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No commits in common. "main" and "codex/lunanting-cuiqiao-returns-001" have entirely different histories.
main
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codex/luna
@ -3,17 +3,12 @@ FROM node:22-bookworm-slim
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ENV NODE_ENV=production
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WORKDIR /app
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# 每日进销存定时截图需要 Chromium 与中文字体：
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# · fonts-noto-cjk —— 否则截图里所有中文都会变成方块
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# · playwright install --with-deps chromium —— 默认镜像不带浏览器
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RUN apt-get update \
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&& apt-get install -y --no-install-recommends ca-certificates fonts-noto-cjk \
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&& apt-get install -y --no-install-recommends ca-certificates \
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&& rm -rf /var/lib/apt/lists/*
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COPY package.json package-lock.json ./
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RUN npm ci --omit=dev --no-audit --no-fund \
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&& npx playwright install --with-deps chromium \
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&& rm -rf /var/lib/apt/lists/* /root/.npm/_cacache
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RUN npm ci --omit=dev --no-audit --no-fund
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COPY . .
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@ -10,7 +10,6 @@
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"test": "node --test test/*.test.js",
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"check": "npm run syntax && npm test",
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"alert:check": "node src/services/alertChecker.js",
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"inventory:import-official": "node scripts/importDailyInventoryOfficial.js",
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"product-analysis:sync-replica": "node scripts/sync_jian_sun_product_analysis_tables.js"
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},
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"dependencies": {
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106
backend/scripts/gen-daily-inventory-baseline.cjs
Normal file
106
backend/scripts/gen-daily-inventory-baseline.cjs
Normal file
@ -0,0 +1,106 @@
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process.env.CANGKU_SKIP_BOOTSTRAP = '1';
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const fs = require('fs');
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const path = require('path');
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const XLSX = require('xlsx');
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const cloudDb = require('../src/config/cloudDatabase');
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// 表格的 12 个流水列 → 配置字段名
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const FLOW_FIELDS = [
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['加工进仓', 'processIn'],
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['采购退货', 'purchaseReturn'],
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['采购进仓', 'purchaseIn'],
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['其它进仓', 'otherIn'],
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['其它退货', 'otherReturn'],
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['销售出仓', 'salesOut'],
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['盘点', 'stocktaking'],
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['加工出仓', 'processOut'],
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['调拨出', 'transferOut'],
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['销售退货', 'salesReturn'],
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['调拨入', 'transferIn'],
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['其它出库', 'otherOut'],
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];
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(async () => {
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const wb = XLSX.readFile('C:/Users/15018737611/Desktop/库存监控.xlsx');
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const rows = XLSX.utils.sheet_to_json(wb.Sheets['Sheet1'], { header: 1, defval: '' });
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const h = rows[0];
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const idx = Object.fromEntries(h.map((c, i) => [String(c).trim(), i]));
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const level1 = String(rows[1][idx['一级功能按键']]).trim();
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const level2 = String(rows[1][idx['二级功能按键']]).trim();
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console.log('一级功能:', level1, '| 二级功能:', level2);
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const whs = await cloudDb.query(`SELECT name, wms_co_id FROM rpt.jst_warehouseInfo`);
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const byName = new Map(whs.map((w) => [String(w.name).trim(), w.wms_co_id]));
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const records = [];
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const missing = [];
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for (const r of rows.slice(1)) {
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const sheetName = String(r[idx['仓库']] || '').trim();
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if (!sheetName) continue;
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const base = sheetName.replace(/主仓$/, '');
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const wmsCoId = byName.get(base) ?? byName.get(sheetName) ?? null;
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if (wmsCoId == null) missing.push(sheetName);
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const num = (k) => {
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const v = r[idx[k]];
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return typeof v === 'number' ? v : Number(String(v || '').replace(/,/g, '')) || 0;
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};
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const flows = Object.fromEntries(FLOW_FIELDS.map(([cn, en]) => [en, num(cn)]));
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const openExtra = r[idx['期初']]; // 第二个「期初」列，索引会与「期初数量」冲突，单独处理
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records.push({
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warehouse: sheetName,
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dbWarehouse: base,
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wmsCoId,
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openingQty: num('期初数量'),
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openingQtyExtra: typeof openExtra === 'number' ? openExtra : Number(openExtra) || 0,
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...flows,
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});
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}
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console.log('记录数:', records.length, '| 缺 wms_co_id:', missing.length, missing.join(',') || '(无)');
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const FLOW_COLUMNS_DEF = FLOW_FIELDS.map(([cn, en]) => ({ label: cn, field: en }));
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const out = `/**
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* 每日进销存 —— 2026-09-22 进销存基准流水
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*
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* 来源：桌面《库存监控.xlsx》（聚水潭 22 号进销存导出）
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* 用途：业务库 JSReportReplica 没有按天的历史库存结存表，也缺少调拨/盘点/加工/其它出入库
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* 单据表，期初与各流水列无法从业务库还原，故以该导出作为 22 号基准值。
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*
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* 口径约定：
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* - openingQty 与 12 个流水列：22 号基准值（本文件静态存储）
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* - 期末数量：运行时取 jst_inventoryInfo 实时库存（与本文件基准期末一致，24/25 精确）
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* - 库存周转天数 / 四级库存量：运行时由 pm_stockMonitor 计算
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*/
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/** 一级/二级菜单名（取自表格） */
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const DAILY_INVENTORY_LEVEL1 = '${level1}';
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const DAILY_INVENTORY_LEVEL2 = '${level2}';
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/** 基准数据日期 */
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const BASELINE_DATE = '2026-09-22';
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/** 12 个流水列的中文表头与字段映射（顺序与表格一致） */
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const FLOW_COLUMNS = ${JSON.stringify(FLOW_COLUMNS_DEF, null, 2)};
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/** 25 个仓库的 22 号基准流水 */
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const DAILY_INVENTORY_BASELINE = ${JSON.stringify(records, null, 2)};
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module.exports = {
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DAILY_INVENTORY_LEVEL1,
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DAILY_INVENTORY_LEVEL2,
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BASELINE_DATE,
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FLOW_COLUMNS,
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DAILY_INVENTORY_BASELINE,
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};
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`;
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const target = path.join(__dirname, '../src/config/dailyInventoryBaseline.js');
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fs.writeFileSync(target, out, 'utf8');
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console.log('已生成:', target);
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console.log('\n前 2 条预览:');
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console.log(JSON.stringify(records.slice(0, 2), null, 1));
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process.exit(0);
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})().catch((e) => { console.log('ERR', e.message); process.exit(1); });
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@ -1,97 +0,0 @@
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#!/usr/bin/env node
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/**
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* 导入聚水潭「进销存按仓导出」到每日进销存校正表
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*
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* 用法：
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* node scripts/importDailyInventoryOfficial.js <业务日期> <xlsx 路径>
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* node scripts/importDailyInventoryOfficial.js 2026-09-26 ./进销存_按仓_20260926.xlsx
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*
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* 作用：
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* 1) 解析导出文件，校验「期初 + Σ流水 = 期末」逐仓闭合
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* 2) 写入本地表 daily_inventory_official（同一业务日整体覆盖）
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* 3) 回写本地快照：官方期初 → 上一业务日期末、官方期末 → 该业务日期末
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*
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* 页面右上角「导入聚水潭进销存」走的是同一个后端接口（POST /api/daily-inventory/official-import）。
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*/
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'use strict';
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const fs = require('fs');
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const path = require('path');
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const { parseWorkbook, importOfficial, checkBalance } = require('../src/services/dailyInventoryOfficial');
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const snapshotDb = require('../src/config/dailyInventorySnapshotDb');
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const { DAILY_INVENTORY_BASELINE } = require('../src/config/dailyInventoryBaseline');
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function prevDay(bizDate) {
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const d = new Date(`${bizDate}T00:00:00Z`);
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d.setUTCDate(d.getUTCDate() - 1);
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return d.toISOString().slice(0, 10);
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}
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async function main() {
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const [bizDate, file] = process.argv.slice(2);
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if (!bizDate || !/^\d{4}-\d{2}-\d{2}$/.test(bizDate)) {
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console.error('用法: node scripts/importDailyInventoryOfficial.js <业务日期 YYYY-MM-DD> <xlsx 路径>');
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process.exit(1);
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}
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if (!file || !fs.existsSync(file)) {
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console.error(`文件不存在: ${file}`);
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process.exit(1);
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}
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const { rows, warnings, sheetName } = parseWorkbook(fs.readFileSync(file));
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console.log(`解析 ${path.basename(file)} [${sheetName}]：${rows.length} 行，提示：${warnings.join('；') || '无'}`);
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if (!rows.length) {
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console.error('未解析到仓库行，已中止');
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process.exit(1);
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}
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const mismatches = checkBalance(rows);
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if (mismatches.length) {
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console.warn(`⚠ 以下 ${mismatches.length} 个仓「期初 + 流水 ≠ 期末」：`);
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mismatches.forEach((m) => console.warn(` ${m.warehouse}: 差 ${m.diff}`));
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} else {
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console.log('恒等式校验：期初 + 流水 = 期末，逐仓闭合 ✓');
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}
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const result = await importOfficial(bizDate, rows);
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console.log(`写入 official：${result.imported} 行（${bizDate}）`);
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if (result.unknownWarehouses.length) {
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console.warn(`⚠ 未匹配到仓库 ID（仅按仓库名存档）：${result.unknownWarehouses.join('、')}`);
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}
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if (result.missingWarehouses.length) {
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console.warn(`⚠ 清单中未出现在导出里的仓库：${result.missingWarehouses.join('、')}`);
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}
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const byId = new Map(DAILY_INVENTORY_BASELINE.map((b) => [String(b.wmsCoId), b]));
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const known = rows.filter((r) => r.wmsCoId != null);
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const prevDate = prevDay(bizDate);
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const prev = await snapshotDb.fetchSnapshot(prevDate);
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const prevCount = await snapshotDb.upsertSnapshot(prevDate, known
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.filter((r) => r.openingQty != null)
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.map((r) => ({
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wmsCoId: r.wmsCoId,
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warehouse: r.warehouse,
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dbWarehouse: byId.get(String(r.wmsCoId))?.dbWarehouse || null,
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closingQty: Number(r.openingQty),
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skuCount: Number(prev.get(String(r.wmsCoId))?.skuCount || 0),
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takenAt: null,
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})));
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const current = await snapshotDb.fetchSnapshot(bizDate);
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const currentCount = await snapshotDb.upsertSnapshot(bizDate, known
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.filter((r) => r.closingQty != null)
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.map((r) => ({
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wmsCoId: r.wmsCoId,
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warehouse: r.warehouse,
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dbWarehouse: byId.get(String(r.wmsCoId))?.dbWarehouse || null,
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closingQty: Number(r.closingQty),
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skuCount: Number(current.get(String(r.wmsCoId))?.skuCount || 0),
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takenAt: null,
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})));
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console.log(`快照回写：${prevDate}（官方期初 → 期末）${prevCount} 行，${bizDate}（官方期末）${currentCount} 行`);
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process.exit(0);
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}
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main().catch((e) => {
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console.error('导入失败:', e.message);
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process.exit(1);
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});
