.count || 0
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// 獲取昨日活躍用戶數（用於比較）
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const yesterday = new Date(Date.now() - 24 * 60 * 60 * 1000).toISOString().split('T')[0]
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const yesterdayActiveUsersResult = await dbService.query(`
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SELECT COUNT(DISTINCT user_id) as count
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FROM activity_logs
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WHERE DATE(created_at) = ? AND action = 'login'
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`, [yesterday])
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const yesterdayActiveUsers = yesterdayActiveUsersResult[0]?.count || 0
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// 計算今日活躍用戶增長率
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const todayActiveGrowth = yesterdayActiveUsers > 0
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? ((todayActiveUsers - yesterdayActiveUsers) / yesterdayActiveUsers * 100).toFixed(1)
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: 0
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// 獲取平均評分
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const avgRatingResult = await dbService.query(`
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SELECT AVG(rating) as avg_rating FROM apps WHERE is_active = TRUE AND rating > 0
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`)
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const avgRating = avgRatingResult[0]?.avg_rating || 0
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// 獲取上週平均評分（用於比較）
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const lastWeek = new Date(Date.now() - 7 * 24 * 60 * 60 * 1000).toISOString().split('T')[0]
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const lastWeekRatingResult = await dbService.query(`
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SELECT AVG(rating) as avg_rating
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FROM apps
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WHERE is_active = TRUE AND rating > 0 AND created_at < ?
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`, [lastWeek])
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const lastWeekRating = lastWeekRatingResult[0]?.avg_rating || 0
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// 計算評分增長
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const ratingGrowth = lastWeekRating > 0
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? (avgRating - lastWeekRating).toFixed(1)
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: 0
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// 獲取應用總數
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const totalAppsResult = await dbService.query(`
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SELECT COUNT(*) as total FROM apps WHERE is_active = TRUE
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`)
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const totalApps = totalAppsResult[0]?.total || 0
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// 獲取本週新增應用數
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const weekStart = new Date(Date.now() - 7 * 24 * 60 * 60 * 1000).toISOString().split('T')[0]
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const newThisWeekResult = await dbService.query(`
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SELECT COUNT(*) as count
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FROM apps
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WHERE is_active = TRUE AND DATE(created_at) >= ?
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`, [weekStart])
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const newThisWeek = newThisWeekResult[0]?.count || 0
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// 獲取上月用戶數（用於比較）
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const lastMonth = new Date(Date.now() - 30 * 24 * 60 * 60 * 1000).toISOString().split('T')[0]
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const lastMonthUsersResult = await dbService.query(`
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SELECT COUNT(*) as total
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FROM users
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WHERE is_active = TRUE AND created_at < ?
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`, [lastMonth])
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const lastMonthUsers = lastMonthUsersResult[0]?.total || 0
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// 計算用戶增長率
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const userGrowth = lastMonthUsers > 0
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? ((totalUsers - lastMonthUsers) / lastMonthUsers * 100).toFixed(1)
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: 0
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// 獲取近7天的使用趨勢數據
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const dailyUsageData = []
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for (let i = 6; i >= 0; i--) {
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const date = new Date(Date.now() - i * 24 * 60 * 60 * 1000)
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const dateStr = date.toISOString().split('T')[0]
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const dayName = ["日", "一", "二", "三", "四", "五", "六"][date.getDay()]
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// 獲取當日活躍用戶數
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const dailyUsersResult = await dbService.query(`
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SELECT COUNT(DISTINCT user_id) as count
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FROM activity_logs
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WHERE DATE(created_at) = ? AND action IN ('login', 'view')
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`, [dateStr])
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const dailyUsers = dailyUsersResult[0]?.count || 0
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// 獲取當日會話數
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const dailySessionsResult = await dbService.query(`
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SELECT COUNT(*) as count
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FROM activity_logs
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WHERE DATE(created_at) = ? AND action = 'view'
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`, [dateStr])
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const dailySessions = dailySessionsResult[0]?.count || 0
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dailyUsageData.push({
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date: `${date.getMonth() + 1}/${date.getDate()}`,
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fullDate: date.toLocaleDateString("zh-TW"),
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dayName: dayName,
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users: dailyUsers,
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sessions: dailySessions,
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cpuPeak: Math.min(80, 40 + dailyUsers * 0.1), // 模擬CPU使用率
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avgCpu: Math.min(70, 30 + dailyUsers * 0.08),
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memoryPeak: Math.min(75, 35 + dailyUsers * 0.12),
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requests: dailySessions * 5 // 模擬請求數
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})
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}
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// 獲取應用類別分布
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const categoryDataResult = await dbService.query(`
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SELECT
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type as category,
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COUNT(*) as app_count,
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SUM(views_count) as total_views
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FROM apps
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WHERE is_active = TRUE
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GROUP BY type
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ORDER BY app_count DESC
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`)
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const totalAppCount = categoryDataResult.reduce((sum, item) => sum + item.app_count, 0)
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const categoryData = categoryDataResult.map((item, index) => {
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const colors = ["#3b82f6", "#ef4444", "#10b981", "#f59e0b", "#8b5cf6"]
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return {
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name: item.category,
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value: Math.round((item.app_count / totalAppCount) * 100),
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color: colors[index % colors.length],
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users: Math.round(item.total_views * 0.3), // 估算用戶數
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apps: item.app_count
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}
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})
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// 獲取熱門應用排行
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const topAppsResult = await dbService.query(`
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SELECT
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a.name,
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a.views_count as views,
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a.rating,
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a.type as category
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FROM apps a
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WHERE a.is_active = TRUE
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ORDER BY a.views_count DESC
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LIMIT 5
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`)
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const topApps = topAppsResult.map(app => ({
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name: app.name,
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views: app.views || 0,
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rating: parseFloat(app.rating) || 0,
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category: app.category
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}))
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// 獲取用戶滿意度數據
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const satisfactionResult = await dbService.query(`
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SELECT
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AVG(rating) as avg_rating,
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COUNT(*) as total_ratings
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FROM user_ratings
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WHERE created_at >= DATE_SUB(NOW(), INTERVAL 7 DAY)
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`)
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const satisfaction = satisfactionResult[0] || { avg_rating: 0, total_ratings: 0 }
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const satisfactionRate = satisfaction.avg_rating > 0
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? Math.round((satisfaction.avg_rating / 5) * 100)
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: 92 // 預設值
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return NextResponse.json({
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success: true,
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data: {
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// 關鍵指標
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totalUsers,
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todayActiveUsers,
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todayActiveGrowth: parseFloat(todayActiveGrowth),
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avgRating: parseFloat(avgRating.toFixed(1)),
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ratingGrowth: parseFloat(ratingGrowth),
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totalApps,
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newThisWeek,
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userGrowth: parseFloat(userGrowth),
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// 趨勢數據
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dailyUsageData,
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categoryData,
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topApps,
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// 滿意度數據
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satisfactionRate,
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weeklyFeedback: satisfaction.total_ratings || 0
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}
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})
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} catch (error) {
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console.error('獲取分析數據錯誤:', error)
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return NextResponse.json(
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{ success: false, error: '獲取分析數據時發生錯誤' },
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{ status: 500 }
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)
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}
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}
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