feat: report analysis with date aggregation and user filtering
- Implement date aggregation logic, sum multiple reports on same day - Add user filtering with multi-select Chip components - Fix IpcResult data unwrapping bug in frontend - Add loading state and empty state indicators - Update test cases to verify aggregation logic Fixes: - Timeline confusion: Now sorted by date ascending - Data duplication: Same-day data automatically aggregated - No filtering: Added user selector for filtering by users
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Misaka_Company
@@ -3,7 +3,7 @@ import { createLogger } from '../logger'
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const log = createLogger('ReportAnalyzer')
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/**
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* Parsed report data structure
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* Parsed report data structure - 单条报告记录
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*/
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export interface ParsedReportData {
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/** 报告日期 (从文件名或内容提取) */
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@@ -26,6 +26,30 @@ export interface ParsedReportData {
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durationSeconds: number
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}
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/**
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* Aggregated daily data - 按日期聚合后的数据
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*/
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export interface AggregatedDailyData {
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/** 日期 */
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date: string
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/** 处理订单数总和 */
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ordersProcessed: number
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/** 删除物料数总和 */
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materialsDeleted: number
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/** 跳过物料数总和 */
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materialsSkipped: number
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/** 错误数量总和 */
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errorCount: number
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/** 重试订单数总和 */
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retriedOrders: number
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/** 成功重试数总和 */
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successfulRetries: number
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/** 执行耗时平均值 (秒) */
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avgDurationSeconds: number
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/** 执行次数 */
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executionCount: number
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}
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/**
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* ReportAnalyzer - 解析和分析 ERP 物料清理执行报告
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*/
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@@ -85,12 +109,13 @@ export class ReportAnalyzer {
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}
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/**
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* 批量解析多个报告
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* 批量解析多个报告并按日期聚合
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* @param reports 报告元数据和内容列表
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* @returns 解析后的数据列表 (自动跳过解析失败的报告)
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* @returns 按日期聚合后的数据，按日期升序排序
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*/
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analyzeReports(reports: Array<{ content: string; filename?: string }>): ParsedReportData[] {
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const results: ParsedReportData[] = []
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analyzeReports(reports: Array<{ content: string; filename?: string }>): AggregatedDailyData[] {
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// 第一步：解析所有报告
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const parsedReports: ParsedReportData[] = []
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for (const report of reports) {
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const parsed = this.parseMarkdownReport(report.content)
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@@ -102,13 +127,153 @@ export class ReportAnalyzer {
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parsed.date = dateFromFilename
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}
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}
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results.push(parsed)
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parsedReports.push(parsed)
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} else {
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log.warn('Skipping report due to parse failure', { filename: report.filename })
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}
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}
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return results
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// 第二步：按日期聚合数据
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const dateMap = new Map<string, ParsedReportData[]>()
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for (const report of parsedReports) {
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const existing = dateMap.get(report.date) || []
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existing.push(report)
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dateMap.set(report.date, existing)
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}
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// 第三步：计算每天的聚合数据
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const aggregated: AggregatedDailyData[] = []
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for (const [date, reportsOnDate] of dateMap.entries()) {
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const totalOrdersProcessed = reportsOnDate.reduce((sum, r) => sum + r.ordersProcessed, 0)
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const totalMaterialsDeleted = reportsOnDate.reduce((sum, r) => sum + r.materialsDeleted, 0)
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const totalMaterialsSkipped = reportsOnDate.reduce((sum, r) => sum + r.materialsSkipped, 0)
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const totalErrorCount = reportsOnDate.reduce((sum, r) => sum + r.errorCount, 0)
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const totalRetriedOrders = reportsOnDate.reduce((sum, r) => sum + r.retriedOrders, 0)
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const totalSuccessfulRetries = reportsOnDate.reduce((sum, r) => sum + r.successfulRetries, 0)
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const totalDurationSeconds = reportsOnDate.reduce((sum, r) => sum + r.durationSeconds, 0)
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const executionCount = reportsOnDate.length
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aggregated.push({
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date,
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ordersProcessed: totalOrdersProcessed,
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materialsDeleted: totalMaterialsDeleted,
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materialsSkipped: totalMaterialsSkipped,
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errorCount: totalErrorCount,
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retriedOrders: totalRetriedOrders,
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successfulRetries: totalSuccessfulRetries,
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avgDurationSeconds: Math.round(totalDurationSeconds / executionCount),
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executionCount