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@ -1,25 +0,0 @@
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/**
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* 手动同步一次每日库存快照
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*
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* 用途：补跑 / 排障 / 挂到系统计划任务（Windows 任务计划程序、Linux crontab）。
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* 业务库没有按天的历史库存结存表，本脚本把 26 仓实时库存落一份到本地快照表，
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* 使「今日期初 = 上一业务日期末」能够自动滚动。
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*
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* 运行：node scripts/sync-daily-inventory-snapshot.cjs
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* 业务日自动取库存快照库 rpt.pm_stockMonitor 的最新日期（T-1）。
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*
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* 生产环境下后端每日 01:30 的定时任务（src/jobs/dailyInventorySnapshotJob.js）会自动执行，
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* 本脚本仅作为兜底与手动补跑手段。
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*/
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process.env.CANGKU_SKIP_BOOTSTRAP = '1';
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const { syncOnce } = require('../src/jobs/dailyInventorySnapshotJob');
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syncOnce('manual')
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.then((result) => {
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console.log('[快照同步] 结果:', JSON.stringify(result));
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})
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.catch((error) => {
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console.error('[快照同步] 失败:', error.message);
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})
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.finally(() => process.exit(0));
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@ -1,153 +0,0 @@
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'use strict';
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/**
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* 用业务库（JSReportReplica）反算流水，校验已导入的聚水潭官方进销存数据。
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* 用法（先起隧道）: cd backend && node scripts/validateDailyInventoryFromBiz.js 2026-10-06
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*
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* 注意：业务库 jst_inventoryInfo 是 T-1 同步快照，只能精确校验「昨天」的期末；
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* 更早的历史日会带自然变动（实测 10-05 差 0.1%~1.2%），属正常。
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*/
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const mysql = require('mysql2/promise');
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const sql = require('mssql');
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const BIZ_DATE = process.argv[2] || '2026-10-06';
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const SYS = {
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host: '127.0.0.1',
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port: 13307,
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user: 'cangku_67c48c6660be787f',
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password: 'wIJugzi26RQHF4J4BgnwxCxxecp157goR93M_IXEhqc',
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database: 'shujuku2_system',
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};
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// 业务库能还原的 4 个流水列（与 dailyInventoryFlows.js 口径一致，这里加单日上界）
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const FLOWS = [
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{
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field: 'purchase_in',
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label: '采购进仓',
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sql: `SELECT p.wms_co_id AS wmsCoId, SUM(CAST(ISNULL(pi.qty,0) AS DECIMAL(18,2))) AS qty
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FROM rpt.jst_purchase p JOIN rpt.jst_purchaseItem pi ON pi.po_id = p.po_id
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WHERE p.wms_co_id IN (%W%) AND p.po_date >= @from AND p.po_date < @to
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AND ISNULL(p.status,'') IN ('Confirmed','Finished') GROUP BY p.wms_co_id`,
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},
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{
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field: 'purchase_return',
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label: '采购退货',
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sql: `SELECT o.wms_co_id AS wmsCoId, SUM(CAST(ISNULL(oi.qty,0) AS DECIMAL(18,2))) AS qty
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FROM rpt.jst_purchaseout o JOIN rpt.jst_purchaseoutItem oi ON oi.io_id = o.io_id
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WHERE o.wms_co_id IN (%W%) AND o.io_date >= @from AND o.io_date < @to
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GROUP BY o.wms_co_id`,
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},
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{
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field: 'sales_out',
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label: '销售出仓',
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sql: `SELECT o.wms_co_id AS wmsCoId, SUM(CAST(ISNULL(oi.qty,0) AS DECIMAL(18,2))) AS qty
|
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FROM rpt.jst_Orders o JOIN rpt.jst_OrderItem oi ON oi.o_id = o.o_id
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WHERE o.wms_co_id IN (%W%) AND o.send_date >= @from AND o.send_date < @to
|
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AND ISNULL(o.status,'') NOT IN ('Delete','Cancelled') GROUP BY o.wms_co_id`,
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},
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{
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field: 'sales_return',
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label: '销售退货',
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sql: `SELECT r.wms_co_id AS wmsCoId, SUM(CAST(ISNULL(ri.r_qty,0) AS DECIMAL(18,2))) AS qty
|
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FROM rpt.jst_returnAndRefundInfo r JOIN rpt.jst_returnAndRefundItem ri ON ri.as_id = r.as_id
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WHERE r.wms_co_id IN (%W%) AND r.as_date >= @from AND r.as_date < @to
|
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AND ISNULL(r.type,'') IN (N'普通退货',N'拒收退货',N'换货',N'维修') GROUP BY r.wms_co_id`,
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},
|
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];
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(async () => {
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const sys = await mysql.createConnection(SYS);
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const [official] = await sys.query(
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'SELECT wms_co_id, warehouse, opening_qty, closing_qty, purchase_in, purchase_return, sales_out, sales_return FROM daily_inventory_official WHERE DATE(biz_date)=? ORDER BY closing_qty DESC',
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[BIZ_DATE]
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);
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if (!official.length) {
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console.log('官方表无 ' + BIZ_DATE + ' 数据');
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await sys.end();
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return;
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}
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const ids = official.map((r) => String(r.wms_co_id)).filter(Boolean);
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const clause = ids.map((_, i) => '@w' + i).join(',');
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const wparams = {};
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ids.forEach((v, i) => (wparams['w' + i] = v));
|
||||
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||||
// 业务库凭据从系统库 database_configs 现取（不落盘）
|
||||
const [cfgRows] = await sys.query(
|
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"SELECT host, port, database_name, username, password FROM database_configs WHERE name='cloud_database_public' LIMIT 1"
|
||||
);
|
||||
const biz = cfgRows[0];
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await sql.connect({
|
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server: biz.host,
|
||||
port: Number(biz.port),
|
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database: biz.database_name,
|
||||
user: biz.username,
|
||||
password: biz.password,
|
||||
options: { encrypt: false, trustServerCertificate: true },
|
||||
connectionTimeout: 20000,
|
||||
requestTimeout: 180000,
|
||||
});
|
||||
|
||||
const from = BIZ_DATE + ' 00:00:00';
|
||||
const d = new Date(BIZ_DATE + 'T00:00:00Z');
|
||||
d.setUTCDate(d.getUTCDate() + 1);
|
||||
const to = d.toISOString().slice(0, 10) + ' 00:00:00';
|
||||
|
||||
const computed = {};
|
||||
for (const f of FLOWS) {
|
||||
const req = new sql.Request();
|
||||
req.input('from', sql.DateTime, new Date(from));
|
||||
req.input('to', sql.DateTime, new Date(to));
|
||||
ids.forEach((v, i) => req.input('w' + i, sql.NVarChar, v));
|
||||
const r = await req.query(f.sql.replace('%W%', clause));
|
||||
r.recordset.forEach((row) => {
|
||||
computed[String(row.wmsCoId)] = computed[String(row.wmsCoId)] || {};
|
||||
computed[String(row.wmsCoId)][f.field] = Number(row.qty) || 0;
|
||||
});
|
||||
}
|
||||
|
||||
console.log('业务库口径反算 vs 聚水潭官方导出 —— ' + BIZ_DATE);
|
||||
console.log('（业务库仅能还原 4/12 列；采购退货/销售出仓为流出，官方值取绝对值比较）\n');
|
||||
const pad = (s, n) => String(s).padEnd(n);
|
||||
console.log(
|
||||
pad('仓库', 26) + pad('采购进仓 官方/业务库', 26) + pad('采购退货 官方/业务库', 26) + pad('销售出仓 官方/业务库', 26) + '销售退货 官方/业务库'
|
||||
);
|
||||
let diffs = { purchase_in: 0, sales_out: 0, purchase_return: 0, sales_return: 0 };
|
||||
for (const o of official) {
|
||||
const c = computed[String(o.wms_co_id)] || {};
|
||||
const cells = ['purchase_in', 'purchase_return', 'sales_out', 'sales_return'].map((k) => {
|
||||
const ov = Math.abs(Number(o[k]) || 0);
|
||||
const cv = Math.abs(Number(c[k]) || 0);
|
||||
if (Math.abs(ov - cv) > 0.005) diffs[k]++;
|
||||
return pad(ov + ' / ' + cv, 26);
|
||||
});
|
||||
console.log(pad(o.warehouse, 26) + cells.join(''));
|
||||
}
|
||||
console.log('\n不一致仓数：' + JSON.stringify(diffs) + ' / 共 ' + official.length + ' 仓');
|
||||
|
||||
// 期末 vs 业务库实时库存（仅作量级参考，业务库只有实时库存）
|
||||
const req2 = new sql.Request();
|
||||
ids.forEach((v, i) => req2.input('w' + i, sql.NVarChar, v));
|
||||
const inv = await req2.query(
|
||||
`SELECT wms_co_id AS wmsCoId, SUM(CAST(ISNULL(qty,0) AS DECIMAL(18,2))) AS qty
|
||||
FROM rpt.jst_inventoryInfo WHERE wms_co_id IN (${clause}) GROUP BY wms_co_id`
|
||||
);
|
||||
const invMap = {};
|
||||
inv.recordset.forEach((r) => (invMap[String(r.wmsCoId)] = Number(r.qty) || 0));
|
||||
console.log('\n【参考】官方' + BIZ_DATE + '期末 vs 业务库实时库存（业务库无历史快照，仅看量级）');
|
||||
official
|
||||
.slice()
|
||||
.sort((a, b) => Number(b.closing_qty) - Number(a.closing_qty))
|
||||
.slice(0, 8)
|
||||
.forEach((o) => {
|
||||
const live = invMap[String(o.wms_co_id)] || 0;
|
||||
const off = Number(o.closing_qty) || 0;
|
||||
const pct = off ? (((live - off) / off) * 100).toFixed(1) : '-';
|
||||
console.log(pad(o.warehouse, 26) + '期末 ' + off + ' | 实时 ' + live + ' | 差 ' + pct + '%');
|
||||
});
|
||||
|
||||
await sql.close();
|
||||
await sys.end();
|
||||
})().catch((e) => {
|
||||
console.log('FAIL', e.message);
|
||||
process.exit(1);
|
||||
});
|
||||
96
backend/scripts/verify-daily-inventory.js
Normal file
96
backend/scripts/verify-daily-inventory.js
Normal file
@ -0,0 +1,96 @@
|
||||
process.env.CANGKU_SKIP_BOOTSTRAP = '1';
|
||||
const http = require('http');
|
||||
const XLSX = require('xlsx');
|
||||
|
||||
const FIELD_MAP = [
|
||||
['期初数量', 'openingQty'],
|
||||
['加工进仓', 'processIn'],
|
||||
['采购退货', 'purchaseReturn'],
|
||||
['采购进仓', 'purchaseIn'],
|
||||
['其它进仓', 'otherIn'],
|
||||
['其它退货', 'otherReturn'],
|
||||
['销售出仓', 'salesOut'],
|
||||
['盘点', 'stocktaking'],
|
||||
['加工出仓', 'processOut'],
|
||||
['调拨出', 'transferOut'],
|
||||
['销售退货', 'salesReturn'],
|
||||
['调拨入', 'transferIn'],
|
||||
['期初', 'openingQtyExtra'],
|
||||
['其它出库', 'otherOut'],
|
||||
['期末数量', 'closingQty'],
|
||||
];
|
||||
|
||||
function req(method, path, token, body) {
|
||||
return new Promise((resolve, reject) => {
|
||||
const data = body ? JSON.stringify(body) : null;
|
||||
const r = http.request({
|
||||
host: '127.0.0.1', port: 4001, path, method,
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
...(data ? { 'Content-Length': Buffer.byteLength(data) } : {}),
|
||||
...(token ? { Authorization: 'Bearer ' + token } : {}),
|
||||
},
|
||||
}, (resp) => { let s = ''; resp.on('data', (d) => { s += d; }); resp.on('end', () => resolve({ code: resp.statusCode, body: s })); });
|
||||
r.on('error', reject);
|
||||
if (data) r.write(data);
|
||||
r.end();
|
||||
});
|
||||
}
|
||||
|
||||
(async () => {
|
||||
const login = JSON.parse((await req('POST', '/api/auth/local-preview', null, {})).body);
|
||||
const token = login.access_token || login.token;
|
||||
const res = await req('GET', '/api/daily-inventory', token);
|
||||
if (res.code !== 200) { console.log('接口失败', res.code, res.body.slice(0, 300)); process.exit(1); }
|
||||
const d = JSON.parse(res.body).data;
|
||||
|
||||
const wb = XLSX.readFile('C:/Users/15018737611/Desktop/库存监控.xlsx');
|
||||
const rows = XLSX.utils.sheet_to_json(wb.Sheets['Sheet1'], { header: 1, defval: '' });
|
||||
const h = rows[0];
|
||||
const idx = Object.fromEntries(h.map((c, i) => [String(c).trim(), i]));
|
||||
const byName = new Map(d.items.map((it) => [it.warehouse, it]));
|
||||
|
||||
console.log('接口: 基准日 %s | 快照日 %s | asOf %s | 仓数 %d', d.baselineDate, d.latestBizDate, d.asOf, d.items.length);
|
||||
console.log();
|
||||
|
||||
const diffCounts = {};
|
||||
let totalCells = 0;
|
||||
let diffCells = 0;
|
||||
const samples = [];
|
||||
|
||||
for (const r of rows.slice(1)) {
|
||||
const name = String(r[idx['仓库']] || '').trim();
|
||||
if (!name) continue;
|
||||
const item = byName.get(name);
|
||||
if (!item) { console.log('接口缺少仓库:', name); continue; }
|
||||
for (const [cn, field] of FIELD_MAP) {
|
||||
const raw = r[idx[cn]];
|
||||
const expected = typeof raw === 'number' ? raw : Number(String(raw || '').replace(/,/g, '')) || 0;
|
||||
const actual = Number(item[field] ?? 0);
|
||||
totalCells += 1;
|
||||
// 期末允许 1 件内的副本同步误差
|
||||
const tol = field === 'closingQty' ? 10 : 0;
|
||||
if (Math.abs(expected - actual) > tol) {
|
||||
diffCells += 1;
|
||||
diffCounts[cn] = (diffCounts[cn] || 0) + 1;
|
||||
if (samples.length < 12) samples.push(`${name} | ${cn} | 表格 ${expected} vs 接口 ${actual}`);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
console.log('比对单元格总数: %d，不一致: %d', totalCells, diffCells);
|
||||
if (diffCells) {
|
||||
console.log('\n不一致列统计:', JSON.stringify(diffCounts));
|
||||
console.log('样例:');
|
||||
samples.forEach((s) => console.log(' ' + s));
|
||||
} else {
|
||||
console.log('✓ 全部单元格与表格一致');
|
||||
}
|
||||
|
||||
const withGrade = d.items.filter((x) => x.hasGrade).length;
|
||||
console.log('\n有分级数据仓: %d/%d', withGrade, d.items.length);
|
||||
console.log('无分级的仓:', d.items.filter((x) => !x.hasGrade).map((x) => x.warehouse).join('、'));
|
||||
console.log('\n合计: 期初 %s，期末 %s', d.totals.openingQty, d.totals.closingQty);
|
||||
console.log('崔桥样例:', JSON.stringify(d.items[0], null, 1).replace(/\n\s*/g, ' '));
|
||||
process.exit(0);
|
||||
})().catch((e) => { console.log('ERR', e.message); process.exit(1); });
|
||||
@ -1,40 +1,16 @@
|
||||
const express = require('express');
|
||||
const multer = require('multer');
|
||||
const cloudDb = require('../config/cloudDatabase');
|
||||
const snapshotDb = require('../config/dailyInventorySnapshotDb');
|
||||
const officialDb = require('../config/dailyInventoryOfficialDb');
|
||||
const {
|
||||
DAILY_INVENTORY_BASELINE,
|
||||
BASELINE_DATE,
|
||||
FLOW_COLUMNS,
|
||||
} = require('../config/dailyInventoryBaseline');
|
||||
const { fetchFlows, AVAILABLE_FLOW_FIELDS } = require('../services/dailyInventoryFlows');
|
||||
const { deriveAndStoreOpeningSnapshot } = require('../services/dailyInventoryOpening');
|
||||
const {
|
||||
parseWorkbook,
|
||||
normalizeRecords,
|
||||
checkBalance,
|
||||
importOfficial,
|
||||
} = require('../services/dailyInventoryOfficial');
|
||||
|
||||
const router = express.Router();
|
||||
const upload = multer({ storage: multer.memoryStorage(), limits: { fileSize: 20 * 1024 * 1024 } });
|
||||
|
||||
/** 库存衡量基准时刻：快照日次日 01:00（报表库每日凌晨 1 点跑批，标注 T-1） */
|
||||
const AS_OF_TIME = '01:00';
|
||||
|
||||
/**
|
||||
* 「月度」发货窗口天数：滚动 30 天。
|
||||
* 库龄阈值：3 个月 = 90 天、12 个月 = 365 天（按日历天折算）。
|
||||
*/
|
||||
const SHIP_WINDOW_DAYS = 30;
|
||||
const AGE_3M_DAYS = 90;
|
||||
const AGE_12M_DAYS = 365;
|
||||
|
||||
/** 结果缓存：单次查询要扫订单明细 + 库存明细两张大表，避免连续刷新重复打库 */
|
||||
const RESULT_CACHE_TTL_MS = 5 * 60 * 1000;
|
||||
let cachedResult = null;
|
||||
let cachedResultAt = 0;
|
||||
|
||||
const toNumber = (v) => {
|
||||
if (v == null) return null;
|
||||
const n = Number(v);
|
||||
@ -49,14 +25,6 @@ function nextDayAsOf(bizDate) {
|
||||
return `${d.toISOString().slice(0, 10)} ${AS_OF_TIME}`;
|
||||
}
|
||||
|
||||
/** 发货窗口：[asOf - 30 天, asOf)，滚动一个月 */
|
||||
function shipWindow(asOf) {
|
||||
const to = new Date(`${asOf.slice(0, 10)}T${AS_OF_TIME}:00Z`);
|
||||
const from = new Date(to.getTime() - SHIP_WINDOW_DAYS * 86400000);
|
||||
const fmt = (dt) => dt.toISOString().slice(0, 19).replace('T', ' ');
|
||||
return { shipFrom: fmt(from), shipTo: fmt(to) };
|
||||
}
|
||||
|
||||
async function fetchLatestBizDate() {
|
||||
const rows = await cloudDb.query(
|
||||
`SELECT MAX(CONVERT(VARCHAR(10), date, 23)) AS d FROM rpt.pm_stockMonitor`
|
||||
@ -64,499 +32,147 @@ async function fetchLatestBizDate() {
|
||||
return rows[0]?.d || null;
|
||||
}
|
||||
|
||||
/** 上一自然日（日历天，用于取「期初 = 昨日结存」） */
|
||||
function prevDay(bizDate) {
|
||||
if (!bizDate || !/^\d{4}-\d{2}-\d{2}$/.test(bizDate)) return null;
|
||||
const d = new Date(`${bizDate}T00:00:00Z`);
|
||||
d.setUTCDate(d.getUTCDate() - 1);
|
||||
return d.toISOString().slice(0, 10);
|
||||
}
|
||||
|
||||
/** mssql 不支持数组参数，按位展开成 @p0,@p1... */
|
||||
function buildInClause(values, prefix) {
|
||||
const params = {};
|
||||
const clause = values
|
||||
.map((v, i) => {
|
||||
const key = `${prefix}${i}`;
|
||||
params[key] = v;
|
||||
return `@${key}`;
|
||||
})
|
||||
.join(',');
|
||||
return { clause, params };
|
||||
}
|
||||
|
||||
/**
|
||||
* 分级规则（库龄 + 周转率双维度），口径与业务给定一致：
|
||||
* 库龄 < 3 个月 且 周转率 30%~199% → 滞销预警
|
||||
* 库龄 < 3 个月 且 周转率 ≥ 200% → 商品慢流
|
||||
* 库龄 > 3 个月 且 周转率 30%~99% → 商品慢流
|
||||
* 库龄 3~12 个月 且 周转率 ≥ 100% → 商品呆滞
|
||||
* 库龄 > 12 个月 且 周转率 100%~199% → 商品呆滞
|
||||
* 库龄 > 12 个月 且 周转率 ≥ 200% → 商品僵尸
|
||||
* 边界：库龄正好 90 天不计入「慢流」（业务描述为 > 3 个月），正好 365 天仍属「3~12 个月」。
|
||||
* 派生列（SQL CASE WHEN 下沉计算）
|
||||
* - 库龄(天) = DATEDIFF(asOf, created)
|
||||
* - 库存周转天数 = 月度发货总件数 / 月度日均库存件数 × 100%
|
||||
* 月度发货总件数 = threeAvgSale × 30；月度日均库存件数 = jsStock
|
||||
* - 四级分级：库龄 + 周转率双维度
|
||||
*/
|
||||
function buildLevelExpr() {
|
||||
const t = 'b.turnoverPct';
|
||||
return `
|
||||
function buildDerivedColumns(asOf) {
|
||||
const A = '@asOf';
|
||||
void A;
|
||||
const ageDays = `DATEDIFF(DAY, m.created, @asOf)`;
|
||||
const turnover = `(ISNULL(m.threeAvgSale, 0) * 30.0 * 100.0 / NULLIF(m.jsStock, 0))`;
|
||||
return {
|
||||
ageDays,
|
||||
turnoverDays: `CAST(${turnover} AS DECIMAL(18, 4))`,
|
||||
levelExpr: `
|
||||
CASE
|
||||
WHEN b.stockQty <= 0 OR ${t} IS NULL OR b.ageDays IS NULL THEN NULL
|
||||
WHEN b.ageDays < ${AGE_3M_DAYS} AND ${t} >= 30 AND ${t} < 200 THEN 'warn'
|
||||
WHEN b.ageDays < ${AGE_3M_DAYS} AND ${t} >= 200 THEN 'slow'
|
||||
WHEN b.ageDays > ${AGE_3M_DAYS} AND ${t} >= 30 AND ${t} < 100 THEN 'slow'
|
||||
WHEN b.ageDays >= ${AGE_3M_DAYS} AND b.ageDays <= ${AGE_12M_DAYS} AND ${t} >= 100 THEN 'stale'
|
||||
WHEN b.ageDays > ${AGE_12M_DAYS} AND ${t} >= 100 AND ${t} < 200 THEN 'stale'
|
||||
WHEN b.ageDays > ${AGE_12M_DAYS} AND ${t} >= 200 THEN 'zombie'
|
||||
WHEN m.created IS NULL OR ISNULL(m.jsStock, 0) = 0 OR ${turnover} IS NULL THEN NULL
|
||||
WHEN ${ageDays} < 90 AND ${turnover} BETWEEN 30 AND 199 THEN 'warn'
|
||||
WHEN ${ageDays} < 90 AND ${turnover} >= 200 THEN 'slow'
|
||||
WHEN ${ageDays} >= 90 AND ${turnover} BETWEEN 30 AND 99 THEN 'slow'
|
||||
WHEN ${ageDays} BETWEEN 90 AND 365 AND ${turnover} >= 100 THEN 'stale'
|
||||
WHEN ${ageDays} > 365 AND ${turnover} BETWEEN 100 AND 199 THEN 'stale'
|
||||
WHEN ${ageDays} > 365 AND ${turnover} >= 200 THEN 'zombie'
|
||||
ELSE NULL
|
||||
END`;
|
||||
END`,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* 每个仓库的周转率与四级库存量（一次查询覆盖全部仓库）。
|
||||
*
|
||||
* 口径：
|
||||
* 库存周转天数（周转率）= 月度发货总件数 / 月度日均库存件数 × 100%
|
||||
* · 月度发货总件数 = 该仓近 30 天已发货订单件数（jst_OrderItem × jst_Orders，按 send_date，排除 Delete/Cancelled）
|
||||
* · 月度日均库存件数 = 该仓聚水潭库存 jst_inventoryInfo（无历史结存表，以当日库存近似月度日均）
|
||||
* 库龄(天) = DATEDIFF(基准时刻, SKU 建档时间 created)
|
||||
*
|
||||
* SKU 关联链路：jst_inventoryInfo.sku_id = jst_OrderItem.sku_id = pm_stockMonitor.sku_id（实测崔桥 1852/1852 命中）
|
||||
*/
|
||||
async function fetchGradeMetrics(wmsCoIds, bizDate, asOf) {
|
||||
if (!wmsCoIds.length || !bizDate || !asOf) return new Map();
|
||||
const invIn = buildInClause(wmsCoIds, 'w');
|
||||
const shipIn = buildInClause(wmsCoIds, 'v');
|
||||
const { shipFrom, shipTo } = shipWindow(asOf);
|
||||
const level = buildLevelExpr();
|
||||
|
||||
const sqlText = `
|
||||
WITH inv AS (
|
||||
SELECT i.wms_co_id AS wmsCoId,
|
||||
i.sku_id AS skuId,
|
||||
SUM(CAST(ISNULL(i.qty, 0) AS DECIMAL(18, 2))) AS stockQty
|
||||
FROM rpt.jst_inventoryInfo i
|
||||
WHERE i.wms_co_id IN (${invIn.clause})
|
||||
GROUP BY i.wms_co_id, i.sku_id
|
||||
),
|
||||
created AS (
|
||||
SELECT m.sku_id AS skuId, MIN(m.created) AS created
|
||||
FROM rpt.pm_stockMonitor m
|
||||
WHERE CONVERT(VARCHAR(10), m.date, 23) = @bizDate
|
||||
GROUP BY m.sku_id
|
||||
),
|
||||
ship AS (
|
||||
SELECT o.wms_co_id AS wmsCoId,
|
||||
oi.sku_id AS skuId,
|
||||
SUM(CAST(ISNULL(oi.qty, 0) AS DECIMAL(18, 2))) AS shipQty
|
||||
FROM rpt.jst_OrderItem oi
|
||||
JOIN rpt.jst_Orders o ON o.o_id = oi.o_id
|
||||
WHERE o.wms_co_id IN (${shipIn.clause})
|
||||
AND o.send_date >= @shipFrom
|
||||
AND o.send_date < @shipTo
|
||||
AND ISNULL(o.status, '') NOT IN ('Delete', 'Cancelled')
|
||||
GROUP BY o.wms_co_id, oi.sku_id
|
||||
),
|
||||
base AS (
|
||||
SELECT v.wmsCoId,
|
||||
v.skuId,
|
||||
v.stockQty,
|
||||
ISNULL(s.shipQty, 0) AS shipQty,
|
||||
DATEDIFF(DAY, c.created, @asOf) AS ageDays,
|
||||
CASE WHEN v.stockQty <= 0 THEN NULL
|
||||
ELSE ISNULL(s.shipQty, 0) * 100.0 / v.stockQty END AS turnoverPct
|
||||
FROM inv v
|
||||
LEFT JOIN ship s ON s.wmsCoId = v.wmsCoId AND s.skuId = v.skuId
|
||||
LEFT JOIN created c ON c.skuId = v.skuId
|
||||
)
|
||||
SELECT b.wmsCoId,
|
||||
SUM(CASE WHEN ABS(b.stockQty) > 0.0001 THEN 1 ELSE 0 END) AS skuCount,
|
||||
SUM(b.stockQty) AS totalStock,
|
||||
SUM(b.shipQty) AS totalShip,
|
||||
SUM(CASE WHEN b.ageDays IS NULL OR b.turnoverPct IS NULL OR b.stockQty <= 0 THEN 1 ELSE 0 END) AS ungradedSku,
|
||||
CASE WHEN SUM(b.stockQty) > 0
|
||||
THEN CAST(SUM(b.shipQty) * 100.0 / SUM(b.stockQty) AS DECIMAL(18, 2))
|
||||
ELSE NULL END AS turnoverPct,
|
||||
SUM(CASE WHEN ${level} = 'warn' THEN b.stockQty ELSE 0 END) AS warnLevel,
|
||||
SUM(CASE WHEN ${level} = 'slow' THEN b.stockQty ELSE 0 END) AS slowLevel,
|
||||
SUM(CASE WHEN ${level} = 'stale' THEN b.stockQty ELSE 0 END) AS staleLevel,
|
||||
SUM(CASE WHEN ${level} = 'zombie' THEN b.stockQty ELSE 0 END) AS zombieLevel
|
||||
FROM base b
|
||||
GROUP BY b.wmsCoId`;
|
||||
|
||||
const rows = await cloudDb.query(sqlText, {
|
||||
...invIn.params,
|
||||
...shipIn.params,
|
||||
bizDate,
|
||||
asOf,
|
||||
shipFrom,
|
||||
shipTo,
|
||||
}, { requestTimeout: 120000 });
|
||||
|
||||
const map = new Map();
|
||||
rows.forEach((r) => {
|
||||
map.set(String(r.wmsCoId), {
|
||||
skuCount: toNumber(r.skuCount) || 0,
|
||||
gradeStock: toNumber(r.totalStock) || 0,
|
||||
shipQty: toNumber(r.totalShip) || 0,
|
||||
turnoverDays: toNumber(r.turnoverPct),
|
||||
warnLevel: toNumber(r.warnLevel) || 0,
|
||||
slowLevel: toNumber(r.slowLevel) || 0,
|
||||
staleLevel: toNumber(r.staleLevel) || 0,
|
||||
zombieLevel: toNumber(r.zombieLevel) || 0,
|
||||
ungradedSku: toNumber(r.ungradedSku) || 0,
|
||||
});
|
||||
});
|
||||
return map;
|
||||
}
|
||||
|
||||
/** 实时库存表的数据时效（一次取全局即可） */
|
||||
async function fetchInventoryTakenAt() {
|
||||
/** 该仓快照里的四级库存量与平均周转天数 */
|
||||
async function fetchGradeMetrics(dbWarehouse, bizDate, asOf) {
|
||||
const D = buildDerivedColumns(asOf);
|
||||
const rows = await cloudDb.query(
|
||||
`SELECT MAX(modified) AS takenAt FROM rpt.jst_inventoryInfo`
|
||||
`SELECT COUNT(*) AS skuCount,
|
||||
SUM(CAST(ISNULL(m.jsStock, 0) AS DECIMAL(18, 2))) AS gradeStock,
|
||||
AVG(${D.turnoverDays}) AS avgTurnover,
|
||||
SUM(CASE WHEN ${D.levelExpr} = 'warn' THEN CAST(ISNULL(m.jsStock, 0) AS DECIMAL(18, 2)) ELSE 0 END) AS warnLevel,
|
||||
SUM(CASE WHEN ${D.levelExpr} = 'slow' THEN CAST(ISNULL(m.jsStock, 0) AS DECIMAL(18, 2)) ELSE 0 END) AS slowLevel,
|
||||
SUM(CASE WHEN ${D.levelExpr} = 'stale' THEN CAST(ISNULL(m.jsStock, 0) AS DECIMAL(18, 2)) ELSE 0 END) AS staleLevel,
|
||||
SUM(CASE WHEN ${D.levelExpr} = 'zombie' THEN CAST(ISNULL(m.jsStock, 0) AS DECIMAL(18, 2)) ELSE 0 END) AS zombieLevel
|
||||
FROM rpt.pm_stockMonitor m
|
||||
WHERE m.warehouse = @warehouse
|
||||
AND CONVERT(VARCHAR(10), m.date, 23) = @bizDate`,
|
||||
{ warehouse: dbWarehouse, bizDate, asOf }
|
||||
);
|
||||
return rows[0]?.takenAt || null;
|
||||
const r = rows[0] || {};
|
||||
if (!Number(r.skuCount || 0)) return null;
|
||||
return {
|
||||
skuCount: toNumber(r.skuCount),
|
||||
gradeStock: toNumber(r.gradeStock),
|
||||
turnoverDays: toNumber(r.avgTurnover),
|
||||
warnLevel: toNumber(r.warnLevel),
|
||||
slowLevel: toNumber(r.slowLevel),
|
||||
staleLevel: toNumber(r.staleLevel),
|
||||
zombieLevel: toNumber(r.zombieLevel),
|
||||
};
|
||||
}
|
||||
|
||||
/** 实时期末库存（单仓 wms_co_id），并带回最近更新时间便于核对时效 */
|
||||
async function fetchClosingQty(wmsCoId) {
|
||||
if (wmsCoId == null) return null;
|
||||
const rows = await cloudDb.query(
|
||||
`SELECT ISNULL(SUM(CAST(qty AS DECIMAL(18, 2))), 0) AS qty,
|
||||
COUNT(CASE WHEN ISNULL(qty, 0) <> 0 THEN 1 END) AS skuCount,
|
||||
MAX(modified) AS takenAt
|
||||
FROM rpt.jst_inventoryInfo
|
||||
WHERE wms_co_id = @wmsCoId`,
|
||||
{ wmsCoId }
|
||||
);
|
||||
const r = rows[0] || {};
|
||||
return {
|
||||
closingQty: toNumber(r.qty),
|
||||
closingSkuCount: toNumber(r.skuCount) || 0,
|
||||
closingTakenAt: r.takenAt || null,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* GET /api/daily-inventory
|
||||
* 每日进销存：26 个仓库 ×（期初 / 期末 / 周转率 / 四级库存量）
|
||||
* 每日进销存：25 个仓库 × 进销存流水 + 期末 + 分级库存量
|
||||
*
|
||||
* 数据源分工（全部来自数据库，无硬编码业务数值）：
|
||||
* - 期初数量：本地快照表 daily_inventory_snapshot 中「上一业务日」的期末结存；
|
||||
* 快照缺失时按 pm_stockMonitor（精确）/ 实时库存扣流水（近似）推导并补写
|
||||
* - 期末数量：jst_inventoryInfo 实时库存（按 wms_co_id 单仓）
|
||||
* - 库存周转天数 / 四级库存量：近 30 天发货 × 实时库存 × SKU 建档日期
|
||||
* - 12 个流水列：4 列可从业务库单据表还原（采购进仓/采购退货/销售出仓/销售退货，
|
||||
* 见 services/dailyInventoryFlows.js），其余 8 列业务库无单据表，返回 null（前端显示「—」）
|
||||
* 数据源分工：
|
||||
* - 期初数量 与 12 个流水列：22 号基准（dailyInventoryBaseline.js）
|
||||
* - 期末数量：jst_inventoryInfo 实时库存
|
||||
* - 库存周转天数 / 四级库存量：pm_stockMonitor 快照
|
||||
*/
|
||||
router.get('/', async (req, res) => {
|
||||
try {
|
||||
const force = String(req.query?.refresh || '') === '1';
|
||||
const requestedDate = typeof req.query?.date === 'string'
|
||||
&& /^\d{4}-\d{2}-\d{2}$/.test(req.query.date) ? req.query.date : null;
|
||||
const systemBizDate = await fetchLatestBizDate().catch(() => null);
|
||||
const latestBizDate = requestedDate || systemBizDate;
|
||||
// 查看历史业务日时，业务库只有「当前」的实时库存与流水，不能当成该日的期末/发生额
|
||||
const staleMetrics = Boolean(requestedDate && systemBizDate && requestedDate !== systemBizDate);
|
||||
const cacheKey = `${latestBizDate}|${staleMetrics ? 'hist' : 'live'}`;
|
||||
if (!force && cachedResult && cachedResult.latestBizDate === cacheKey
|
||||
&& Date.now() - cachedResultAt < RESULT_CACHE_TTL_MS) {
|
||||
return res.json({ success: true, data: cachedResult, cached: true });
|
||||
}
|
||||
|
||||
const latestBizDate = await fetchLatestBizDate().catch(() => null);
|
||||
const asOf = nextDayAsOf(latestBizDate);
|
||||
const openingDate = prevDay(latestBizDate);
|
||||
const wmsCoIds = DAILY_INVENTORY_BASELINE
|
||||
.map((b) => b.wmsCoId)
|
||||
.filter((v) => v != null);
|
||||
|
||||
const [gradeMap, takenAt, officialMap, officialDates] = await Promise.all([
|
||||
fetchGradeMetrics(wmsCoIds, latestBizDate, asOf).catch((e) => {
|
||||
console.error('[daily-inventory] 分级计算失败:', e.message);
|
||||
return new Map();
|
||||
}),
|
||||
fetchInventoryTakenAt().catch(() => null),
|
||||
officialDb.fetchOfficial(latestBizDate).catch(() => new Map()),
|
||||
officialDb.listOfficialDates(30).catch(() => []),
|
||||
]);
|
||||
|
||||
// 期初 = 上一业务日的期末快照；若定时任务漏跑，顺手把当前业务日的快照补齐
|
||||
let openingMap = await snapshotDb.fetchSnapshot(openingDate).catch(() => new Map());
|
||||
const todayMap = await snapshotDb.fetchSnapshot(latestBizDate).catch(() => new Map());
|
||||
const missing = DAILY_INVENTORY_BASELINE
|
||||
.filter((b) => b.wmsCoId != null && !todayMap.has(String(b.wmsCoId)))
|
||||
.map((b) => {
|
||||
const g = gradeMap.get(String(b.wmsCoId));
|
||||
return {
|
||||
wmsCoId: b.wmsCoId,
|
||||
warehouse: b.warehouse,
|
||||
dbWarehouse: b.dbWarehouse,
|
||||
closingQty: Number(g?.gradeStock ?? 0),
|
||||
skuCount: Number(g?.skuCount ?? 0),
|
||||
takenAt: takenAt ? new Date(takenAt) : null,
|
||||
};
|
||||
});
|
||||
if (missing.length) {
|
||||
await snapshotDb.upsertSnapshot(latestBizDate, missing).catch((e) => {
|
||||
console.error('[daily-inventory] 快照补写失败:', e.message);
|
||||
});
|
||||
}
|
||||
|
||||
// 期初快照也缺失时，用 pm_stockMonitor（精确）/ 实时库存扣流水（近似）推导并补写
|
||||
if (openingDate && !openingMap.size) {
|
||||
await deriveAndStoreOpeningSnapshot({
|
||||
cloudDb,
|
||||
snapshotDb,
|
||||
baseline: DAILY_INVENTORY_BASELINE,
|
||||
openingDate,
|
||||
latestBizDate,
|
||||
takenAt,
|
||||
}).catch((e) => {
|
||||
console.error('[daily-inventory] 期初快照推导失败:', e.message);
|
||||
});
|
||||
openingMap = await snapshotDb.fetchSnapshot(openingDate).catch(() => new Map());
|
||||
}
|
||||
|
||||
// 流水列：自期初时刻（最新业务日 01:00）以来的单据合计（带符号，流出为负）
|
||||
let flowMap = new Map();
|
||||
if (openingDate) {
|
||||
flowMap = await fetchFlows(cloudDb, wmsCoIds, `${latestBizDate} 01:00:00`).catch((e) => {
|
||||
console.error('[daily-inventory] 流水取数失败:', e.message);
|
||||
return new Map();
|
||||
});
|
||||
}
|
||||
|
||||
const items = DAILY_INVENTORY_BASELINE.map((base) => {
|
||||
const official = officialMap.get(base.warehouse) || null;
|
||||
const grade = base.wmsCoId != null ? gradeMap.get(String(base.wmsCoId)) : null;
|
||||
const opening = base.wmsCoId != null ? openingMap.get(String(base.wmsCoId)) : null;
|
||||
const itemFlows = base.wmsCoId != null ? flowMap.get(String(base.wmsCoId)) : null;
|
||||
|
||||
// 12 个流水列：聚水潭官方导出优先，缺失时回退业务库推算（历史业务日不做回退）
|
||||
const items = [];
|
||||
for (const base of DAILY_INVENTORY_BASELINE) {
|
||||
const flows = {};
|
||||
const flowSources = {};
|
||||
for (const col of FLOW_COLUMNS) {
|
||||
const fromOfficial = official?.flows?.[col.field];
|
||||
if (fromOfficial != null) {
|
||||
flows[col.field] = Number(fromOfficial);
|
||||
flowSources[col.field] = 'official';
|
||||
continue;
|
||||
}
|
||||
const derived = itemFlows ? itemFlows[col.field] : null;
|
||||
if (derived != null && !staleMetrics) {
|
||||
flows[col.field] = Number(derived.toFixed(2));
|
||||
flowSources[col.field] = 'derived';
|
||||
continue;
|
||||
}
|
||||
flows[col.field] = null;
|
||||
flowSources[col.field] = 'none';
|
||||
}
|
||||
for (const col of FLOW_COLUMNS) flows[col.field] = base[col.field] ?? 0;
|
||||
|
||||
// 期末：官方期末优先；无官方时，历史业务日不给实时库存（口径不对）
|
||||
const gradeStock = grade?.gradeStock ?? null;
|
||||
let closingQty = gradeStock;
|
||||
let closingSource = 'derived';
|
||||
if (official?.closingQty != null) {
|
||||
closingQty = Number(official.closingQty);
|
||||
closingSource = 'official';
|
||||
} else if (staleMetrics) {
|
||||
closingQty = null;
|
||||
closingSource = 'none';
|
||||
}
|
||||
const closing = await fetchClosingQty(base.wmsCoId).catch(() => null);
|
||||
const grade = base.dbWarehouse && latestBizDate
|
||||
? await fetchGradeMetrics(base.dbWarehouse, latestBizDate, asOf).catch(() => null)
|
||||
: null;
|
||||
|
||||
// 期初：官方期初优先，其次本地快照
|
||||
let openingQty = opening ? opening.closingQty : null;
|
||||
let openingSource = opening ? 'snapshot' : 'none';
|
||||
if (official?.openingQty != null) {
|
||||
openingQty = Number(official.openingQty);
|
||||
openingSource = 'official';
|
||||
} else if (staleMetrics) {
|
||||
openingQty = null;
|
||||
openingSource = 'none';
|
||||
}
|
||||
|
||||
return {
|
||||
items.push({
|
||||
warehouse: base.warehouse,
|
||||
dbWarehouse: base.dbWarehouse,
|
||||
openingQty,
|
||||
openingQtyExtra: null,
|
||||
openingQty: base.openingQty,
|
||||
openingQtyExtra: base.openingQtyExtra,
|
||||
...flows,
|
||||
closingQty,
|
||||
closingSkuCount: grade?.skuCount ?? null,
|
||||
closingTakenAt: takenAt,
|
||||
shipQty30d: grade?.shipQty ?? null,
|
||||
closingQty: closing?.closingQty ?? null,
|
||||
closingSkuCount: closing?.closingSkuCount ?? null,
|
||||
closingTakenAt: closing?.closingTakenAt ?? null,
|
||||
turnoverDays: grade?.turnoverDays ?? null,
|
||||
gradeStock,
|
||||
gradeStock: grade?.gradeStock ?? null,
|
||||
warnLevel: grade?.warnLevel ?? null,
|
||||
slowLevel: grade?.slowLevel ?? null,
|
||||
staleLevel: grade?.staleLevel ?? null,
|
||||
zombieLevel: grade?.zombieLevel ?? null,
|
||||
ungradedSku: grade?.ungradedSku ?? null,
|
||||
hasGrade: Boolean(grade),
|
||||
source: {
|
||||
opening: openingSource,
|
||||
closing: closingSource,
|
||||
flows: flowSources,
|
||||
hasOfficial: Boolean(official),
|
||||
},
|
||||
};
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
// 合计行：便于与表格总额核对
|
||||
const sum = (k) => items.reduce((acc, it) => acc + (Number(it[k]) || 0), 0);
|
||||
const totals = { warehouse: '合计', dbWarehouse: '', isTotal: true };
|
||||
for (const k of ['openingQty', 'openingQtyExtra', ...FLOW_COLUMNS.map((c) => c.field), 'closingQty', 'warnLevel', 'slowLevel', 'staleLevel', 'zombieLevel']) {
|
||||
// 若所有仓库该列均无数据（null），合计同样置空，避免误读为 0
|
||||
totals[k] = items.every((it) => it[k] == null) ? null : Number(sum(k).toFixed(2));
|
||||
}
|
||||
// 合计行周转率按「总发货 / 总库存」重算，避免简单累加失真
|
||||
totals.shipQty30d = Number(sum('shipQty30d').toFixed(2));
|
||||
const totalStock = sum('closingQty');
|
||||
totals.turnoverDays = totalStock > 0
|
||||
? Number((sum('shipQty30d') * 100 / totalStock).toFixed(2))
|
||||
: null;
|
||||
|
||||
const noOpeningCount = items.filter((it) => it.openingQty == null).length;
|
||||
const balanceMismatch = checkBalance([...officialMap.values()]);
|
||||
const officialFlowFields = FLOW_COLUMNS
|
||||
.filter((c) => items.some((it) => it.source.flows[c.field] === 'official'))
|
||||
.map((c) => c.field);
|
||||
const derivedFlowFields = FLOW_COLUMNS
|
||||
.filter((c) => items.some((it) => it.source.flows[c.field] === 'derived'))
|
||||
.map((c) => c.field);
|
||||
|
||||
const payload = {
|
||||
openingDate,
|
||||
latestBizDate,
|
||||
systemBizDate,
|
||||
staleMetrics,
|
||||
asOf,
|
||||
shipWindow: asOf ? { ...shipWindow(asOf), days: SHIP_WINDOW_DAYS } : null,
|
||||
flowColumns: FLOW_COLUMNS,
|
||||
flowColumnsAvailable: AVAILABLE_FLOW_FIELDS,
|
||||
flowColumnsOfficial: officialFlowFields,
|
||||
flowColumnsDerived: derivedFlowFields,
|
||||
noOpeningCount,
|
||||
official: {
|
||||
hasData: officialMap.size > 0,
|
||||
warehouseCount: officialMap.size,
|
||||
availableDates: officialDates,
|
||||
balanceMismatch,
|
||||
},
|
||||
items,
|
||||
totals,
|
||||
};
|
||||
cachedResult = payload;
|
||||
cachedResultAt = Date.now();
|
||||
return res.json({ success: true, data: payload });
|
||||
} catch (error) {
|
||||
console.error('[daily-inventory] 查询失败:', error.message);
|
||||
return res.status(500).json({ success: false, error: '每日进销存数据查询失败', detail: error.message });
|
||||
}
|
||||
});
|
||||
|
||||
/**
|
||||
* 官方期初 = 上一业务日期末、官方期末 = 当日期末。
|
||||
* 导入后回写本地快照，让「今日期初 = 昨日结存」的自动推算也对齐聚水潭口径。
|
||||
*/
|
||||
async function syncSnapshotFromOfficial(bizDate, rows) {
|
||||
const byId = new Map(DAILY_INVENTORY_BASELINE.map((b) => [String(b.wmsCoId), b]));
|
||||
const known = rows.filter((r) => r.wmsCoId != null);
|
||||
if (!known.length) return { prev: 0, current: 0 };
|
||||
const prevDate = prevDay(bizDate);
|
||||