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})
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}
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// 第四步：按日期升序排序（从早到晚），确保图表时间轴正确
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aggregated.sort((a, b) => {
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const dateA = new Date(a.date)
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const dateB = new Date(b.date)
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return dateA.getTime() - dateB.getTime()
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})
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return aggregated
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}
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/**
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* 获取所有唯一的用户名列表
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* @param reports 报告元数据和内容列表
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* @returns 按字母顺序排序的用户名列表
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*/
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getAllUsernames(reports: Array<{ content: string; filename?: string }>): string[] {
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const usernames = new Set<string>()
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for (const report of reports) {
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const parsed = this.parseMarkdownReport(report.content)
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if (parsed && parsed.username) {
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usernames.add(parsed.username)
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}
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}
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return Array.from(usernames).sort()
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}
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/**
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* 按用户筛选报告并返回聚合数据
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* @param reports 报告元数据和内容列表
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* @param selectedUsernames 选中的用户名列表
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* @returns 按日期聚合后的数据，仅包含选中用户的报告
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*/
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analyzeReportsByUsers(
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reports: Array<{ content: string; filename?: string }>,
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selectedUsernames: string[]
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): AggregatedDailyData[] {
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// 如果未选择任何用户，返回空数组
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if (selectedUsernames.length === 0) {
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return []
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}
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// 第一步：解析所有报告
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const parsedReports: ParsedReportData[] = []
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for (const report of reports) {
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const parsed = this.parseMarkdownReport(report.content)
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if (parsed) {
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// 如果有文件名，尝试从文件名提取日期覆盖
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if (report.filename) {
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const dateFromFilename = this.extractDateFromFilename(report.filename)
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if (dateFromFilename) {
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parsed.date = dateFromFilename
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}
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}
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parsedReports.push(parsed)
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} else {
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log.warn('Skipping report due to parse failure', { filename: report.filename })
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}
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}
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// 第二步：按选中的用户过滤
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const filteredReports = parsedReports.filter((report) =>
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selectedUsernames.includes(report.username)
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)
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// 第三步：按日期聚合过滤后的数据
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const dateMap = new Map<string, ParsedReportData[]>()
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for (const report of filteredReports) {
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const existing = dateMap.get(report.date) || []
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existing.push(report)
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dateMap.set(report.date, existing)
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}
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// 第四步：计算每天的聚合数据
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const aggregated: AggregatedDailyData[] = []
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for (const [date, reportsOnDate] of dateMap.entries()) {
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const totalOrdersProcessed = reportsOnDate.reduce((sum, r) => sum + r.ordersProcessed, 0)
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const totalMaterialsDeleted = reportsOnDate.reduce((sum, r) => sum + r.materialsDeleted, 0)
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const totalMaterialsSkipped = reportsOnDate.reduce((sum, r) => sum + r.materialsSkipped, 0)
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const totalErrorCount = reportsOnDate.reduce((sum, r) => sum + r.errorCount, 0)
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const totalRetriedOrders = reportsOnDate.reduce((sum, r) => sum + r.retriedOrders, 0)
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const totalSuccessfulRetries = reportsOnDate.reduce((sum, r) => sum + r.successfulRetries, 0)
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const totalDurationSeconds = reportsOnDate.reduce((sum, r) => sum + r.durationSeconds, 0)
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const executionCount = reportsOnDate.length
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aggregated.push({
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date,
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ordersProcessed: totalOrdersProcessed,
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materialsDeleted: totalMaterialsDeleted,
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materialsSkipped: totalMaterialsSkipped,
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errorCount: totalErrorCount,
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retriedOrders: totalRetriedOrders,
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successfulRetries: totalSuccessfulRetries,
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avgDurationSeconds: Math.round(totalDurationSeconds / executionCount),
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executionCount
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})
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}
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// 第五步：按日期升序排序（从早到晚），确保图表时间轴正确
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aggregated.sort((a, b) => {
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const dateA = new Date(a.date)
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const dateB = new Date(b.date)
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return dateA.getTime() - dateB.getTime()
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})
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return aggregated
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}
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/**
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