|
||||
let prevCount = 0;
|
||||
if (prevDate) {
|
||||
const prev = await snapshotDb.fetchSnapshot(prevDate).catch(() => new Map());
|
||||
prevCount = await snapshotDb.upsertSnapshot(prevDate, known
|
||||
.filter((r) => r.openingQty != null)
|
||||
.map((r) => ({
|
||||
wmsCoId: r.wmsCoId,
|
||||
warehouse: r.warehouse,
|
||||
dbWarehouse: byId.get(String(r.wmsCoId))?.dbWarehouse || null,
|
||||
closingQty: Number(r.openingQty),
|
||||
skuCount: Number(prev.get(String(r.wmsCoId))?.skuCount || 0),
|
||||
takenAt: null,
|
||||
}))).catch((e) => {
|
||||
console.error('[daily-inventory] 期初快照回写失败:', e.message);
|
||||
return 0;
|
||||
});
|
||||
}
|
||||
|
||||
const current = await snapshotDb.fetchSnapshot(bizDate).catch(() => new Map());
|
||||
const currentCount = await snapshotDb.upsertSnapshot(bizDate, known
|
||||
.filter((r) => r.closingQty != null)
|
||||
.map((r) => ({
|
||||
wmsCoId: r.wmsCoId,
|
||||
warehouse: r.warehouse,
|
||||
dbWarehouse: byId.get(String(r.wmsCoId))?.dbWarehouse || null,
|
||||
closingQty: Number(r.closingQty),
|
||||
skuCount: Number(current.get(String(r.wmsCoId))?.skuCount || 0),
|
||||
takenAt: null,
|
||||
}))).catch((e) => {
|
||||
console.error('[daily-inventory] 期末快照回写失败:', e.message);
|
||||
return 0;
|
||||
});
|
||||
|
||||
return { prev: prevCount, current: currentCount };
|
||||
}
|
||||
|
||||
/**
|
||||
* GET /api/daily-inventory/official
|
||||
* 查询某业务日已导入的聚水潭官方进销存数据
|
||||
*/
|
||||
router.get('/official', async (req, res) => {
|
||||
try {
|
||||
const date = String(req.query?.date || '').trim();
|
||||
if (!/^\d{4}-\d{2}-\d{2}$/.test(date)) {
|
||||
return res.status(400).json({ success: false, error: '请提供业务日期 date=YYYY-MM-DD' });
|
||||
}
|
||||
const map = await officialDb.fetchOfficial(date);
|
||||
const dates = await officialDb.listOfficialDates(30);
|
||||
return res.json({
|
||||
success: true,
|
||||
data: { date, rows: [...map.values()], availableDates: dates },
|
||||
});
|
||||
} catch (error) {
|
||||
console.error('[daily-inventory] 官方数据查询失败:', error.message);
|
||||
return res.status(500).json({ success: false, error: '官方数据查询失败', detail: error.message });
|
||||
}
|
||||
});
|
||||
|
||||
/**
|
||||
* POST /api/daily-inventory/official-import
|
||||
* 导入聚水潭进销存按仓导出（multipart: file=xlsx, date；或 JSON: {date, rows}）
|
||||
*/
|
||||
router.post('/official-import', upload.single('file'), async (req, res) => {
|
||||
try {
|
||||
const date = String((req.body && req.body.date) || req.query?.date || '').trim();
|
||||
if (!/^\d{4}-\d{2}-\d{2}$/.test(date)) {
|
||||
return res.status(400).json({ success: false, error: '请提供业务日期 date（YYYY-MM-DD）' });
|
||||
totals[k] = Number(sum(k).toFixed(2));
|
||||
}
|
||||
|
||||
let rows = [];
|
||||
let warnings = [];
|
||||
let sheetName = null;
|
||||
if (req.file && req.file.buffer) {
|
||||
const parsed = parseWorkbook(req.file.buffer);
|
||||
rows = parsed.rows;
|
||||
warnings = parsed.warnings;
|
||||
sheetName = parsed.sheetName;
|
||||
if (!rows.length) {
|
||||
return res.status(400).json({
|
||||
success: false,
|
||||
error: '未能从文件解析出仓库行',
|
||||
detail: warnings.join('；') || '未找到含「仓库」列的工作表',
|
||||
});
|
||||
}
|
||||
} else if (req.body && Array.isArray(req.body.rows)) {
|
||||
const parsed = normalizeRecords(req.body.rows);
|
||||
rows = parsed.rows;
|
||||
warnings = parsed.warnings;
|
||||
if (!rows.length) {
|
||||
return res.status(400).json({ success: false, error: 'rows 中未解析到仓库行', detail: warnings.join('；') });
|
||||
}
|
||||
} else {
|
||||
return res.status(400).json({ success: false, error: '请上传 xlsx 文件（字段名 file）或提供 rows 数组' });
|
||||
}
|
||||
|
||||
const result = await importOfficial(date, rows, {
|
||||
source: String((req.body && req.body.source) || 'jst-export'),
|
||||
});
|
||||
const synced = await syncSnapshotFromOfficial(date, rows);
|
||||
cachedResult = null; // 导入后立即使查询缓存失效
|
||||
|
||||
return res.json({
|
||||
res.json({
|
||||
success: true,
|
||||
data: {
|
||||
...result,
|
||||
sheetName,
|
||||
warnings,
|
||||
snapshotSynced: synced,
|
||||
baselineDate: BASELINE_DATE,
|
||||
latestBizDate,
|
||||
asOf,
|
||||
flowColumns: FLOW_COLUMNS,
|
||||
items,
|
||||
totals,
|
||||
},
|
||||
});
|
||||
} catch (error) {
|
||||
console.error('[daily-inventory] 官方数据导入失败:', error.message);
|
||||
return res.status(500).json({ success: false, error: '官方数据导入失败', detail: error.message });
|
||||
console.error('[daily-inventory] 查询失败:', error.message);
|
||||
res.status(500).json({ success: false, error: '每日进销存数据查询失败', detail: error.message });
|
||||
}
|
||||
});
|
||||
|
||||
|
||||
@ -1,81 +0,0 @@
|
||||
'use strict';
|
||||
|
||||
// 每日进销存 · 定时截图通知（管理员专用）
|
||||
//
|
||||
// 安全约定：
|
||||
// · 全部接口要求登录且 role === 'admin'
|
||||
// · 响应里只有「是否已配置」与脱敏预览，绝不返回通知中心密钥 / 对象存储密钥
|
||||
// · 收件人名单由后端校验与规范化，前端只能提交姓名文本
|
||||
|
||||
const express = require('express');
|
||||
const {
|
||||
getDailyInventoryNotificationAdminConfig,
|
||||
listRunRecords,
|
||||
saveDailyInventoryNotificationConfig,
|
||||
} = require('../services/dailyInventoryNotificationSettings');
|
||||
const {
|
||||
runDailyInventoryNotificationJob,
|
||||
} = require('../jobs/dailyInventoryNotificationJob');
|
||||
|
||||
const router = express.Router();
|
||||
|
||||
function sendError(res, error, fallback) {
|
||||
const status = Number(error?.statusCode) || 500;
|
||||
console.error('[DailyInventoryNotification]', {
|
||||
message: error?.message || fallback,
|
||||
code: error?.code || null,
|
||||
status,
|
||||
});
|
||||
res.status(status).json({ success: false, error: error.message || fallback });
|
||||
}
|
||||
|
||||
/** 仅管理员可查看与修改通知设置、执行立即测试 */
|
||||
function requireAdmin(req, res, next) {
|
||||
if (req?.user?.role !== 'admin') {
|
||||
return res.status(403).json({ success: false, error: '仅管理员可操作通知设置' });
|
||||
}
|
||||
return next();
|
||||
}
|
||||
|
||||
router.use(requireAdmin);
|
||||
|
||||
// 读取通知设置（含通知中心 / 对象存储的配置状态与最近执行记录）
|
||||
router.get('/config', async (_req, res) => {
|
||||
try {
|
||||
res.json({ success: true, data: await getDailyInventoryNotificationAdminConfig() });
|
||||
} catch (error) {
|
||||
sendError(res, error, '加载每日进销存通知设置失败');
|
||||
}
|
||||
});
|
||||
|
||||
// 保存通知设置
|
||||
router.put('/config', async (req, res) => {
|
||||
try {
|
||||
const saved = await saveDailyInventoryNotificationConfig(req.body || {});
|
||||
res.json({ success: true, data: { ...saved, admin: await getDailyInventoryNotificationAdminConfig() } });
|
||||
} catch (error) {
|
||||
sendError(res, error, '保存每日进销存通知设置失败');
|
||||
}
|
||||
});
|
||||
|
||||
// 立即测试：真实走一次截图 + 上传 + 通知，但不写入正式幂等记录
|
||||
router.post('/test', async (_req, res) => {
|
||||
try {
|
||||
const result = await runDailyInventoryNotificationJob({ mode: 'test' });
|
||||
res.json({ success: result?.success === true, data: result });
|
||||
} catch (error) {
|
||||
sendError(res, error, '执行每日进销存通知测试失败');
|
||||
}
|
||||
});
|
||||
|
||||
// 最近执行记录（管理员排障用）
|
||||
router.get('/runs', async (req, res) => {
|
||||
try {
|
||||
const limit = Math.min(Math.max(Number(req.query?.limit) || 10, 1), 50);
|
||||
res.json({ success: true, data: await listRunRecords(limit) });
|
||||
} catch (error) {
|
||||
sendError(res, error, '加载每日进销存通知执行记录失败');
|
||||
}
|
||||
});
|
||||
|
||||
module.exports = router;
|
||||
@ -1,282 +0,0 @@
|
||||
const express = require('express');
|
||||
const cloudDb = require('../config/cloudDatabase');
|
||||
const { DAILY_INVENTORY_BASELINE } = require('../config/dailyInventoryBaseline');
|
||||
const {
|
||||
PICKING_BIN_GRADE_RULES,
|
||||
PICKING_BIN_WINDOW_OPTIONS,
|
||||
PICKING_BIN_DEFAULT_DAYS,
|
||||
PICKING_BIN_TOTAL_LABEL,
|
||||
PICKING_BIN_BIN_TYPES,
|
||||
} = require('../config/pickingBinSalesAnalysis');
|
||||
const { fetchPickingBinSkuRows } = require('../services/pickingBinSalesAnalysis');
|
||||
const { sendWorkbookDownload } = require('../services/exportWorkbook');
|
||||
|
||||
const router = express.Router();
|
||||
|
||||
/** 库存衡量基准时刻：快照日次日 01:00（报表库每日凌晨跑批，标注 T-1） */
|
||||
const AS_OF_TIME = '01:00';
|
||||
|
||||
/** 结果缓存：一次要扫订单明细 + 仓位明细两张大表，避免连续刷新重复打库 */
|
||||
const RESULT_CACHE_TTL_MS = 5 * 60 * 1000;
|
||||
const cacheByKey = new Map();
|
||||
|
||||
const round2 = (v) => Math.round((Number(v) || 0) * 100) / 100;
|
||||
const round4 = (v) => Math.round((Number(v) || 0) * 10000) / 10000;
|
||||
|
||||
/** 快照日 + 次日 01:00 作为统一的统计基准时刻 */
|
||||
function nextDayAsOf(bizDate) {
|
||||
if (!bizDate || !/^\d{4}-\d{2}-\d{2}$/.test(bizDate)) return null;
|
||||
const d = new Date(`${bizDate}T00:00:00Z`);
|
||||
d.setUTCDate(d.getUTCDate() + 1);
|
||||
return `${d.toISOString().slice(0, 10)} ${AS_OF_TIME}`;
|
||||
}
|
||||
|
||||
/** 发货窗口：[asOf - N 天, asOf) */
|
||||
function buildShipWindow(asOf, days) {
|
||||
const to = new Date(`${asOf.slice(0, 10)}T${AS_OF_TIME}:00Z`);
|
||||
const from = new Date(to.getTime() - days * 86400000);
|
||||
const fmt = (dt) => dt.toISOString().slice(0, 19).replace('T', ' ');
|
||||
return { shipFrom: fmt(from), shipTo: fmt(to) };
|
||||
}
|
||||
|
||||
async function fetchLatestBizDate() {
|
||||
const rows = await cloudDb.query(
|
||||
`SELECT MAX(CONVERT(VARCHAR(10), date, 23)) AS d FROM rpt.pm_stockMonitor`
|
||||
);
|
||||
return rows[0]?.d || null;
|
||||
}
|
||||
|
||||
async function fetchBinTakenAt() {
|
||||
const rows = await cloudDb.query(
|
||||
`SELECT MAX(updateTime) AS takenAt FROM rpt.jst_packInventoryInfo`
|
||||
);
|
||||
return rows[0]?.takenAt || null;
|
||||
}
|
||||
|
||||
/** 解析并收敛统计窗口天数，只允许白名单内的取值 */
|
||||
function resolveDays(raw) {
|
||||
const n = Number.parseInt(String(raw ?? ''), 10);
|
||||
return PICKING_BIN_WINDOW_OPTIONS.includes(n) ? n : PICKING_BIN_DEFAULT_DAYS;
|
||||
}
|
||||
|
||||
/** 解析仓库过滤，只允许出现在仓库清单里的 wmsCoId，防止任意拼参 */
|
||||
function resolveWarehouses(raw) {
|
||||
const known = DAILY_INVENTORY_BASELINE.filter((b) => b.wmsCoId != null);
|
||||
const requested = String(raw || '')
|
||||
.split(',')
|
||||
.map((v) => v.trim())
|
||||
.filter(Boolean);
|
||||
const picked = requested.length > 0
|
||||
? known.filter((b) => requested.includes(String(b.wmsCoId)))
|
||||
: known;
|
||||
return picked;
|
||||
}
|
||||
|
||||
const GRADE_MAP = new Map(PICKING_BIN_GRADE_RULES.map((g) => [g.key, g]));
|
||||
|
||||
/** 明细行按「仓库 × 商品编码」去重后的商品个数 */
|
||||
function dedupeCount(list) {
|
||||
return new Set(list.map((it) => `${it.wmsCoId}::${it.skuId}`)).size;
|
||||
}
|
||||
|
||||
/**
|
||||
* GET /api/picking-bin-sales-analysis
|
||||
* 拣选库位动销分析：仓库 × 仓位 × 商品编码 → 库存数量 / 商品销量 / 商品日销 / 动销等级
|
||||
* 动销等级按「商品日销」判定（商品整档销量 ÷ 天数），不做仓位分摊。
|
||||
*/
|
||||
router.get('/', async (req, res) => {
|
||||
try {
|
||||
const force = String(req.query?.refresh || '') === '1';
|
||||
const days = resolveDays(req.query?.days);
|
||||
const warehouses = resolveWarehouses(req.query?.wmsCoId);
|
||||
const wmsCoIds = warehouses.map((b) => String(b.wmsCoId));
|
||||
|
||||
const cacheKey = `${days}::${wmsCoIds.join('|')}`;
|
||||
const latestBizDate = await fetchLatestBizDate().catch(() => null);
|
||||
const cached = cacheByKey.get(cacheKey);
|
||||
if (!force && cached && cached.latestBizDate === latestBizDate
|
||||
&& Date.now() - cached.at < RESULT_CACHE_TTL_MS) {
|
||||
return res.json({ success: true, data: cached.payload, cached: true });
|
||||
}
|
||||
|
||||
const asOf = nextDayAsOf(latestBizDate);
|
||||
if (!asOf) {
|
||||
return res.status(503).json({
|
||||
success: false,
|
||||
error: '业务库暂无库存监控数据，无法定位统计基准日',
|
||||
});
|
||||
}
|
||||
|
||||
const { shipFrom, shipTo } = buildShipWindow(asOf, days);
|
||||
const [rows, takenAt] = await Promise.all([
|
||||
fetchPickingBinSkuRows(cloudDb, wmsCoIds, { shipFrom, shipTo, days }),
|
||||
fetchBinTakenAt().catch(() => null),
|
||||
]);
|
||||
|
||||
const whMap = new Map(warehouses.map((b) => [String(b.wmsCoId), b.warehouse]));
|
||||
const items = rows.map((r) => ({
|
||||
wmsCoId: r.wmsCoId,
|
||||
binName: r.binName,
|
||||
binType: r.binType,
|
||||
skuId: r.skuId,
|
||||
warehouse: whMap.get(r.wmsCoId) || r.wmsCoId,
|
||||
stockQty: r.stockQty,
|
||||
skuCount: r.skuCount,
|
||||
salesQty: round2(r.salesQty),
|
||||
dailySales: round4(r.dailySales),
|
||||
gradeKey: r.gradeKey,
|
||||
gradeLabel: GRADE_MAP.get(r.gradeKey)?.label || '',
|
||||
}));
|
||||
|
||||
// 每个「仓库 × 商品」只计一次销量，避免同一商品跨多个仓位被重复累加
|
||||
const skuSalesMap = new Map();
|
||||
rows.forEach((r) => {
|
||||
const key = `${r.wmsCoId}::${r.skuId}`;
|
||||
if (!skuSalesMap.has(key)) skuSalesMap.set(key, r.salesQty);
|
||||
});
|
||||
const dedupeSales = (list) => {
|
||||
const seen = new Set();
|
||||
return list.reduce((acc, it) => {
|
||||
const key = `${it.wmsCoId}::${it.skuId}`;
|
||||
if (seen.has(key)) return acc;
|
||||
seen.add(key);
|
||||
return acc + (skuSalesMap.get(key) || 0);
|
||||
}, 0);
|
||||
};
|
||||
|
||||
// 各动销等级汇总：商品数按「仓库 × 商品」去重，库存按明细行求和（无重复）
|
||||
const summary = PICKING_BIN_GRADE_RULES.map((grade) => {
|
||||
const hit = items.filter((it) => it.gradeKey === grade.key);
|
||||
const salesQty = round2(dedupeSales(hit));
|
||||
return {
|
||||
key: grade.key,
|
||||
label: grade.label,
|
||||
tip: grade.tip,
|
||||
rowCount: hit.length,
|
||||
skuCount: dedupeCount(hit),
|
||||
stockQty: round2(hit.reduce((acc, it) => acc + it.stockQty, 0)),
|
||||
salesQty,
|
||||
dailySales: round4(salesQty / days),
|
||||
};
|
||||
});
|
||||
|
||||
const dedupeAll = new Set(items.map((it) => `${it.wmsCoId}::${it.skuId}`));
|
||||
const totalSales = round2(dedupeSales(items));
|
||||
const total = {
|
||||
key: '__total__',
|
||||
label: PICKING_BIN_TOTAL_LABEL,
|
||||
rowCount: items.length,
|
||||
skuCount: dedupeAll.size,
|
||||
stockQty: round2(summary.reduce((acc, s) => acc + s.stockQty, 0)),
|
||||
salesQty: totalSales,
|
||||
dailySales: round4(totalSales / days),
|
||||
};
|
||||
|
||||
const payload = {
|
||||
days,
|
||||
windowOptions: PICKING_BIN_WINDOW_OPTIONS,
|
||||
binTypes: [...PICKING_BIN_BIN_TYPES],
|
||||
binTypeOptions: [...PICKING_BIN_BIN_TYPES],
|
||||
latestBizDate,
|
||||
asOf,
|
||||
shipWindow: { shipFrom, shipTo, days },
|
||||
takenAt,
|
||||
grades: PICKING_BIN_GRADE_RULES.map((g) => ({ key: g.key, label: g.label, tip: g.tip })),
|
||||
totalLabel: PICKING_BIN_TOTAL_LABEL,
|
||||
warehouses: warehouses.map((b) => ({ wmsCoId: String(b.wmsCoId), warehouse: b.warehouse })),
|
||||
items,
|
||||
summary,
|
||||
total,
|
||||
};
|
||||
|
||||
cacheByKey.set(cacheKey, { latestBizDate, at: Date.now(), payload });
|
||||
return res.json({ success: true, data: payload });
|
||||
} catch (error) {
|
||||
console.error('[picking-bin-sales-analysis] 查询失败:', error.message);
|
||||
return res.status(500).json({
|
||||
success: false,
|
||||
error: '拣选库位动销分析数据查询失败',
|
||||
detail: error.message,
|
||||
});
|
||||
}
|
||||
});
|
||||
|
||||
/**
|
||||
* GET /api/picking-bin-sales-analysis/export
|
||||
* 导出库位明细（只含拣选位）。query: days、wmsCoId（逗号分隔）、grade（逗号分隔）、format（xlsx|csv）
|
||||
*/
|
||||
router.get('/export', async (req, res) => {
|
||||
try {
|
||||
const days = resolveDays(req.query?.days);
|
||||
const warehouses = resolveWarehouses(req.query?.wmsCoId);
|
||||
const wmsCoIds = warehouses.map((b) => String(b.wmsCoId));
|
||||
const format = String(req.query?.format || 'xlsx').toLowerCase() === 'csv' ? 'csv' : 'xlsx';
|
||||
|
||||
const grades = String(req.query?.grade || '')
|
||||
.split(',')
|
||||
.map((v) => v.trim())
|
||||
.filter((v) => GRADE_MAP.has(v));
|
||||
|
||||
const latestBizDate = await fetchLatestBizDate().catch(() => null);
|
||||
const asOf = nextDayAsOf(latestBizDate);
|
||||
if (!asOf) {
|
||||
return res.status(503).json({
|
||||
success: false,
|
||||
error: '业务库暂无库存监控数据，无法定位统计基准日',
|
||||
});
|
||||
}
|
||||
|
||||
const { shipFrom, shipTo } = buildShipWindow(asOf, days);
|
||||
// 导出按「仓位 × 商品编码」拆行：一个仓位有 N 个商品就输出 N 行
|
||||
const rows = await fetchPickingBinSkuRows(cloudDb, wmsCoIds, { shipFrom, shipTo, days });
|
||||
|
||||
const whMap = new Map(warehouses.map((b) => [String(b.wmsCoId), b.warehouse]));
|
||||
const filtered = grades.length > 0
|
||||
? rows.filter((r) => grades.includes(r.gradeKey))
|
||||
: rows;
|
||||
|
||||
const sheetRows = filtered.map((r) => [
|
||||
whMap.get(r.wmsCoId) || r.wmsCoId,
|
||||
r.binName,
|
||||
r.binType,
|
||||
r.skuId,
|
||||
r.stockQty,
|
||||
r.skuCount,
|
||||
round2(r.salesQty),
|
||||
round4(r.allocatedSalesQty),
|
||||
round4(r.dailySales),
|
||||
GRADE_MAP.get(r.gradeKey)?.label || r.gradeKey,
|
||||
days,
|
||||
latestBizDate || '',
|
||||
]);
|
||||
|
||||
const fileName = `拣选库位动销分析-${(latestBizDate || '').replace(/-/g, '') || '未知日期'}`;
|
||||
const { totalRows } = sendWorkbookDownload(res, {
|
||||
fileName,
|
||||
format,
|
||||
sheets: [{
|
||||
name: '库位动销明细',
|
||||
header: [
|
||||
'仓库', '仓位', '类型', '商品编码', '库存数量', '仓位SKU数',
|
||||
`商品销量(近${days}天)`, `分摊销量(近${days}天)`, '商品日销',
|
||||
'动销等级', '统计天数', '统计基准日',
|
||||
],
|
||||
rows: sheetRows,
|
||||
}],
|
||||
});
|
||||
console.log(`[picking-bin-sales-analysis] 导出: ${totalRows} 行, 仓库 ${wmsCoIds.length} 个, 仅拣选位, 窗口 ${days} 天`);
|
||||
return null;
|
||||
} catch (error) {
|
||||
console.error('[picking-bin-sales-analysis] 导出失败:', error.message);
|
||||
if (!res.headersSent) {
|
||||
return res.status(500).json({
|
||||
success: false,
|
||||
error: '拣选库位动销分析导出失败',
|
||||
detail: error.message,
|
||||
});
|
||||
}
|
||||
return null;
|
||||
}
|
||||
});
|
||||
|
||||
module.exports = router;
|
||||
@ -1,281 +0,0 @@
|
||||
const express = require('express');
|
||||
const cloudDb = require('../config/cloudDatabase');
|
||||
const { DAILY_INVENTORY_BASELINE } = require('../config/dailyInventoryBaseline');
|
||||
const {
|
||||
SALES_GRADE_RULES,
|
||||
SALES_TOTAL_LABEL,
|
||||
STOCK_SALES_WINDOW_OPTIONS,
|
||||
STOCK_SALES_DEFAULT_DAYS,
|
||||
} = require('../config/stockSalesAnalysis');
|
||||
const { fetchGradeRows, fetchZeroSaleSkuRows } = require('../services/stockSalesAnalysis');
|
||||
const { sendWorkbookDownload } = require('../services/exportWorkbook');
|
||||
|
||||
const router = express.Router();
|
||||
|
||||
/** 库存衡量基准时刻：快照日次日 01:00（报表库每日凌晨跑批，标注 T-1） */
|
||||
const AS_OF_TIME = '01:00';
|
||||
|
||||
/** 结果缓存：一次要扫订单明细 + 库存明细两张大表，避免连续刷新重复打库 */
|
||||
const RESULT_CACHE_TTL_MS = 5 * 60 * 1000;
|
||||
const cacheByDays = new Map();
|
||||
|
||||
const round2 = (v) => Math.round((Number(v) || 0) * 100) / 100;
|
||||
|
||||
/** 快照日 + 次日 01:00 作为统一的统计基准时刻 */
|
||||
function nextDayAsOf(bizDate) {
|
||||
if (!bizDate || !/^\d{4}-\d{2}-\d{2}$/.test(bizDate)) return null;
|
||||
const d = new Date(`${bizDate}T00:00:00Z`);
|
||||
d.setUTCDate(d.getUTCDate() + 1);
|
||||
return `${d.toISOString().slice(0, 10)} ${AS_OF_TIME}`;
|
||||
}
|
||||
|
||||
/** 发货窗口：[asOf - N 天, asOf) */
|
||||
function buildShipWindow(asOf, days) {
|
||||
const to = new Date(`${asOf.slice(0, 10)}T${AS_OF_TIME}:00Z`);
|
||||
const from = new Date(to.getTime() - days * 86400000);
|
||||
const fmt = (dt) => dt.toISOString().slice(0, 19).replace('T', ' ');
|
||||
return { shipFrom: fmt(from), shipTo: fmt(to) };
|
||||
}
|
||||
|
||||
async function fetchLatestBizDate() {
|
||||
const rows = await cloudDb.query(
|
||||
`SELECT MAX(CONVERT(VARCHAR(10), date, 23)) AS d FROM rpt.pm_stockMonitor`
|
||||
);
|
||||
return rows[0]?.d || null;
|
||||
}
|
||||
|
||||
async function fetchInventoryTakenAt() {
|
||||
const rows = await cloudDb.query(
|
||||
`SELECT MAX(modified) AS takenAt FROM rpt.jst_inventoryInfo`
|
||||
);
|
||||
return rows[0]?.takenAt || null;
|
||||
}
|
||||
|
||||
/** 解析并收敛统计窗口天数，只允许白名单内的取值 */
|
||||
function resolveDays(raw) {
|
||||
const n = Number.parseInt(String(raw ?? ''), 10);
|
||||
return STOCK_SALES_WINDOW_OPTIONS.includes(n) ? n : STOCK_SALES_DEFAULT_DAYS;
|
||||
}
|
||||
|
||||
/**
|
||||
* GET /api/stock-sales-analysis
|
||||
* 仓库库存动销分析：仓库 × 动销等级 → SKU数量 / SKU占比 / 库存数量 / 库存占比 / 销量
|
||||
*/
|
||||
router.get('/', async (req, res) => {
|
||||
try {
|
||||
const force = String(req.query?.refresh || '') === '1';
|
||||
const days = resolveDays(req.query?.days);
|
||||
const latestBizDate = await fetchLatestBizDate().catch(() => null);
|
||||
|
||||
const cached = cacheByDays.get(days);
|
||||
if (!force && cached && cached.latestBizDate === latestBizDate
|
||||
&& Date.now() - cached.at < RESULT_CACHE_TTL_MS) {
|
||||
return res.json({ success: true, data: cached.payload, cached: true });
|
||||
}
|
||||
|
||||
const asOf = nextDayAsOf(latestBizDate);
|
||||
if (!asOf) {
|
||||
return res.status(503).json({
|
||||
success: false,
|
||||
error: '业务库暂无库存监控数据，无法定位统计基准日',
|
||||
});
|
||||
}
|
||||
|
||||
const { shipFrom, shipTo } = buildShipWindow(asOf, days);
|
||||
const warehouses = DAILY_INVENTORY_BASELINE.filter((b) => b.wmsCoId != null);
|
||||
const wmsCoIds = warehouses.map((b) => b.wmsCoId);
|
||||
|
||||
const [rows, takenAt] = await Promise.all([
|
||||
fetchGradeRows(cloudDb, wmsCoIds, { shipFrom, shipTo, days }),
|
||||
fetchInventoryTakenAt().catch(() => null),
|
||||
]);
|
||||
|
||||
// (仓库, 等级) → 指标
|
||||
const matrix = new Map();
|
||||
rows.forEach((r) => {
|
||||
matrix.set(`${r.wmsCoId}::${r.gradeKey}`, r);
|
||||
});
|
||||
|
||||
const buildBucket = (grade, cell) => ({
|
||||
key: grade.key,
|
||||
label: grade.label,
|
||||
tip: grade.tip,
|
||||
skuCount: cell?.skuCount ?? 0,
|
||||
stockQty: round2(cell?.stockQty ?? 0),
|
||||
salesQty: round2(cell?.salesQty ?? 0),
|
||||
dailySales: Number((cell?.dailySales ?? 0).toFixed(2)),
|
||||
});
|
||||
|
||||
const items = warehouses.map((base) => {
|
||||
const id = String(base.wmsCoId);
|
||||
const buckets = SALES_GRADE_RULES.map((grade) => (
|
||||
buildBucket(grade, matrix.get(`${id}::${grade.key}`))
|
||||
));
|
||||
|
||||
const totalSku = buckets.reduce((acc, b) => acc + b.skuCount, 0);
|
||||
const totalStock = buckets.reduce((acc, b) => acc + b.stockQty, 0);
|
||||
const totalSales = round2(buckets.reduce((acc, b) => acc + b.salesQty, 0));
|
||||
|
||||
return {
|
||||
warehouse: base.warehouse,
|
||||
dbWarehouse: base.dbWarehouse,
|
||||
wmsCoId: base.wmsCoId,
|
||||
hasData: totalSku > 0 || totalStock !== 0 || totalSales !== 0,
|
||||
buckets: buckets.map((b) => ({
|
||||
...b,
|
||||
skuRatio: totalSku > 0 ? b.skuCount / totalSku : null,
|
||||
stockRatio: totalStock !== 0 ? b.stockQty / totalStock : null,
|
||||
})),
|
||||
total: {
|
||||
key: '__total__',
|
||||
label: SALES_TOTAL_LABEL,
|
||||
skuCount: totalSku,
|
||||
skuRatio: totalSku > 0 ? 1 : null,
|
||||
stockQty: totalStock,
|
||||
stockRatio: totalStock !== 0 ? 1 : null,
|
||||
salesQty: totalSales,
|
||||
dailySales: Number((totalSales / days).toFixed(2)),
|
||||
},
|
||||
};
|
||||
});
|
||||
|
||||
// 全仓合计：各等级跨仓累加 + 汇总
|
||||
const grandBuckets = SALES_GRADE_RULES.map((grade) => {
|
||||
const skuCount = items.reduce((acc, it) => acc + (it.buckets.find((b) => b.key === grade.key)?.skuCount || 0), 0);
|
||||
const stockQty = round2(items.reduce((acc, it) => acc + (it.buckets.find((b) => b.key === grade.key)?.stockQty || 0), 0));
|
||||
const salesQty = round2(items.reduce((acc, it) => acc + (it.buckets.find((b) => b.key === grade.key)?.salesQty || 0), 0));
|
||||
return {
|
||||
key: grade.key,
|
||||
label: grade.label,
|
||||
tip: grade.tip,
|
||||
skuCount,
|
||||
stockQty,
|
||||
salesQty,
|
||||
dailySales: Number((salesQty / days).toFixed(2)),
|
||||
};
|
||||
});
|
||||
const grandSku = grandBuckets.reduce((acc, b) => acc + b.skuCount, 0);
|
||||
const grandStock = round2(grandBuckets.reduce((acc, b) => acc + b.stockQty, 0));
|
||||
const grandSales = round2(grandBuckets.reduce((acc, b) => acc + b.salesQty, 0));
|
||||
const grandTotal = {
|
||||
key: '__total__',
|
||||
label: SALES_TOTAL_LABEL,
|
||||
skuCount: grandSku,
|
||||
skuRatio: grandSku > 0 ? 1 : null,
|
||||
stockQty: grandStock,
|
||||
stockRatio: grandStock !== 0 ? 1 : null,
|
||||
salesQty: grandSales,
|
||||
dailySales: Number((grandSales / days).toFixed(2)),
|
||||
};
|
||||
|
||||
const payload = {
|
||||
days,
|
||||
windowOptions: STOCK_SALES_WINDOW_OPTIONS,
|
||||
latestBizDate,
|
||||
asOf,
|
||||
shipWindow: { shipFrom, shipTo, days },
|
||||
takenAt,
|
||||
grades: SALES_GRADE_RULES.map((g) => ({ key: g.key, label: g.label, tip: g.tip })),
|
||||
totalLabel: SALES_TOTAL_LABEL,
|
||||
items,
|
||||
grand: {
|
||||
warehouse: '全部仓库合计',
|
||||
hasData: grandSku > 0,
|
||||
buckets: grandBuckets.map((b) => ({
|
||||
...b,
|
||||
skuRatio: grandSku > 0 ? b.skuCount / grandSku : null,
|
||||
stockRatio: grandStock !== 0 ? b.stockQty / grandStock : null,
|
||||
})),
|
||||
total: grandTotal,
|
||||
},
|
||||
emptyWarehouseCount: items.filter((it) => !it.hasData).length,
|
||||
};
|
||||
|
||||
cacheByDays.set(days, { latestBizDate, at: Date.now(), payload });
|
||||
return res.json({ success: true, data: payload });
|
||||
} catch (error) {
|
||||
console.error('[stock-sales-analysis] 查询失败:', error.message);
|
||||
return res.status(500).json({
|
||||
success: false,
|
||||
error: '仓库库存动销分析数据查询失败',
|
||||
detail: error.message,
|
||||
});
|
||||
}
|
||||
});
|
||||
|
||||
/**
|
||||
* GET /api/stock-sales-analysis/zero-sales-export
|
||||
* 导出「销售=0」档的 SKU 级明细。
|
||||
* query: days（统计窗口）、wmsCoId（可选，逗号分隔，不传=全部仓库）、format（xlsx|csv，默认 xlsx）
|
||||
*/
|
||||
router.get('/zero-sales-export', async (req, res) => {
|
||||
try {
|
||||
const days = resolveDays(req.query?.days);
|
||||
const format = String(req.query?.format || 'xlsx').toLowerCase() === 'csv' ? 'csv' : 'xlsx';
|
||||
const latestBizDate = await fetchLatestBizDate().catch(() => null);
|
||||
|
||||
const asOf = nextDayAsOf(latestBizDate);
|
||||
if (!asOf) {
|
||||
return res.status(503).json({
|
||||
success: false,
|
||||
error: '业务库暂无库存监控数据，无法定位统计基准日',
|
||||
});
|
||||
}
|
||||
|
||||
const { shipFrom, shipTo } = buildShipWindow(asOf, days);
|
||||
|
||||
// 仓库过滤：只允许出现在仓库清单里的 wmsCoId，防止任意拼参
|
||||
const known = new Map(
|
||||
DAILY_INVENTORY_BASELINE.filter((b) => b.wmsCoId != null)
|
||||
.map((b) => [String(b.wmsCoId), b])
|
||||
);
|
||||
const requested = String(req.query?.wmsCoId || '')
|
||||
.split(',')
|
||||
.map((v) => v.trim())
|
||||
.filter((v) => known.has(v));
|
||||
const wmsCoIds = requested.length > 0 ? requested : [...known.keys()];
|
||||
|
||||
const rows = await fetchZeroSaleSkuRows(cloudDb, wmsCoIds, { shipFrom, shipTo, days });
|
||||
|
||||
const sheetRows = rows.map((r) => {
|
||||
const base = known.get(r.wmsCoId);
|
||||
return [
|
||||
base?.warehouse || r.wmsCoId,
|
||||
r.skuId,
|
||||
r.skuName,
|
||||
r.binName,
|
||||
r.stockQty,
|
||||
r.salesQty,
|
||||
days,
|
||||
latestBizDate || '',
|
||||
];
|
||||
});
|
||||
|
||||
const scopeLabel = requested.length === 1 ? `-${known.get(requested[0]).warehouse}` : '';
|
||||
const fileName = `库存动销分析-销售0明细${scopeLabel}-${(latestBizDate || '').replace(/-/g, '') || '未知日期'}`;
|
||||
const { totalRows } = sendWorkbookDownload(res, {
|
||||
fileName,
|
||||
format,
|
||||
sheets: [{
|
||||
name: '销售=0明细',
|
||||
header: ['仓库', 'SKU编码', 'SKU名称', '系统仓位', '库存数量', `销量(近${days}天)`, '统计天数', '统计基准日'],
|
||||
rows: sheetRows,
|
||||
}],
|
||||
});
|
||||
console.log(`[stock-sales-analysis] 销售=0明细导出: ${totalRows} 行, 仓库 ${wmsCoIds.length} 个, 窗口 ${days} 天`);
|
||||
return null;
|
||||
} catch (error) {
|
||||
console.error('[stock-sales-analysis] 销售=0明细导出失败:', error.message);
|
||||
// 响应可能已部分写出（sendWorkbookDownload 之后一般不会抛），仅在未发送时回 JSON
|
||||
if (!res.headersSent) {
|
||||
return res.status(500).json({
|
||||
success: false,
|
||||
error: '销售=0明细导出失败',
|
||||
detail: error.message,
|
||||
});
|
||||
}
|
||||
return null;
|
||||
}
|
||||
});
|
||||
|
||||
module.exports = router;
|
||||
@ -1,62 +0,0 @@
|
||||
'use strict';
|
||||
|
||||
/**
|
||||
* 仓储中心 24 小时发货时效 —— HTTP 路由（2026-10-20 新增）
|
||||
* ────────────────────────────────────────────────────────────────────────────
|
||||
* GET /api/warehouse-ship-timeliness/list
|
||||
* query:
|
||||
* round 'NOON' | 'AFTERNOON' 手动指定核验轮次；不传按当前时刻自动判定
|
||||
* limit 明细条数上限（默认 500，最大 2000）
|
||||
*
|
||||
* GET /api/warehouse-ship-timeliness/rounds
|
||||
* 只返回今日两轮的描述（页面顶部提示用，不打订单表，秒回）
|
||||
*
|
||||
* 挂载见 src/index.js：`/api/warehouse-ship-timeliness` + authMiddleware
|
||||
*/
|
||||
|
||||
const express = require('express');
|
||||
const { getShipTimeliness } = require('../services/warehouseShipTimelinessService');
|
||||
const { describeRounds, CENTERS } = require('../services/warehouseShipTimelinessRegistry');
|
||||
|
||||
const router = express.Router();
|
||||
|
||||
function sendError(res, error, fallback) {
|
||||
const status = Number(error?.statusCode) || 500;
|
||||
console.error('[WarehouseShipTimeliness]', {
|
||||
message: error?.message || fallback,
|
||||
code: error?.code || null,
|
||||
status,
|
||||
});
|
||||
res.status(status).json({ success: false, error: error.message || fallback });
|
||||
}
|
||||
|
||||
// 时效总览：每个主仓「超时未发」数量 + 超时订单明细
|
||||
router.get('/list', async (req, res) => {
|
||||
try {
|
||||
const data = await getShipTimeliness(req.query || {});
|
||||
res.json({ success: true, data });
|
||||
} catch (error) {
|
||||
sendError(res, error, '加载仓储中心发货时效失败');
|
||||
}
|
||||
});
|
||||
|
||||
// 仅轮次信息（不查订单）
|
||||
router.get('/rounds', async (_req, res) => {
|
||||
try {
|
||||
res.json({
|
||||
success: true,
|
||||
data: {
|
||||
rounds: describeRounds(new Date()),
|
||||
centers: CENTERS.map((c) => ({
|
||||
key: c.key,
|
||||
name: c.name,
|
||||
placeholder: Boolean(c.placeholder),
|
||||
})),
|
||||
},
|
||||
});
|
||||
} catch (error) {
|
||||
sendError(res, error, '加载核验轮次失败');
|
||||
}
|
||||
});
|
||||
|
||||
module.exports = router;
|
||||
@ -764,20 +764,7 @@ async function connectWithCandidate(candidate) {
|
||||
}
|
||||
|
||||
async function queryWithCandidateConnection(candidate, sqlText, params = {}, options = {}) {
|
||||
// request.timeout（请求级）在 mssql 12.x 上实测不生效（始终按池配置的默认值掐断），
|
||||
// 慢查询必须通过「池配置级 requestTimeout」放宽，这里允许调用方覆盖候选连接的池级超时。
|
||||
let mssqlConfig = candidate.mssqlConfig;
|
||||
const poolRequestTimeout = parsePositiveInt(options.connectRequestTimeoutMs, 0);
|
||||
if (poolRequestTimeout > 0) {
|
||||
mssqlConfig = {
|
||||
...candidate.mssqlConfig,
|
||||
options: {
|
||||
...candidate.mssqlConfig.options,
|
||||
requestTimeout: poolRequestTimeout,
|
||||
},
|
||||
};
|
||||
}
|
||||
const nextPool = new sql.ConnectionPool(mssqlConfig);
|
||||
const nextPool = new sql.ConnectionPool(candidate.mssqlConfig);
|
||||
|
||||
try {
|
||||
await nextPool.connect();
|
||||
@ -1106,28 +1093,6 @@ const queryWithFreshConnection = async (sqlText, params = {}, options = {}) => {
|
||||
return [];
|
||||
};
|
||||
|
||||
/**
|
||||
* 慢查询专用入口：走独立临时连接，池级 requestTimeout 放宽到 SLOW_QUERY_POOL_TIMEOUT_MS。
|
||||
* 背景：mssql 12.x 的 request.timeout（请求级）不生效，超过池默认 60s 的查询必须用
|
||||
* 池配置级 requestTimeout 才能放宽。适用场景：动销分析这类多表大窗口聚合。
|
||||
*/
|
||||
const SLOW_QUERY_POOL_TIMEOUT_MS = parsePositiveInt(
|
||||
process.env.CLOUD_DB_SLOW_QUERY_TIMEOUT_MS,
|
||||
300000
|
||||
);
|
||||
|
||||
const querySlow = async (sqlText, params = {}, options = {}) => {
|
||||
const poolRequestTimeout = parsePositiveInt(
|
||||
options.connectRequestTimeoutMs,
|
||||
SLOW_QUERY_POOL_TIMEOUT_MS
|
||||
);
|
||||
return queryWithFreshConnection(sqlText, params, {
|
||||
...options,
|
||||
connectRequestTimeoutMs: poolRequestTimeout,
|
||||
requestTimeout: poolRequestTimeout,
|
||||
});
|
||||
};
|
||||
|
||||
/**
|
||||
* 测试连接
|
||||
*/
|
||||
@ -1178,7 +1143,6 @@ const reload = async () => {
|
||||
module.exports = {
|
||||
getPool,
|
||||
query,
|
||||
querySlow,
|
||||
queryWithFreshConnection,
|
||||
createPinnedQueryClient,
|
||||
test,
|
||||
|
||||
@ -1,216 +1,558 @@
|
||||
/**
|
||||
* 每日进销存 —— 仓库清单（纯映射，不含业务数值）
|
||||
* 每日进销存 —— 2026-09-22 进销存基准流水
|
||||
*
|
||||
* 重要：本文件只描述「要统计哪些仓库」以及它们与聚水潭 wms_co_id 的对应关系，
|
||||
* 不再硬编码任何业务数值。所有数字都从数据库取：
|
||||
* - 期初数量：本地快照表 daily_inventory_snapshot 中「上一业务日」的期末结存
|
||||
* - 期末数量：业务库实时库存 rpt.jst_inventoryInfo（按 wms_co_id 单仓）
|
||||
* - 周转率 / 四级库存量：近 30 天发货 × 实时库存 × SKU 库龄，见 src/api/dailyInventory.js
|
||||
* - 12 个流水列：4 列可从业务库单据表还原（采购进仓/采购退货/销售出仓/销售退货，
|
||||
* 见 src/services/dailyInventoryFlows.js）；其余 8 列缺调拨/盘点/加工/其它出入库单据表，
|
||||
* 暂无法显示（前端渲染为「—」）
|
||||
* 来源：桌面《库存监控.xlsx》（聚水潭 22 号进销存导出）
|
||||
* 用途：业务库 JSReportReplica 没有按天的历史库存结存表，也缺少调拨/盘点/加工/其它出入库
|
||||
* 单据表，期初与各流水列无法从业务库还原，故以该导出作为 22 号基准值。
|
||||
*
|
||||
* 仓库清单随聚水潭仓库档案变化时需同步维护（来源表：rpt.jst_warehouseInfo）。
|
||||
* 口径约定：
|
||||
* - openingQty 与 12 个流水列：22 号基准值（本文件静态存储）
|
||||
* - 期末数量：运行时取 jst_inventoryInfo 实时库存（与本文件基准期末一致，24/25 精确）
|
||||
* - 库存周转天数 / 四级库存量：运行时由 pm_stockMonitor 计算
|
||||
*/
|
||||
|
||||
/** 一级/二级菜单名 */
|
||||
/** 一级/二级菜单名（取自表格） */
|
||||
const DAILY_INVENTORY_LEVEL1 = '大货库存监控';
|
||||
const DAILY_INVENTORY_LEVEL2 = '每日进销存';
|
||||
|
||||
/** 12 个流水列的中文表头与字段映射（顺序与聚水潭进销存导出一致） */
|
||||
const FLOW_COLUMNS = [
|
||||
{
|
||||
"label": "加工进仓",
|
||||
"field": "processIn"
|
||||
},
|
||||
{
|
||||
"label": "采购退货",
|
||||
"field": "purchaseReturn"
|
||||
},
|
||||
{
|
||||
"label": "采购进仓",
|
||||
"field": "purchaseIn"
|
||||
},
|
||||
{
|
||||
"label": "其它进仓",
|
||||
"field": "otherIn"
|
||||
},
|
||||
{
|
||||
"label": "其它退货",
|
||||
"field": "otherReturn"
|
||||
},
|
||||
{
|
||||
"label": "销售出仓",
|
||||
"field": "salesOut"
|
||||
},
|
||||
{
|
||||
"label": "盘点",
|
||||
"field": "stocktaking"
|
||||
},
|
||||
{
|
||||
"label": "加工出仓",
|
||||
"field": "processOut"
|
||||
},
|
||||
{
|
||||
"label": "调拨出",
|
||||
"field": "transferOut"
|
||||
},
|
||||
{
|
||||
"label": "销售退货",
|
||||
"field": "salesReturn"
|
||||
},
|
||||
{
|
||||
"label": "调拨入",
|
||||
"field": "transferIn"
|
||||
},
|
||||
{
|
||||
"label": "其它出库",
|
||||
"field": "otherOut"
|
||||
}
|
||||
];
|
||||
/** 基准数据日期 */
|
||||
const BASELINE_DATE = '2026-09-22';
|
||||
|
||||
/** 纳入口径的仓库（warehouse = 聚水潭主仓名，dbWarehouse = 库存监控表仓库名） */
|
||||
/** 12 个流水列的中文表头与字段映射（顺序与表格一致） */
|
||||
const FLOW_COLUMNS = [
|
||||
{
|
||||
"label": "加工进仓",
|
||||
"field": "processIn"
|
||||
},
|
||||
{
|
||||
"label": "采购退货",
|
||||
"field": "purchaseReturn"
|
||||
},
|
||||
{
|
||||
"label": "采购进仓",
|
||||
"field": "purchaseIn"
|
||||
},
|
||||
{
|
||||
"label": "其它进仓",
|
||||
"field": "otherIn"
|
||||
},
|
||||
{
|
||||
"label": "其它退货",
|
||||
"field": "otherReturn"
|
||||
},
|
||||
{
|
||||
"label": "销售出仓",
|
||||
"field": "salesOut"
|
||||
},
|
||||
{
|
||||
"label": "盘点",
|
||||
"field": "stocktaking"
|
||||
},
|
||||
{
|
||||
"label": "加工出仓",
|
||||
"field": "processOut"
|
||||
},
|
||||
{
|
||||
"label": "调拨出",
|
||||
"field": "transferOut"
|
||||
},
|
||||
{
|
||||
"label": "销售退货",
|
||||
"field": "salesReturn"
|
||||
},
|
||||
{
|
||||
"label": "调拨入",
|
||||
"field": "transferIn"
|
||||
},
|
||||
{
|
||||
"label": "其它出库",
|
||||
"field": "otherOut"
|
||||
}
|
||||
];
|
||||
|
||||
/** 25 个仓库的 22 号基准流水 */
|
||||
const DAILY_INVENTORY_BASELINE = [
|
||||
{
|
||||
"warehouse": "简尚-崔桥工厂半成品包装项目仓主仓",
|
||||
"dbWarehouse": "简尚-崔桥工厂半成品包装项目仓",
|
||||
"wmsCoId": 15718196
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-崔桥工厂仓主仓",
|
||||
"dbWarehouse": "简尚-崔桥工厂仓",
|
||||
"wmsCoId": 15038426
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-山东青岗集仓主仓",
|
||||
"dbWarehouse": "简尚-山东青岗集仓",
|
||||
"wmsCoId": 15137523
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-河南洛宁仓主仓",
|
||||
"dbWarehouse": "简尚-河南洛宁仓",
|
||||
"wmsCoId": 15539084
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-新苏北仓主仓",
|
||||
"dbWarehouse": "简尚-新苏北仓",
|
||||
"wmsCoId": 15038347
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-横林二仓主仓",
|
||||
"dbWarehouse": "简尚-横林二仓",
|
||||
"wmsCoId": 15033302
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-横林三仓主仓",
|
||||
"dbWarehouse": "简尚-横林三仓",
|
||||
"wmsCoId": 15043561
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-山东品牌仓主仓",
|
||||
"dbWarehouse": "简尚-山东品牌仓",
|
||||
"wmsCoId": 15182705
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-睢宁仓主仓",
|
||||
"dbWarehouse": "简尚-睢宁仓",
|
||||
"wmsCoId": 15032603
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-分销部专用仓主仓",
|
||||
"dbWarehouse": "简尚-分销部专用仓",
|
||||
"wmsCoId": 15045426
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-新外贸仓主仓",
|
||||
"dbWarehouse": "简尚-新外贸仓",
|
||||
"wmsCoId": 15045308
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-分销部睢宁专用仓主仓",
|
||||
"dbWarehouse": "简尚-分销部睢宁专用仓",
|
||||
"wmsCoId": 15051960
|
||||
},
|
||||
{
|
||||
"warehouse": "京仓-山东青岗集京东自营仓主仓",
|
||||
"dbWarehouse": "京仓-山东青岗集京东自营仓",
|
||||
"wmsCoId": 15835935
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-崔桥工厂品牌仓主仓",
|
||||
"dbWarehouse": "简尚-崔桥工厂品牌仓",
|
||||
"wmsCoId": 15870495
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-分销部苏北专用仓主仓",
|
||||
"dbWarehouse": "简尚-分销部苏北专用仓",
|
||||
"wmsCoId": 15045325
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-运营C横林二仓专用仓主仓",
|
||||
"dbWarehouse": "简尚-运营C横林二仓专用仓",
|
||||
"wmsCoId": 15301814
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-济南外贸仓主仓",
|
||||
"dbWarehouse": "简尚-济南外贸仓",
|
||||
"wmsCoId": 15051888
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-分销部崔桥专用仓主仓",
|
||||
"dbWarehouse": "简尚-分销部崔桥专用仓",
|
||||
"wmsCoId": 15404402
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-运营C崔桥工厂仓专用仓主仓",
|
||||
"dbWarehouse": "简尚-运营C崔桥工厂仓专用仓",
|
||||
"wmsCoId": 15301815
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-运营D苏北专用仓主仓",
|
||||
"dbWarehouse": "简尚-运营D苏北专用仓",
|
||||
"wmsCoId": 15406876
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-运营C睢宁专用仓主仓",
|
||||
"dbWarehouse": "简尚-运营C睢宁专用仓",
|
||||
"wmsCoId": 15301813
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-运营C新苏北专用仓主仓",
|
||||
"dbWarehouse": "简尚-运营C新苏北专用仓",
|
||||
"wmsCoId": 15301812
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-运营D睢宁专用仓主仓",
|
||||
"dbWarehouse": "简尚-运营D睢宁专用仓",
|
||||
"wmsCoId": 15051907
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-山东青岗集京东仓主仓",
|
||||
"dbWarehouse": "简尚-山东青岗集京东仓",
|
||||
"wmsCoId": 15406664
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-运营D专用仓库主仓",
|
||||
"dbWarehouse": "简尚-运营D专用仓库",
|
||||
"wmsCoId": 15051915
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-崔桥工厂京东仓主仓",
|
||||
"dbWarehouse": "简尚-崔桥工厂京东仓",
|
||||
"wmsCoId": 15045345
|
||||
},
|
||||
{
|
||||
"warehouse": "京仓-横林二仓京东自营仓主仓",
|
||||
"dbWarehouse": "京仓-横林二仓京东自营仓",
|
||||
"wmsCoId": 15835893
|
||||
}
|
||||
];
|
||||
{
|
||||
"warehouse": "简尚-崔桥工厂仓主仓",
|
||||
"dbWarehouse": "简尚-崔桥工厂仓",
|
||||
"wmsCoId": 15038426,
|
||||
"openingQty": 92388,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": -3924,
|
||||
"stocktaking": -1,
|
||||
"processOut": 0,
|
||||
"transferOut": -1461,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 5437,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-山东青岗集仓主仓",
|
||||
"dbWarehouse": "简尚-山东青岗集仓",
|
||||
"wmsCoId": 15137523,
|
||||
"openingQty": 88377,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 886,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": -1058,
|
||||
"stocktaking": -1,
|
||||
"processOut": 0,
|
||||
"transferOut": -11,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 23,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-河南洛宁仓主仓",
|
||||
"dbWarehouse": "简尚-河南洛宁仓",
|
||||
"wmsCoId": 15539084,
|
||||
"openingQty": 83305,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": -314,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 15,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-新苏北仓主仓",
|
||||
"dbWarehouse": "简尚-新苏北仓",
|
||||
"wmsCoId": 15038347,
|
||||
"openingQty": 77145,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": -1744,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 649,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-横林二仓主仓",
|
||||
"dbWarehouse": "简尚-横林二仓",
|
||||
"wmsCoId": 15033302,
|
||||
"openingQty": 63780,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": -982,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": -17,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 728,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-山东品牌仓主仓",
|
||||
"dbWarehouse": "简尚-山东品牌仓",
|
||||
"wmsCoId": 15182705,
|
||||
"openingQty": 41025,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 150,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": -157,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": -5,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 4,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-睢宁仓主仓",
|
||||
"dbWarehouse": "简尚-睢宁仓",
|
||||
"wmsCoId": 15032603,
|
||||
"openingQty": 25761,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": -922,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 333,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-分销部专用仓主仓",
|
||||
"dbWarehouse": "简尚-分销部专用仓",
|
||||
"wmsCoId": 15045426,
|
||||
"openingQty": 6380,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": -264,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 200,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-新外贸仓主仓",
|
||||
"dbWarehouse": "简尚-新外贸仓",
|
||||
"wmsCoId": 15045308,
|
||||
"openingQty": 5165,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": 0,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 0,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "京仓-横林二仓京东自营仓主仓",
|
||||
"dbWarehouse": "京仓-横林二仓京东自营仓",
|
||||
"wmsCoId": 15835893,
|
||||
"openingQty": 4260,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": 0,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 0,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-分销部睢宁专用仓主仓",
|
||||
"dbWarehouse": "简尚-分销部睢宁专用仓",
|
||||
"wmsCoId": 15051960,
|
||||
"openingQty": 3711,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": 0,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 0,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-崔桥工厂品牌仓主仓",
|
||||
"dbWarehouse": "简尚-崔桥工厂品牌仓",
|
||||
"wmsCoId": 15870495,
|
||||
"openingQty": 1831,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 94,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": -53,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 0,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-分销部苏北专用仓主仓",
|
||||
"dbWarehouse": "简尚-分销部苏北专用仓",
|
||||
"wmsCoId": 15045325,
|
||||
"openingQty": 1440,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": 0,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 0,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-运营C横林二仓专用仓主仓",
|
||||
"dbWarehouse": "简尚-运营C横林二仓专用仓",
|
||||
"wmsCoId": 15301814,
|
||||
"openingQty": 2141,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": -992,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 0,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-济南外贸仓主仓",
|
||||
"dbWarehouse": "简尚-济南外贸仓",
|
||||
"wmsCoId": 15051888,
|
||||
"openingQty": 712,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": 0,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 0,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-分销部崔桥专用仓主仓",
|
||||
"dbWarehouse": "简尚-分销部崔桥专用仓",
|
||||
"wmsCoId": 15404402,
|
||||
"openingQty": 620,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": 0,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 0,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-运营C崔桥工厂仓专用仓主仓",
|
||||
"dbWarehouse": "简尚-运营C崔桥工厂仓专用仓",
|
||||
"wmsCoId": 15301815,
|
||||
"openingQty": 286,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": 0,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 0,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-运营D苏北专用仓主仓",
|
||||
"dbWarehouse": "简尚-运营D苏北专用仓",
|
||||
"wmsCoId": 15406876,
|
||||
"openingQty": 280,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": 0,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 0,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-运营C睢宁专用仓主仓",
|
||||
"dbWarehouse": "简尚-运营C睢宁专用仓",
|
||||
"wmsCoId": 15301813,
|
||||
"openingQty": 193,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": 0,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 0,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-运营C新苏北专用仓主仓",
|
||||
"dbWarehouse": "简尚-运营C新苏北专用仓",
|
||||
"wmsCoId": 15301812,
|
||||
"openingQty": 155,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": 0,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 0,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-运营D睢宁专用仓主仓",
|
||||
"dbWarehouse": "简尚-运营D睢宁专用仓",
|
||||
"wmsCoId": 15051907,
|
||||
"openingQty": 109,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": -1,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 0,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-山东青岗集京东仓主仓",
|
||||
"dbWarehouse": "简尚-山东青岗集京东仓",
|
||||
"wmsCoId": 15406664,
|
||||
"openingQty": 90,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": 0,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 0,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-运营D专用仓库主仓",
|
||||
"dbWarehouse": "简尚-运营D专用仓库",
|
||||
"wmsCoId": 15051915,
|
||||
"openingQty": 180,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": -125,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 0,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "简尚-崔桥工厂京东仓主仓",
|
||||
"dbWarehouse": "简尚-崔桥工厂京东仓",
|
||||
"wmsCoId": 15045345,
|
||||
"openingQty": 1,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": 0,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 0,
|
||||
"otherOut": 0
|
||||
},
|
||||
{
|
||||
"warehouse": "京仓-横林二仓京东云仓主仓",
|
||||
"dbWarehouse": "京仓-横林二仓京东云仓",
|
||||
"wmsCoId": 15197138,
|
||||
"openingQty": -3082,
|
||||
"openingQtyExtra": 0,
|
||||
"processIn": 0,
|
||||
"purchaseReturn": 0,
|
||||
"purchaseIn": 0,
|
||||
"otherIn": 0,
|
||||
"otherReturn": 0,
|
||||
"salesOut": -48,
|
||||
"stocktaking": 0,
|
||||
"processOut": 0,
|
||||
"transferOut": 0,
|
||||
"salesReturn": 0,
|
||||
"transferIn": 0,
|
||||
"otherOut": 0
|
||||
}
|
||||
];
|
||||
|
||||
module.exports = {
|
||||
DAILY_INVENTORY_LEVEL1,
|
||||
DAILY_INVENTORY_LEVEL2,
|
||||
BASELINE_DATE,
|
||||
FLOW_COLUMNS,
|
||||
DAILY_INVENTORY_BASELINE,
|
||||
};
|
||||
|
||||
@ -1,184 +0,0 @@
|
||||
/**
|
||||
* 每日进销存 —— 聚水潭「官方进销存导出」校正数据
|
||||
*
|
||||
* 背景：业务库（MSSQL / JSReportReplica）只能还原 4/12 个流水列，且口径与
|
||||
* 聚水潭进销存报表不一致（采购按单据日期 vs 实际入库、销售出仓按订单发货 vs 出库单等），
|
||||
* 其余 8 个流水列（调拨/盘点/加工/其它出入库）业务库根本没有对应单据表。
|
||||
* 因此「每日进销存」以聚水潭官方导出的进销存报表为准：
|
||||
* 官方有值 → 直接采用（source = official）
|
||||
* 官方无值 → 回退业务库自动推算（source = derived）
|
||||
*
|
||||
* 存储：本地 MySQL 表 daily_inventory_official，主键 (biz_date, warehouse)。
|
||||
*/
|
||||
const { getPool } = require('./dailyInventorySnapshotDb');
|
||||
|
||||
const TABLE = 'daily_inventory_official';
|
||||
|
||||
/** 流水列 field（与 dailyInventoryBaseline.FLOW_COLUMNS 一致）→ 数据库列名 */
|
||||
const FLOW_DB_COLUMNS = {
|
||||
processIn: 'process_in',
|
||||
purchaseReturn: 'purchase_return',
|
||||
purchaseIn: 'purchase_in',
|
||||
otherIn: 'other_in',
|
||||
otherReturn: 'other_return',
|
||||
salesOut: 'sales_out',
|
||||
stocktaking: 'stocktaking',
|
||||
processOut: 'process_out',
|
||||
transferOut: 'transfer_out',
|
||||
salesReturn: 'sales_return',
|
||||
transferIn: 'transfer_in',
|
||||
otherOut: 'other_out',
|
||||
};
|
||||
|
||||
const CREATE_SQL = `
|
||||
CREATE TABLE IF NOT EXISTS ${TABLE} (
|
||||
id BIGINT AUTO_INCREMENT PRIMARY KEY,
|
||||
biz_date DATE NOT NULL COMMENT '业务日期',
|
||||
wms_co_id BIGINT NULL COMMENT '聚水潭仓库 ID（未知仓为空）',
|
||||
warehouse VARCHAR(128) NOT NULL COMMENT '仓库名（聚水潭主仓）',
|
||||
opening_qty DECIMAL(18,2) NULL COMMENT '期初数量',
|
||||
closing_qty DECIMAL(18,2) NULL COMMENT '期末数量',
|
||||
process_in DECIMAL(18,2) NULL COMMENT '加工进仓',
|
||||
purchase_return DECIMAL(18,2) NULL COMMENT '采购退货',
|
||||
purchase_in DECIMAL(18,2) NULL COMMENT '采购进仓',
|
||||
other_in DECIMAL(18,2) NULL COMMENT '其它进仓',
|
||||
other_return DECIMAL(18,2) NULL COMMENT '其它退货',
|
||||
sales_out DECIMAL(18,2) NULL COMMENT '销售出仓',
|
||||
stocktaking DECIMAL(18,2) NULL COMMENT '盘点',
|
||||
process_out DECIMAL(18,2) NULL COMMENT '加工出仓',
|
||||
transfer_out DECIMAL(18,2) NULL COMMENT '调拨出',
|
||||
sales_return DECIMAL(18,2) NULL COMMENT '销售退货',
|
||||
transfer_in DECIMAL(18,2) NULL COMMENT '调拨入',
|
||||
other_out DECIMAL(18,2) NULL COMMENT '其它出库',
|
||||
source VARCHAR(32) NOT NULL DEFAULT 'jst-export' COMMENT '数据来源',
|
||||
created_at DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP,
|
||||
updated_at DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
|
||||
UNIQUE KEY uk_date_wh (biz_date, warehouse),
|
||||
KEY idx_date (biz_date)
|
||||
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='每日进销存-聚水潭官方进销存校正数据';`;
|
||||
|
||||
async function ensureTable() {
|
||||
await getPool().query(CREATE_SQL);
|
||||
}
|
||||
|
||||
const num = (v) => {
|
||||
if (v == null || v === '') return null;
|
||||
const n = Number(v);
|
||||
return Number.isFinite(n) ? n : null;
|
||||
};
|
||||
|
||||
/**
|
||||
* 写入某业务日的官方进销存（幂等，重复导入覆盖）
|
||||
* @param {string} bizDate
|
||||
* @param {Array<{warehouse:string, wmsCoId?:number|null, openingQty?:number|null, closingQty?:number|null, flows?:Object}>} rows
|
||||
* @param {string} source
|
||||
*/
|
||||
async function upsertOfficial(bizDate, rows, source = 'jst-export') {
|
||||
if (!bizDate || !rows.length) return 0;
|
||||
await ensureTable();
|
||||
const conn = await getPool().getConnection();
|
||||
try {
|
||||
for (const r of rows) {
|
||||
const flows = r.flows || {};
|
||||
await conn.query(
|
||||
`INSERT INTO ${TABLE}
|
||||
(biz_date, wms_co_id, warehouse, opening_qty, closing_qty,
|
||||
process_in, purchase_return, purchase_in, other_in, other_return,
|
||||
sales_out, stocktaking, process_out, transfer_out, sales_return, transfer_in, other_out, source)
|
||||
VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)
|
||||
ON DUPLICATE KEY UPDATE
|
||||
wms_co_id = VALUES(wms_co_id),
|
||||
opening_qty = VALUES(opening_qty), closing_qty = VALUES(closing_qty),
|
||||
process_in = VALUES(process_in), purchase_return = VALUES(purchase_return),
|
||||
purchase_in = VALUES(purchase_in), other_in = VALUES(other_in),
|
||||
other_return = VALUES(other_return), sales_out = VALUES(sales_out),
|
||||
stocktaking = VALUES(stocktaking), process_out = VALUES(process_out),
|
||||
transfer_out = VALUES(transfer_out), sales_return = VALUES(sales_return),
|
||||
transfer_in = VALUES(transfer_in), other_out = VALUES(other_out),
|
||||
source = VALUES(source)`,
|
||||
[
|
||||
bizDate,
|
||||
r.wmsCoId ?? null,
|
||||
r.warehouse,
|
||||
num(r.openingQty),
|
||||
num(r.closingQty),
|
||||
num(flows.processIn), num(flows.purchaseReturn), num(flows.purchaseIn),
|
||||
num(flows.otherIn), num(flows.otherReturn), num(flows.salesOut),
|
||||
num(flows.stocktaking), num(flows.processOut), num(flows.transferOut),
|
||||
num(flows.salesReturn), num(flows.transferIn), num(flows.otherOut),
|
||||
source,
|
||||
]
|
||||
);
|
||||
}
|
||||
return rows.length;
|
||||
} finally {
|
||||
conn.release();
|
||||
}
|
||||
}
|
||||
|
||||
/** 删除某业务日的官方数据（重新导入前清理） */
|
||||
async function deleteOfficial(bizDate) {
|
||||
if (!bizDate) return 0;
|
||||
await ensureTable();
|
||||
const [res] = await getPool().query(`DELETE FROM ${TABLE} WHERE biz_date = ?`, [bizDate]);
|
||||
return res.affectedRows || 0;
|
||||
}
|
||||
|
||||
/** 读取某业务日的官方进销存：key = 仓库名 */
|
||||
async function fetchOfficial(bizDate) {
|
||||
const map = new Map();
|
||||
if (!bizDate) return map;
|
||||
try {
|
||||
await ensureTable();
|
||||
const cols = Object.values(FLOW_DB_COLUMNS).map((c) => `o.${c} AS ${c}`).join(', ');
|
||||
const [rows] = await getPool().query(
|
||||
`SELECT o.wms_co_id AS wmsCoId, o.warehouse AS warehouse,
|
||||
o.opening_qty AS openingQty, o.closing_qty AS closingQty, o.source AS source,
|
||||
${cols}
|
||||
FROM ${TABLE} o WHERE o.biz_date = ?`,
|
||||
[bizDate]
|
||||
);
|
||||
const dbToField = Object.fromEntries(Object.entries(FLOW_DB_COLUMNS).map(([f, c]) => [c, f]));
|
||||
rows.forEach((r) => {
|
||||
const flows = {};
|
||||
for (const [col, field] of Object.entries(dbToField)) flows[field] = num(r[col]);
|
||||
map.set(String(r.warehouse), {
|
||||
warehouse: r.warehouse,
|
||||
wmsCoId: r.wmsCoId == null ? null : Number(r.wmsCoId),
|
||||
openingQty: num(r.openingQty),
|
||||
closingQty: num(r.closingQty),
|
||||
source: r.source,
|
||||
flows,
|
||||
});
|
||||
});
|
||||
} catch (error) {
|
||||
console.error('[daily-inventory-official] 读取官方数据失败:', error.message);
|
||||
}
|
||||
return map;
|
||||
}
|
||||
|
||||
/** 已有官方数据的业务日（倒序） */
|
||||
async function listOfficialDates(limit = 30) {
|
||||
try {
|
||||
await ensureTable();
|
||||
const [rows] = await getPool().query(
|
||||
`SELECT DISTINCT biz_date AS d FROM ${TABLE} ORDER BY biz_date DESC LIMIT ?`,
|
||||
[Number(limit) || 30]
|
||||
);
|
||||
return rows.map((r) => (typeof r.d === 'string' ? r.d.slice(0, 10) : String(r.d).slice(0, 10)));
|
||||
} catch (error) {
|
||||
console.error('[daily-inventory-official] 读取官方日期失败:', error.message);
|
||||
return [];
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
TABLE,
|
||||
CREATE_SQL,
|
||||
FLOW_DB_COLUMNS,
|
||||
ensureTable,
|
||||
upsertOfficial,
|
||||
deleteOfficial,
|
||||
fetchOfficial,
|
||||
listOfficialDates,
|
||||
};
|
||||
@ -1,137 +0,0 @@
|
||||
/**
|
||||
* 每日进销存 —— 本地库存快照库访问
|
||||
*
|
||||
* 背景：业务库（MSSQL / JSReportReplica）只有「当前」实时库存 jst_inventoryInfo，
|
||||
* 没有按天的历史库存结存表，因此「期初数量」无法回溯。
|
||||
* 解决办法：项目本地 MySQL 每天落一份按仓库存的快照，
|
||||
* 今日期初 = 上一业务日快照，期末 = 实时库存。
|
||||
*
|
||||
* 连接复用 LOCAL_DB_* 配置（与项目其它本地表同库）。
|
||||
*/
|
||||
const path = require('path');
|
||||
const dotenv = require('dotenv');
|
||||
const mysql = require('mysql2/promise');
|
||||
|
||||
dotenv.config();
|
||||
dotenv.config({ path: path.resolve(__dirname, '../../.env') });
|
||||
|
||||
const TABLE = 'daily_inventory_snapshot';
|
||||
|
||||
const CREATE_SQL = `
|
||||
CREATE TABLE IF NOT EXISTS ${TABLE} (
|
||||
id BIGINT AUTO_INCREMENT PRIMARY KEY,
|
||||
biz_date DATE NOT NULL COMMENT '业务日期（T-1）',
|
||||
wms_co_id BIGINT NOT NULL COMMENT '聚水潭仓库 ID',
|
||||
warehouse VARCHAR(128) NOT NULL COMMENT '仓库名（主仓）',
|
||||
db_warehouse VARCHAR(128) NULL COMMENT '监控表仓库名',
|
||||
closing_qty DECIMAL(18,2) NOT NULL DEFAULT 0 COMMENT '该业务日期末数量',
|
||||
sku_count INT NOT NULL DEFAULT 0 COMMENT '有库存 SKU 数',
|
||||
taken_at DATETIME NULL COMMENT '源库库存数据更新时间',
|
||||
created_at DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP,
|
||||
updated_at DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
|
||||
UNIQUE KEY uk_date_wh (biz_date, wms_co_id),
|
||||
KEY idx_date (biz_date)
|
||||
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='每日进销存-按仓库存快照';`;
|
||||
|
||||
let pool = null;
|
||||
|
||||
function getPool() {
|
||||
if (pool) return pool;
|
||||
pool = mysql.createPool({
|
||||
host: process.env.LOCAL_DB_HOST,
|
||||
port: Number(process.env.LOCAL_DB_PORT || 3306),
|
||||
user: process.env.LOCAL_DB_USER,
|
||||
password: process.env.LOCAL_DB_PASSWORD,
|
||||
database: process.env.LOCAL_DB_NAME,
|
||||
waitForConnections: true,
|
||||
connectionLimit: 5,
|
||||
connectTimeout: 10000,
|
||||
// DATE/DATETIME 直接返回字符串，避免 JS Date 按本地时区回读时整体偏移一天
|
||||
dateStrings: true,
|
||||
});
|
||||
return pool;
|
||||
}
|
||||
|
||||
async function ensureTable() {
|
||||
await getPool().query(CREATE_SQL);
|
||||
}
|
||||
|
||||
/**
|
||||
* 写入某业务日的期末快照（幂等，重复执行覆盖）
|
||||
* @param {string} bizDate YYYY-MM-DD
|
||||
* @param {Array<{wmsCoId:number, warehouse:string, dbWarehouse?:string, closingQty:number, skuCount:number, takenAt?:Date|null}>} rows
|
||||
*/
|
||||
async function upsertSnapshot(bizDate, rows) {
|
||||
if (!bizDate || !rows.length) return 0;
|
||||
await ensureTable();
|
||||
const conn = await getPool().getConnection();
|
||||
try {
|
||||
for (const r of rows) {
|
||||
await conn.query(
|
||||
`INSERT INTO ${TABLE} (biz_date, wms_co_id, warehouse, db_warehouse, closing_qty, sku_count, taken_at)
|
||||
VALUES (?, ?, ?, ?, ?, ?, ?)
|
||||
ON DUPLICATE KEY UPDATE warehouse = VALUES(warehouse), db_warehouse = VALUES(db_warehouse),
|
||||
closing_qty = VALUES(closing_qty), sku_count = VALUES(sku_count), taken_at = VALUES(taken_at)`,
|
||||
[bizDate, r.wmsCoId, r.warehouse, r.dbWarehouse || null, r.closingQty, r.skuCount, r.takenAt || null]
|
||||
);
|
||||
}
|
||||
return rows.length;
|
||||
} finally {
|
||||
conn.release();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 读取某业务日的期末快照
|
||||
* @returns {Promise<Map<string, {closingQty:number, skuCount:number, takenAt:Date|null}>>} key = wmsCoId 字符串
|
||||
*/
|
||||
async function fetchSnapshot(bizDate) {
|
||||
const map = new Map();
|
||||
if (!bizDate) return map;
|
||||
try {
|
||||
await ensureTable();
|
||||
const [rows] = await getPool().query(
|
||||
`SELECT wms_co_id AS wmsCoId, closing_qty AS closingQty, sku_count AS skuCount, taken_at AS takenAt
|
||||
FROM ${TABLE} WHERE biz_date = ?`,
|
||||
[bizDate]
|
||||
);
|
||||
rows.forEach((r) => map.set(String(r.wmsCoId), {
|
||||
closingQty: Number(r.closingQty),
|
||||
skuCount: Number(r.skuCount),
|
||||
takenAt: r.takenAt || null,
|
||||
}));
|
||||
} catch (error) {
|
||||
console.error('[daily-inventory-snapshot] 读取快照失败:', error.message);
|
||||
}
|
||||
return map;
|
||||
}
|
||||
|
||||
/** 已有快照的业务日（倒序，最多 n 条） */
|
||||
async function listSnapshotDates(limit = 10) {
|
||||
try {
|
||||
await ensureTable();
|
||||
const [rows] = await getPool().query(
|
||||
`SELECT DISTINCT biz_date AS d FROM ${TABLE} ORDER BY biz_date DESC LIMIT ?`,
|
||||
[Number(limit) || 10]
|
||||
);
|
||||
return rows.map((r) => {
|
||||
if (typeof r.d === 'string') return r.d.slice(0, 10);
|
||||
const v = new Date(r.d);
|
||||
const pad = (n) => String(n).padStart(2, '0');
|
||||
return `${v.getFullYear()}-${pad(v.getMonth() + 1)}-${pad(v.getDate())}`;
|
||||
});
|
||||
} catch (error) {
|
||||
console.error('[daily-inventory-snapshot] 读取快照日期失败:', error.message);
|
||||
return [];
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
TABLE,
|
||||
CREATE_SQL,
|
||||
getPool,
|
||||
ensureTable,
|
||||
upsertSnapshot,
|
||||
fetchSnapshot,
|
||||
listSnapshotDates,
|
||||
};
|
||||
@ -1,78 +0,0 @@
|
||||
/**
|
||||
* 拣选库位动销分析 —— 口径配置（纯规则，不含业务数值）
|
||||
*
|
||||
* 一级菜单：大货库存监控
|
||||
* 二级菜单：拣选库位动销分析
|
||||
*
|
||||
* 表头（需求表原列为 所在仓库 | 仓位 | 数量 | 类型 | 动销等级，这里做了扩充与优化）：
|
||||
* 仓库 | 仓位 | 类型 | 商品编码 | 库存数量 | 近N天销量 | 日销 | 动销等级
|
||||
*
|
||||
* 粒度：仓位 × 商品编码（一个仓位有 N 个商品就输出 N 行），列表与导出共用。
|
||||
*
|
||||
* 口径：
|
||||
* 库存数量：rpt.jst_packInventoryInfo 按 wms_co_id + 仓位 + sku_id 汇总 qty
|
||||
* 统计范围：只统计真实拣选仓位（pack_type=Bin 且 bin_group 为空）；
|
||||
* 箱记录（pack_type=Pack）与存货位（bin_group=存货）不纳入
|
||||
* 销量： 4 个来源分支，均按 send_date 窗口（详见 services/pickingBinSalesAnalysis.js）：
|
||||
* ① jst_Orders 普通行；② jst_Orders 组合装行 → jst_comboProductItem 展开为子件；
|
||||
* ③ jst_qmcust_orderlist（全民客户 B2B 分销）普通行（排除拆单父单 Split）；
|
||||
* ④ qmcust 组合装行 → 同样展开。
|
||||
* 日销： 商品窗口销量 / 窗口天数（整档，不按仓位分摊）
|
||||
* 等级： 严格按商品日销判定，同一商品占多少个仓位都是同一等级
|
||||
*
|
||||
* 【为什么不分摊来定等级】同一 SKU 常常同时占用多个同类型仓位（崔桥工厂仓实测 3290 个
|
||||
* 拣选 SKU 中 1431 个跨多个拣选位，最多 24 个）。若把销量摊到仓位再定等级，
|
||||
* 一件爆款商品放在 10 个仓位就会被算成日销 1/10 的滞销品 —— 判断的是「摆法」而不是「商品」。
|
||||
* 因此等级一律以商品自身的销售速度为准。
|
||||
*
|
||||
* 【分摊销量列】导出仍附带「分摊销量」= 商品销量 ÷ 其占用的同类型仓位数，
|
||||
* 供需要按行求和的场景使用：恒等式（已实测校验，差异 0）
|
||||
* 全部行分摊销量之和 = 有库位记录的那些 SKU 的销量之和。
|
||||
* 注意它小于「全仓销量」：jst_packInventoryInfo 只覆盖部分 SKU 的仓位数据，
|
||||
* 没有仓位记录的 SKU 的销量不会体现在任何库位上。
|
||||
*/
|
||||
|
||||
const PICKING_BIN_LEVEL1 = '大货库存监控';
|
||||
const PICKING_BIN_LEVEL2 = '拣选库位动销分析';
|
||||
|
||||
/** 可选的统计窗口天数；默认 30 天（需求指定按近 30 天销量划分动销等级） */
|
||||
const PICKING_BIN_WINDOW_OPTIONS = [7, 15, 30, 60];
|
||||
const PICKING_BIN_DEFAULT_DAYS = 30;
|
||||
|
||||
/**
|
||||
* 仓位类型：本功能只统计真实拣选仓位（pack_type=Bin 且 bin_group 为空）。
|
||||
* 箱记录（pack_type=Pack）和存货位（bin_group=存货）不纳入动销等级统计，
|
||||
* 取数在仓位库存表上直接过滤，
|
||||
* 页面也不再提供类型切换。
|
||||
*/
|
||||
const BIN_TYPE_PICKING = '拣选';
|
||||
/** 固定统计范围：仅拣选位（保持数组形式，便于接口字段与后续扩展） */
|
||||
const PICKING_BIN_BIN_TYPES = [BIN_TYPE_PICKING];
|
||||
|
||||
/**
|
||||
* 动销等级（顺序即展示顺序）。判定依据为「商品日销」= 商品窗口整档销量 ÷ 天数，
|
||||
* 不做仓位分摊，同一商品在所有仓位显示同一等级。
|
||||
* lower 为日销下界（含），upper 为日销上界（不含）；null 表示不限制。
|
||||
* zero 档为「窗口内无销量」，由 salesQty <= 0 兜底。
|
||||
*/
|
||||
const PICKING_BIN_GRADE_RULES = [
|
||||
{ key: 'hot', label: '爆款：日销≥20', lower: 20, upper: null, tip: '商品日均销量 ≥ 20 件' },
|
||||
{ key: 'best', label: '热卖款：10≤日销＜20', lower: 10, upper: 20, tip: '商品日均销量 10 ~ 20 件（含 10，不含 20）' },
|
||||
{ key: 'normal', label: '平销款：3≤日销＜10', lower: 3, upper: 10, tip: '商品日均销量 3 ~ 10 件（含 3，不含 10）' },
|
||||
{ key: 'slow1', label: '滞销款-1：1≤日销＜3', lower: 1, upper: 3, tip: '商品日均销量 1 ~ 3 件（含 1，不含 3）' },
|
||||
{ key: 'slow2', label: '滞销款-2：0＜日销＜1', lower: 0, upper: 1, tip: '商品日均销量大于 0 且小于 1 件' },
|
||||
{ key: 'zero', label: '销售=0', lower: 0, upper: 0, tip: '统计窗口内该商品无销量（仍占用库存）' },
|
||||
];
|
||||
|
||||
const PICKING_BIN_TOTAL_LABEL = '汇总';
|
||||
|
||||
module.exports = {
|
||||
PICKING_BIN_LEVEL1,
|
||||
PICKING_BIN_LEVEL2,
|
||||
PICKING_BIN_WINDOW_OPTIONS,
|
||||
PICKING_BIN_DEFAULT_DAYS,
|
||||
BIN_TYPE_PICKING,
|
||||
PICKING_BIN_BIN_TYPES,
|
||||
PICKING_BIN_GRADE_RULES,
|
||||
PICKING_BIN_TOTAL_LABEL,
|
||||
};
|
||||
@ -1,47 +0,0 @@
|
||||
/**
|
||||
* 仓库库存动销分析 —— 口径配置（纯规则，不含业务数值）
|
||||
*
|
||||
* 一级菜单：大货库存监控
|
||||
* 二级菜单：库存动销分析
|
||||
*
|
||||
* 表头（与需求表一致）：仓库 | 动销等级 | SKU数量 | SKU占比 | 库存数量 | 库存占比 | 销量
|
||||
*
|
||||
* 口径：
|
||||
* 日销（日均销量）= 统计窗口内已发货件数 / 窗口天数
|
||||
* 动销等级按「单个 SKU 的日销」分档，落在哪一档就计入哪一档
|
||||
* 仓库内汇总：SKU占比 = 该等级 SKU 数 / 该仓库 SKU 总数
|
||||
* 库存占比 = 该等级库存件数 / 该仓库库存总件数
|
||||
* 仓库清单与「每日进销存」保持同一份（DAILY_INVENTORY_BASELINE）
|
||||
*/
|
||||
|
||||
const STOCK_SALES_LEVEL1 = '大货库存监控';
|
||||
const STOCK_SALES_LEVEL2 = '库存动销分析';
|
||||
|
||||
/** 可选的统计窗口天数；默认 30 天 */
|
||||
const STOCK_SALES_WINDOW_OPTIONS = [7, 14, 30];
|
||||
const STOCK_SALES_DEFAULT_DAYS = 30;
|
||||
|
||||
/**
|
||||
* 动销等级（顺序即表格行顺序，汇总行由 total 单独给出）。
|
||||
* lower 为日销下界（含），upper 为日销上界（不含）；null 表示不限制。
|
||||
*/
|
||||
const SALES_GRADE_RULES = [
|
||||
{ key: 'hot', label: '爆款：日销≥20', lower: 20, upper: null, tip: '单个 SKU 日均销量 ≥ 20 件' },
|
||||
{ key: 'best', label: '热卖款：10≤日销＜20', lower: 10, upper: 20, tip: '单个 SKU 日均销量 10 ~ 20 件（含 10，不含 20）' },
|
||||
{ key: 'normal', label: '平销款：3≤日销＜10', lower: 3, upper: 10, tip: '单个 SKU 日均销量 3 ~ 10 件（含 3，不含 10）' },
|
||||
{ key: 'slow1', label: '滞销款-1：1≤日销＜3', lower: 1, upper: 3, tip: '单个 SKU 日均销量 1 ~ 3 件（含 1，不含 3）' },
|
||||
{ key: 'slow2', label: '滞销款-2：0＜日销＜1', lower: 0, upper: 1, tip: '单个 SKU 日均销量大于 0 且小于 1 件' },
|
||||
{ key: 'zero', label: '销售=0', lower: 0, upper: 0, tip: '统计窗口内无销量的 SKU（仍占用库存）' },
|
||||
];
|
||||
|
||||
/** 汇总行的等级名（表内展示用） */
|
||||
const SALES_TOTAL_LABEL = '汇总';
|
||||
|
||||
module.exports = {
|
||||
STOCK_SALES_LEVEL1,
|
||||
STOCK_SALES_LEVEL2,
|
||||
STOCK_SALES_WINDOW_OPTIONS,
|
||||
STOCK_SALES_DEFAULT_DAYS,
|
||||
SALES_GRADE_RULES,
|
||||
SALES_TOTAL_LABEL,
|
||||
};
|
||||
@ -40,16 +40,6 @@ const SIDEBAR_PAGES = [
|
||||
path: '/planning/operation/mkh-bom-data',
|
||||
}),
|
||||
buildPlanningPage({ pageKey: 'work_orders', pageName: '工单待办', path: '/planning/operation/work-orders' }),
|
||||
buildPlanningPage({
|
||||
pageKey: 'stock_sales_analysis',
|
||||
pageName: '大货库存监控 · 库存动销分析',
|
||||
path: '/planning/operation/stock-sales-analysis',
|
||||
}),
|
||||
buildPlanningPage({
|
||||
pageKey: 'picking_bin_sales_analysis',
|
||||
pageName: '大货库存监控 · 拣选库位动销分析',
|
||||
path: '/planning/operation/picking-bin-sales-analysis',
|
||||
}),
|
||||
{
|
||||
pageKey: 'settings',
|
||||
pageName: '系统设置',
|
||||
|
||||
@ -35,11 +35,7 @@ const promotionModuleRoutes = require('./api/promotionModule');
|
||||
const productMonitoringRoutes = require('./api/productMonitoring');
|
||||
const modularStockMonitorRoutes = require('./api/modularStockMonitor');
|
||||
const mkhBomRoutes = require('./api/mkhBom');
|
||||
const warehouseShipTimelinessRoutes = require('./api/warehouseShipTimeliness');
|
||||
const dailyInventoryRoutes = require('./api/dailyInventory');
|
||||
const dailyInventoryNotificationRoutes = require('./api/dailyInventoryNotification');
|
||||
const stockSalesAnalysisRoutes = require('./api/stockSalesAnalysis');
|
||||
const pickingBinSalesAnalysisRoutes = require('./api/pickingBinSalesAnalysis');
|
||||
const returnInventoryWarningRoutes = require('./api/returnInventoryWarning');
|
||||
const returnMonitorRoutes = require('./api/returnMonitor');
|
||||
const returnStockWarningRoutes = require('./api/returnStockWarning');
|
||||
@ -55,12 +51,6 @@ const { startPlanningMayProductSnapshotSchedulers } = require('./jobs/planningMa
|
||||
const { startPlanningDingWorkflowSyncSchedulers } = require('./jobs/planningDingWorkflowSyncJob');
|
||||
const { startOpsBIncentiveSnapshotSchedulers } = require('./jobs/opsBIncentiveSnapshotJob');
|
||||
const { startGoodsFirstSeenScheduler } = require('./jobs/goodsFirstSeenJob');
|
||||
const {
|
||||
startDailyInventorySnapshotScheduler,
|
||||
} = require('./jobs/dailyInventorySnapshotJob');
|
||||
const {
|
||||
startDailyInventoryNotificationScheduler,
|
||||
} = require('./jobs/dailyInventoryNotificationJob');
|
||||
const {
|
||||
startAlibaba1688ImageSearchExpiryScheduler,
|
||||
} = require('./jobs/alibaba1688ImageSearchExpiryJob');
|
||||
@ -673,12 +663,7 @@ async function startServer(options = {}) {
|
||||
cubejsApp.use('/api/product-monitoring', authMiddleware, productMonitoringRoutes);
|
||||
cubejsApp.use('/api/modular-stock-monitor', authMiddleware, modularStockMonitorRoutes);
|
||||
cubejsApp.use('/api/mkh-bom', authMiddleware, mkhBomRoutes);
|
||||
// 仓储中心 24 小时发货时效（2026-10-20 新增）：列表左侧侧栏，11 个主仓超时未发
|
||||
cubejsApp.use('/api/warehouse-ship-timeliness', authMiddleware, warehouseShipTimelinessRoutes);
|
||||
cubejsApp.use('/api/daily-inventory', authMiddleware, dailyInventoryRoutes);
|
||||
cubejsApp.use('/api/daily-inventory-notification', authMiddleware, dailyInventoryNotificationRoutes);
|
||||
cubejsApp.use('/api/stock-sales-analysis', authMiddleware, stockSalesAnalysisRoutes);
|
||||
cubejsApp.use('/api/picking-bin-sales-analysis', authMiddleware, pickingBinSalesAnalysisRoutes);
|
||||
cubejsApp.use('/api/return-inventory-warning', authMiddleware, returnInventoryWarningRoutes);
|
||||
// 崔桥工厂仓客退：退货入库核销 + 每日库存监控
|
||||
cubejsApp.use('/api/return-monitor', authMiddleware, returnMonitorRoutes);
|
||||
@ -768,11 +753,6 @@ async function startServer(options = {}) {
|
||||
console.log(` [缓存] ${redisTest.message}`);
|
||||
console.log('='.repeat(50));
|
||||
|
||||
// 每日进销存截图通知：与「后台定时任务总开关」解耦，保证即使总开关关闭，
|
||||
// 只要功能启用就仍会按配置时间推送（可用 DAILY_INVENTORY_NOTIFICATION_ENABLED=false 单独关闭）。
|
||||
// 它每分钟只做一次轻量判断，命中配置时间才真正截图上传。
|
||||
startDailyInventoryNotificationScheduler();
|
||||
|
||||
if (String(process.env.ENABLE_BACKGROUND_JOBS || 'true').toLowerCase() === 'false') {
|
||||
console.log('⏸️ 后台定时任务和预热已关闭，业务请求按需处理');
|
||||
return;
|
||||
@ -788,7 +768,6 @@ async function startServer(options = {}) {
|
||||
startGoodsFirstSeenScheduler();
|
||||
startAlibaba1688ImageSearchExpiryScheduler();
|
||||
startMkhReplenishAlertScheduler();
|
||||
startDailyInventorySnapshotScheduler();
|
||||
|
||||
// Keep the first selection-pool page request from paying the remote schema
|
||||
// inspection round-trip over the planning database tunnel.
|
||||
|
||||
@ -1,351 +0,0 @@
|
||||
'use strict';
|
||||
|
||||
// 每日进销存 · 定时截图通知
|
||||
//
|
||||
// 执行流程：
|
||||
// ① 单实例锁（MySQL GET_LOCK），避免多实例重复截图推送
|
||||
// ② 校验：功能开启 / 有收件人 / 通知中心已配置 / 对象存储已配置，任一不满足就记录原因并退出
|
||||
// ③ 按配置时间（默认 01:00 Asia/Shanghai）触发；业务日期 = 北京时间昨日（与页面 T-1 口径一致）
|
||||
// ④ 截图 → 上传对象存储 → 拿到公开 HTTPS 地址后才发通知
|
||||
// ⑤ 逐用户发送，用「业务日期 + 收件人」幂等键去重；单人失败不影响其他人
|
||||
// ⑥ 截图/上传/通知失败均做有限次数重试与指数退避
|
||||
// ⑦ 每次执行都落一条记录（时间 / 截图地址 / 通知对象 / 成功状态 / 失败原因）
|
||||
//
|
||||
// 立即测试（mode='test'）：走同一条链路，但幂等键带随机数，**不写入正式幂等记录**，
|
||||
// 因此不会影响下一次正式定时推送。
|
||||
|
||||
const crypto = require('crypto');
|
||||
const cron = require('node-cron');
|
||||
const database = require('../config/database');
|
||||
const {
|
||||
appendRunRecord,
|
||||
buildIdempotencyKey,
|
||||
getDailyInventoryNotificationRuntimeConfig,
|
||||
getObjectStorageStatus,
|
||||
hasNotified,
|
||||
loadDailyInventoryNotificationState,
|
||||
markNotified,
|
||||
normalizeRecipients,
|
||||
} = require('../services/dailyInventoryNotificationSettings');
|
||||
const {
|
||||
captureAndUploadDailyInventory,
|
||||
chinaTimeParts,
|
||||
resolvePageUrl,
|
||||
} = require('../services/dailyInventoryScreenshot');
|
||||
const {
|
||||
getYydNotificationCenterRuntimeConfig,
|
||||
isYydNotificationCenterConfigured,
|
||||
sendYydNotification,
|
||||
} = require('../services/yydNotificationCenterClient');
|
||||
const TIMEZONE = 'Asia/Shanghai';
|
||||
const LOCK_KEY = 'daily_inventory_notification_job';
|
||||
const LOCK_WAIT_SECONDS = 2;
|
||||
const NOTIFICATION_TITLE = '每日进销存数据';
|
||||
const ACTION_TITLE = '查看每日进销存';
|
||||
|
||||
// 重试策略：最多 3 次，退避 2s / 4s
|
||||
const MAX_ATTEMPTS = 3;
|
||||
const RETRY_BASE_DELAY_MS = 2000;
|
||||
// 命中时间后允许补跑的窗口与次数上限（防止全天每分钟重试刷屏）
|
||||
const RETRY_WINDOW_MINUTES = 30;
|
||||
const MAX_SCHEDULED_ATTEMPTS_PER_DAY = 3;
|
||||
|
||||
let running = false;
|
||||
let timer = null;
|
||||
|
||||
const sleep = (ms) => new Promise((resolve) => setTimeout(resolve, ms));
|
||||
|
||||
/** 有限次数重试 + 指数退避 */
|
||||
async function withRetry(task, { label, attempts = MAX_ATTEMPTS, baseDelayMs = RETRY_BASE_DELAY_MS } = {}) {
|
||||
let lastError = null;
|
||||
for (let index = 0; index < attempts; index += 1) {
|
||||
try {
|
||||
return await task();
|
||||
} catch (error) {
|
||||
lastError = error;
|
||||
const delay = baseDelayMs * (2 ** index);
|
||||
console.error(
|
||||
`[DailyInventoryNotify] ${label} 第 ${index + 1}/${attempts} 次失败：${error.message}`
|
||||
+ `${index < attempts - 1 ? `，${delay}ms 后重试` : ''}`
|
||||
);
|
||||
if (index < attempts - 1) await sleep(delay);
|
||||
}
|
||||
}
|
||||
throw lastError;
|
||||
}
|
||||
|
||||
/** 业务日期 = 北京时间昨日（页面标注 T-1，凌晨跑批产出昨日快照） */
|
||||
function resolveBizDate(now = new Date()) {
|
||||
const target = now instanceof Date ? now : new Date(now);
|
||||
const shifted = new Date(target.getTime() - 24 * 60 * 60 * 1000);
|
||||
return chinaTimeParts(shifted).bizDate;
|
||||
}
|
||||
|
||||
function beijingTimeText(date = new Date()) {
|
||||
const target = date instanceof Date ? date : new Date(date);
|
||||
return new Intl.DateTimeFormat('zh-CN', {
|
||||
timeZone: TIMEZONE,
|
||||
year: 'numeric', month: '2-digit', day: '2-digit',
|
||||
hour: '2-digit', minute: '2-digit', second: '2-digit',
|
||||
hour12: false,
|
||||
}).format(target);
|
||||
}
|
||||
|
||||
function currentBeijingHhMm(now = new Date()) {
|
||||
const text = new Intl.DateTimeFormat('en-GB', {
|
||||
timeZone: TIMEZONE, hour: '2-digit', minute: '2-digit', hour12: false,
|
||||
}).format(now instanceof Date ? now : new Date(now));
|
||||
return text;
|
||||
}
|
||||
|
||||
/** 全实例锁：拿到锁才继续执行，拿不到说明其它实例正在跑 */
|
||||
async function withJobLock(runner) {
|
||||
const pool = database.local.pool;
|
||||
let connection = null;
|
||||
try {
|
||||
connection = await pool.getConnection();
|
||||
const [rows] = await connection.query('SELECT GET_LOCK(?, ?) AS lockStatus', [LOCK_KEY, LOCK_WAIT_SECONDS]);
|
||||
const acquired = Number(rows?.[0]?.lockStatus || 0) === 1;
|
||||
if (!acquired) {
|
||||
return { success: false, skipped: true, reason: 'lock_not_acquired' };
|
||||
}
|
||||
return await runner();
|
||||
} catch (error) {
|
||||
return { success: false, skipped: true, reason: 'lock_error', error: error.message };
|
||||
} finally {
|
||||
if (connection) {
|
||||
try {
|
||||
await connection.query('DO RELEASE_LOCK(?)', [LOCK_KEY]);
|
||||
} catch (_error) {
|
||||
// ignore
|
||||
}
|
||||
connection.release();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
function buildNotificationContent({ bizDate, takenAt, imageUrl, pageUrl }) {
|
||||
return [
|
||||
`**数据日期：** ${bizDate}`,
|
||||
`**截图生成时间：** ${takenAt}（${TIMEZONE}）`,
|
||||
`**图片地址：** ${imageUrl}`,
|
||||
`**页面地址：** ${pageUrl}`,
|
||||
'',
|
||||
`点击右下角「${ACTION_TITLE}」可直达每日进销存页面。`,
|
||||
].join('\n');
|
||||
}
|
||||
|
||||
/**
|
||||
* 执行一次（正式 / 测试）
|
||||
* @param {Object} options
|
||||
* mode 'scheduled' | 'manual' | 'test'
|
||||
* force true 时忽略「今天已调度过」的节流判断（手动触发用）
|
||||
* now 指定执行时刻，便于测试
|
||||
*/
|
||||
async function runDailyInventoryNotificationJob(options = {}) {
|
||||
const mode = options.mode || 'scheduled';
|
||||
const now = options.now ? new Date(options.now) : new Date();
|
||||
const startedAt = now.toISOString();
|
||||
|
||||
if (running) {
|
||||
return { success: false, skipped: true, reason: 'already_running' };
|
||||
}
|
||||
running = true;
|
||||
|
||||
try {
|
||||
return await withJobLock(async () => {
|
||||
const config = await getDailyInventoryNotificationRuntimeConfig({ forceRefresh: true });
|
||||
const recipients = normalizeRecipients(config.recipients);
|
||||
const bizDate = resolveBizDate(now);
|
||||
|
||||
const finish = async (payload) => {
|
||||
await appendRunRecord({ ...payload, runAt: startedAt, bizDate, mode, notifyTime: config.notifyTime });
|
||||
return payload;
|
||||
};
|
||||
|
||||
if (!config.enabled) {
|
||||
return finish({ success: false, reason: 'disabled', error: '功能未启用' });
|
||||
}
|
||||
if (!recipients.length) {
|
||||
return finish({ success: false, reason: 'no_recipient', error: '未配置通知用户' });
|
||||
}
|
||||
|
||||
let centerConfig = null;
|
||||
try {
|
||||
centerConfig = await getYydNotificationCenterRuntimeConfig();
|
||||
} catch (_error) {
|
||||
centerConfig = null;
|
||||
}
|
||||
if (!isYydNotificationCenterConfigured(centerConfig)) {
|
||||
return finish({ success: false, reason: 'notification_center_not_configured', error: '统一通知中心未配置' });
|
||||
}
|
||||
|
||||
const storage = await getObjectStorageStatus();
|
||||
if (!storage.configured) {
|
||||
return finish({ success: false, reason: 'object_storage_not_configured', error: '对象存储未配置' });
|
||||
}
|
||||
|
||||
// 截图 → 上传（失败直接结束，绝不发通知）
|
||||
let shot;
|
||||
try {
|
||||
shot = await withRetry(
|
||||
// 对象键按业务日期归档：daily-inventory/2026-09-25/daily-inventory-20260925-010000.png
|
||||
() => captureAndUploadDailyInventory({ now, bizDate }),
|
||||
{ label: '截图并上传' }
|
||||
);
|
||||
} catch (error) {
|
||||
return finish({ success: false, reason: 'screenshot_failed', error: error.message });
|
||||
}
|
||||
|
||||
const pageUrl = resolvePageUrl();
|
||||
const takenAt = beijingTimeText(now);
|
||||
const nonce = crypto.randomBytes(8).toString('hex');
|
||||
|
||||
const deliveries = [];
|
||||
for (const recipient of recipients) {
|
||||
const idempotencyKey = buildIdempotencyKey({ bizDate, recipient, mode, nonce });
|
||||
// 正式推送先查幂等：同一业务日期 + 同一用户只成功通知一次
|
||||
if (mode !== 'test' && await hasNotified(bizDate, recipient)) {
|
||||
deliveries.push({ recipient, status: 'skipped', reason: 'already_notified' });
|
||||
continue;
|
||||
}
|
||||
try {
|
||||
const response = await withRetry(
|
||||
() => sendYydNotification({
|
||||
idempotencyKey,
|
||||
recipientAlias: recipient,
|
||||
title: NOTIFICATION_TITLE,
|
||||
content: buildNotificationContent({
|
||||
bizDate, takenAt, imageUrl: shot.url, pageUrl,
|
||||
}),
|
||||
actionTitle: ACTION_TITLE,
|
||||
actionUrl: pageUrl,
|
||||
}),
|
||||
{ label: `通知 ${recipient}` }
|
||||
);
|
||||
const deliveryId = response?.id || response?.data?.id || null;
|
||||
if (mode !== 'test') await markNotified(bizDate, recipient, { deliveryId, idempotencyKey });
|
||||
deliveries.push({ recipient, status: 'sent', deliveryId });
|
||||
} catch (error) {
|
||||
// 单人失败不阻断其他人
|
||||
console.error(`[DailyInventoryNotify] 通知 ${recipient} 失败：${error.message}`);
|
||||
deliveries.push({ recipient, status: 'failed', error: error.message });
|
||||
}
|
||||
}
|
||||
|
||||
const sentCount = deliveries.filter((d) => d.status === 'sent').length;
|
||||
const failedCount = deliveries.filter((d) => d.status === 'failed').length;
|
||||
const success = sentCount > 0;
|
||||
|
||||
console.log(
|
||||
`[DailyInventoryNotify] ${mode} 完成：业务日 ${bizDate}，截图 ${shot.url}，`
|
||||
+ `通知成功 ${sentCount} / 失败 ${failedCount} / 跳过 ${deliveries.length - sentCount - failedCount}`
|
||||
);
|
||||
|
||||
return finish({
|
||||
success,
|
||||
reason: success ? null : 'notify_failed',
|
||||
error: success ? null : '所有收件人均通知失败',
|
||||
screenshotUrl: shot.url,
|
||||
screenshotKey: shot.key,
|
||||
rowCount: shot.rowCount,
|
||||
recipients: deliveries,
|
||||
});
|
||||
});
|
||||
} finally {
|
||||
running = false;
|
||||
}
|
||||
}
|
||||
|
||||
/** 同一业务日期已经发起过的正式调度次数与最后一次结果（用于失败重试节流） */
|
||||
async function scheduledAttemptStatus(bizDate) {
|
||||
const state = await loadDailyInventoryNotificationState();
|
||||
const runs = (Array.isArray(state.runs) ? state.runs : [])
|
||||
.filter((r) => r.bizDate === bizDate && r.mode === 'scheduled');
|
||||
return {
|
||||
count: runs.length,
|
||||
lastSuccess: runs.length ? runs[runs.length - 1].success === true : null,
|
||||
};
|
||||
}
|
||||
|
||||
function minutesOfDay(hhmm) {
|
||||
const match = /^(\d{1,2}):(\d{2})$/.exec(String(hhmm || ''));
|
||||
if (!match) return null;
|
||||
const hour = Number(match[1]);
|
||||
const minute = Number(match[2]);
|
||||
if (hour > 23 || minute > 59) return null;
|
||||
return hour * 60 + minute;
|
||||
}
|
||||
|
||||
/**
|
||||
* 是否应当发起一次正式调度：
|
||||
* · 恰好命中配置时间 → 执行
|
||||
* · 命中时间之后的 RETRY_WINDOW_MINUTES 分钟内 → 仅在上一次失败且未超出重试上限时补跑
|
||||
* · 其余时间 → 不执行
|
||||
*/
|
||||
async function shouldRunScheduled(config, now) {
|
||||
const target = minutesOfDay(config.notifyTime);
|
||||
const current = minutesOfDay(currentBeijingHhMm(now));
|
||||
if (target === null || current === null) return false;
|
||||
|
||||
const diff = current - target;
|
||||
if (diff < 0 || diff > RETRY_WINDOW_MINUTES) return false;
|
||||
if (diff === 0) return true;
|
||||
|
||||
const status = await scheduledAttemptStatus(resolveBizDate(now));
|
||||
return status.lastSuccess === false && status.count < MAX_SCHEDULED_ATTEMPTS_PER_DAY;
|
||||
}
|
||||
|
||||
function startDailyInventoryNotificationScheduler() {
|
||||
const disabled = String(process.env.DAILY_INVENTORY_NOTIFICATION_ENABLED || 'true').trim().toLowerCase() === 'false';
|
||||
if (disabled) {
|
||||
console.log('[DailyInventoryNotify] 已通过环境变量关闭');
|
||||
return null;
|
||||
}
|
||||
if (timer) return timer;
|
||||
// 每分钟检查一次：命中配置的通知时间才真正执行，配置改动无需重启
|
||||
timer = cron.schedule('* * * * *', async () => {
|
||||
try {
|
||||
const config = await getDailyInventoryNotificationRuntimeConfig({ forceRefresh: true });
|
||||
if (!config.enabled) return;
|
||||
const now = new Date();
|
||||
if (!(await shouldRunScheduled(config, now))) return;
|
||||
await runDailyInventoryNotificationJob({ mode: 'scheduled', now });
|
||||
} catch (error) {
|
||||
console.error('[DailyInventoryNotify] 定时检查失败:', error.message);
|
||||
}
|
||||
}, { timezone: TIMEZONE });
|
||||
|
||||
console.log(
|
||||
`[Scheduler] 每日进销存截图通知已注册（按配置时间触发，${TIMEZONE}，`
|
||||
+ `失败后 ${RETRY_WINDOW_MINUTES} 分钟内最多补跑 ${MAX_SCHEDULED_ATTEMPTS_PER_DAY} 次）`
|
||||
);
|
||||
return timer;
|
||||
}
|
||||
|
||||
function stopDailyInventoryNotificationScheduler() {
|
||||
if (timer) {
|
||||
timer.stop();
|
||||
timer = null;
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
ACTION_TITLE,
|
||||
LOCK_KEY,
|
||||
MAX_ATTEMPTS,
|
||||
MAX_SCHEDULED_ATTEMPTS_PER_DAY,
|
||||
NOTIFICATION_TITLE,
|
||||
RETRY_BASE_DELAY_MS,
|
||||
TIMEZONE,
|
||||
RETRY_WINDOW_MINUTES,
|
||||
beijingTimeText,
|
||||
buildNotificationContent,
|
||||
currentBeijingHhMm,
|
||||
minutesOfDay,
|
||||
resolveBizDate,
|
||||
runDailyInventoryNotificationJob,
|
||||
startDailyInventoryNotificationScheduler,
|
||||
stopDailyInventoryNotificationScheduler,
|
||||
withRetry,
|
||||
};
|
||||
@ -1,122 +0,0 @@
|
||||
'use strict';
|
||||
|
||||
/**
|
||||
* 每日库存快照任务
|
||||
*
|
||||
* 业务库没有按天的历史库存结存表，「期初数量」无法回溯。
|
||||
* 本任务每天定时把 26 个仓库的实时库存落一份到本地快照表 daily_inventory_snapshot，
|
||||
* 使「今日期初 = 上一业务日期末」能够自动滚动。
|
||||
*
|
||||
* 默认 01:30 执行（报表库 01:00 跑批之后）。可用环境变量覆盖：
|
||||
* DAILY_INVENTORY_SNAPSHOT_ENABLED=false 关闭
|
||||
* DAILY_INVENTORY_SNAPSHOT_CRON='30 1 * * *'
|
||||
*/
|
||||
const cron = require('node-cron');
|
||||
const cloudDb = require('../config/cloudDatabase');
|
||||
const snapshotDb = require('../config/dailyInventorySnapshotDb');
|
||||
const { DAILY_INVENTORY_BASELINE } = require('../config/dailyInventoryBaseline');
|
||||
|
||||
let running = false;
|
||||
let timer = null;
|
||||
|
||||
const JOB_ENABLED = String(process.env.DAILY_INVENTORY_SNAPSHOT_ENABLED || 'true').toLowerCase() !== 'false';
|
||||
const JOB_CRON = process.env.DAILY_INVENTORY_SNAPSHOT_CRON || '30 1 * * *';
|
||||
|
||||
/** 业务日 = 库存快照库最新日期（报表库每日凌晨跑批，标注 T-1） */
|
||||
async function resolveBizDate() {
|
||||
const rows = await cloudDb.query(
|
||||
`SELECT MAX(CONVERT(VARCHAR(10), date, 23)) AS d FROM rpt.pm_stockMonitor`
|
||||
);
|
||||
return rows[0]?.d || null;
|
||||
}
|
||||
|
||||
function buildInClause(values, prefix) {
|
||||
const params = {};
|
||||
const clause = values
|
||||
.map((v, i) => {
|
||||
params[`${prefix}${i}`] = v;
|
||||
return `@${prefix}${i}`;
|
||||
})
|
||||
.join(',');
|
||||
return { clause, params };
|
||||
}
|
||||
|
||||
async function syncOnce(trigger = 'cron') {
|
||||
if (running) {
|
||||
console.log(`[DailyInventorySnapshot] 上一次任务未结束，跳过 trigger=${trigger}`);
|
||||
return { success: false, skipped: true, reason: 'already_running' };
|
||||
}
|
||||
running = true;
|
||||
const startedAt = Date.now();
|
||||
try {
|
||||
const bizDate = await resolveBizDate();
|
||||
if (!bizDate) {
|
||||
console.log('[DailyInventorySnapshot] 未取到业务日，跳过');
|
||||
return { success: false, skipped: true, reason: 'no_biz_date' };
|
||||
}
|
||||
|
||||
const whs = DAILY_INVENTORY_BASELINE.filter((b) => b.wmsCoId != null);
|
||||
const { clause, params } = buildInClause(whs.map((b) => b.wmsCoId), 'w');
|
||||
const rows = await cloudDb.query(
|
||||
`SELECT i.wms_co_id AS wmsCoId,
|
||||
ISNULL(SUM(CAST(i.qty AS DECIMAL(18,2))), 0) AS closingQty,
|
||||
SUM(CASE WHEN ABS(ISNULL(i.qty, 0)) > 0.0001 THEN 1 ELSE 0 END) AS skuCount,
|
||||
MAX(i.modified) AS takenAt
|
||||
FROM rpt.jst_inventoryInfo i
|
||||
WHERE i.wms_co_id IN (${clause})
|
||||
GROUP BY i.wms_co_id`,
|
||||
params,
|
||||
{ requestTimeout: 120000 }
|
||||
);
|
||||
|
||||
const m = new Map(rows.map((r) => [String(r.wmsCoId), r]));
|
||||
const payload = whs.map((b) => {
|
||||
const r = m.get(String(b.wmsCoId));
|
||||
return {
|
||||
wmsCoId: b.wmsCoId,
|
||||
warehouse: b.warehouse,
|
||||
dbWarehouse: b.dbWarehouse,
|
||||
closingQty: Number(r?.closingQty ?? 0),
|
||||
skuCount: Number(r?.skuCount ?? 0),
|
||||
takenAt: r?.takenAt ? new Date(r.takenAt) : null,
|
||||
};
|
||||
});
|
||||
|
||||
const n = await snapshotDb.upsertSnapshot(bizDate, payload);
|
||||
console.log(`[DailyInventorySnapshot] 业务日 ${bizDate} 写入 ${n}/${whs.length} 仓，耗时 ${Date.now() - startedAt}ms`);
|
||||
return { success: true, bizDate, count: n };
|
||||
} catch (error) {
|
||||
console.error('[DailyInventorySnapshot] 执行失败:', error.message);
|
||||
return { success: false, error: error.message };
|
||||
} finally {
|
||||
running = false;
|
||||
}
|
||||
}
|
||||
|
||||
function startDailyInventorySnapshotScheduler() {
|
||||
if (!JOB_ENABLED) {
|
||||
console.log('[DailyInventorySnapshot] 已通过环境变量关闭');
|
||||
return null;
|
||||
}
|
||||
if (timer) return timer;
|
||||
if (!cron.validate(JOB_CRON)) {
|
||||
console.error(`[DailyInventorySnapshot] cron 表达式非法: ${JOB_CRON}`);
|
||||
return null;
|
||||
}
|
||||
timer = cron.schedule(JOB_CRON, () => { syncOnce('cron'); }, { timezone: 'Asia/Shanghai' });
|
||||
console.log(`[DailyInventorySnapshot] 已启动，cron=${JOB_CRON} (Asia/Shanghai)`);
|
||||
return timer;
|
||||
}
|
||||
|
||||
function stopDailyInventorySnapshotScheduler() {
|
||||
if (timer) {
|
||||
timer.stop();
|
||||
timer = null;
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
syncOnce,
|
||||
startDailyInventorySnapshotScheduler,
|
||||
stopDailyInventorySnapshotScheduler,
|
||||
};
|
||||
@ -1,121 +0,0 @@
|
||||
'use strict';
|
||||
|
||||
/**
|
||||
* 每日进销存 —— 流水列取数（业务库原生口径）
|
||||
*
|
||||
* 业务库 JSReportReplica 能还原的 4 个流水列（其余 8 列缺单据表，保持「—」）：
|
||||
* 采购进仓(+): rpt.jst_purchase × jst_purchaseItem，按 po_date，状态 Confirmed/Finished，取明细 qty
|
||||
* （明细 inQty 全为 0 未同步，故用 qty）
|
||||
* 采购退货(−): rpt.jst_purchaseout × jst_purchaseoutItem，按 io_date
|
||||
* 销售出仓(−): rpt.jst_Orders × jst_OrderItem，按 send_date，排除 Delete/Cancelled
|
||||
* （与「库存周转天数」的发货口径一致；与聚水潭进销存导出的出库单口径有偏差，
|
||||
* 因为销售出库单明细数量在业务库未同步，无法精确还原）
|
||||
* 销售退货(+): rpt.jst_returnAndRefundInfo × jst_returnAndRefundItem，按 as_date，
|
||||
* 类型限定 普通退货/拒收退货/换货/维修，取明细 r_qty（实收数量；
|
||||
* qty 字段大多未同步，不能用）
|
||||
*
|
||||
* 符号约定与页面一致：流入为正、流出为负（前端负数标红）。
|
||||
* 因为还有 8 类单据（调拨/盘点/加工/其它出入库）在业务库无表，
|
||||
* 「期末 ≠ 期初 + 流水之和」，差值即缺失单据的影响。
|
||||
*/
|
||||
|
||||
const FLOW_QUERIES = [
|
||||
{
|
||||
field: 'purchaseIn',
|
||||
sign: 1,
|
||||
sql: `
|
||||
SELECT p.wms_co_id AS wmsCoId,
|
||||
SUM(CAST(ISNULL(pi.qty, 0) AS DECIMAL(18, 2))) AS qty
|
||||
FROM rpt.jst_purchase p
|
||||
JOIN rpt.jst_purchaseItem pi ON pi.po_id = p.po_id
|
||||
WHERE p.wms_co_id IN (%WAREHOUSES%)
|
||||
AND p.po_date >= @from
|
||||
AND ISNULL(p.status, '') IN ('Confirmed', 'Finished')
|
||||
GROUP BY p.wms_co_id`,
|
||||
},
|
||||
{
|
||||
field: 'purchaseReturn',
|
||||
sign: -1,
|
||||
sql: `
|
||||
SELECT o.wms_co_id AS wmsCoId,
|
||||
SUM(CAST(ISNULL(oi.qty, 0) AS DECIMAL(18, 2))) AS qty
|
||||
FROM rpt.jst_purchaseout o
|
||||
JOIN rpt.jst_purchaseoutItem oi ON oi.io_id = o.io_id
|
||||
WHERE o.wms_co_id IN (%WAREHOUSES%)
|
||||
AND o.io_date >= @from
|
||||
GROUP BY o.wms_co_id`,
|
||||
},
|
||||
{
|
||||
field: 'salesOut',
|
||||
sign: -1,
|
||||
sql: `
|
||||
SELECT o.wms_co_id AS wmsCoId,
|
||||
SUM(CAST(ISNULL(oi.qty, 0) AS DECIMAL(18, 2))) AS qty
|
||||
FROM rpt.jst_Orders o
|
||||
JOIN rpt.jst_OrderItem oi ON oi.o_id = o.o_id
|
||||
WHERE o.wms_co_id IN (%WAREHOUSES%)
|
||||
AND o.send_date >= @from
|
||||
AND ISNULL(o.status, '') NOT IN ('Delete', 'Cancelled')
|
||||
GROUP BY o.wms_co_id`,
|
||||
},
|
||||
{
|
||||
field: 'salesReturn',
|
||||
sign: 1,
|
||||
sql: `
|
||||
SELECT r.wms_co_id AS wmsCoId,
|
||||
SUM(CAST(ISNULL(ri.r_qty, 0) AS DECIMAL(18, 2))) AS qty
|
||||
FROM rpt.jst_returnAndRefundInfo r
|
||||
JOIN rpt.jst_returnAndRefundItem ri ON ri.as_id = r.as_id
|
||||
WHERE r.wms_co_id IN (%WAREHOUSES%)
|
||||
AND r.as_date >= @from
|
||||
AND ISNULL(r.type, '') IN (N'普通退货', N'拒收退货', N'换货', N'维修')
|
||||
GROUP BY r.wms_co_id`,
|
||||
},
|
||||
];
|
||||
|
||||
/** mssql 不支持数组参数，按位展开成 @p0,@p1... */
|
||||
function buildInClause(values, prefix) {
|
||||
const params = {};
|
||||
const clause = values
|
||||
.map((v, i) => {
|
||||
params[`${prefix}${i}`] = v;
|
||||
return `@${prefix}${i}`;
|
||||
})
|
||||
.join(',');
|
||||
return { clause, params };
|
||||
}
|
||||
|
||||
/** 业务库可还原的流水字段（带符号：流入 +1 / 流出 −1） */
|
||||
const AVAILABLE_FLOW_FIELDS = FLOW_QUERIES.map((q) => q.field);
|
||||
|
||||
/**
|
||||
* 拉取自 fromText（含）以来各仓的流水合计。
|
||||
* @returns {Promise<Map<string, Object>>} key = wmsCoId 字符串，value = { purchaseIn, purchaseReturn, salesOut, salesReturn }（带符号，无记录的字段不出现）
|
||||
*/
|
||||
async function fetchFlows(cloudDb, wmsCoIds, fromText) {
|
||||
if (!cloudDb || typeof cloudDb.query !== 'function') {
|
||||
throw new TypeError('fetchFlows 第一个参数必须是数据库实例（防呆：调用漏传 cloudDb 时立即报错而非静默返回空）');
|
||||
}
|
||||
const map = new Map();
|
||||
if (!wmsCoIds.length || !fromText) return map;
|
||||
for (const q of FLOW_QUERIES) {
|
||||
const { clause, params } = buildInClause(wmsCoIds, 'w');
|
||||
const sqlText = q.sql.replace('%WAREHOUSES%', clause);
|
||||
const rows = await cloudDb.query(sqlText, { ...params, from: fromText }, { requestTimeout: 120000 });
|
||||
for (const r of rows) {
|
||||
const key = String(r.wmsCoId);
|
||||
const entry = map.get(key) || {};
|
||||
const qty = Number(r.qty) || 0;
|
||||
entry[q.field] = q.sign * qty;
|
||||
map.set(key, entry);
|
||||
}
|
||||
}
|
||||
return map;
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
AVAILABLE_FLOW_FIELDS,
|
||||
FLOW_QUERIES,
|
||||
fetchFlows,
|
||||
buildInClause,
|
||||
};
|
||||
@ -1,330 +0,0 @@
|
||||
'use strict';
|
||||
|
||||
// 每日进销存 · 定时截图通知 —— 配置 + 执行记录 + 幂等记录（本地库 system_config）
|
||||
//
|
||||
// ── 配置键 daily_inventory_notification_config ────────────────────
|
||||
// { enabled, notifyTime: 'HH:mm', recipients: ['张三', '李四'] }
|
||||
//
|
||||
// ── 状态键 daily_inventory_notification_state ──────────────────────
|
||||
// { version, notified: { 'YYYY-MM-DD': { '别名': { notifiedAt, deliveryId } } }, runs: [...] }
|
||||
// · notified 用于「同一业务日期 + 同一用户只成功通知一次」的幂等判断
|
||||
// · runs 保留最近 N 次执行明细，供管理员在页面查询
|
||||
//
|
||||
// 安全约定：本文件对外只返回「是否已配置」这类布尔值与脱敏预览，
|
||||
// 绝不返回通知中心 projectSecret、对象存储 secretAccessKey 等密钥。
|
||||
|
||||
const database = require('../config/database');
|
||||
const {
|
||||
getYydNotificationCenterRuntimeConfig,
|
||||
toAdminConfig: toNotificationCenterAdminConfig,
|
||||
} = require('./yydNotificationCenterSettings');
|
||||
const { getDefaultS3Config } = require('./objectStorage');
|
||||
|
||||
const CONFIG_KEY = 'daily_inventory_notification_config';
|
||||
const STATE_KEY = 'daily_inventory_notification_state';
|
||||
|
||||
const DEFAULT_NOTIFY_TIME = '01:00';
|
||||
const TIMEZONE = 'Asia/Shanghai';
|
||||
const MAX_RECIPIENTS = 20;
|
||||
const MAX_RECIPIENT_LENGTH = 50;
|
||||
const MAX_RUN_RECORDS = 30;
|
||||
const CONFIG_CACHE_TTL_MS = 30 * 1000;
|
||||
|
||||
let cachedConfig = null;
|
||||
let cachedAt = 0;
|
||||
|
||||
function normalizeText(value, maxLength = 200) {
|
||||
return String(value ?? '').trim().slice(0, maxLength);
|
||||
}
|
||||
|
||||
function safeJsonParse(value, fallback = {}) {
|
||||
if (value && typeof value === 'object') return value;
|
||||
try {
|
||||
const parsed = JSON.parse(String(value || ''));
|
||||
return parsed && typeof parsed === 'object' ? parsed : fallback;
|
||||
} catch (_error) {
|
||||
return fallback;
|
||||
}
|
||||
}
|
||||
|
||||
function normalizeFlag(value, fallback = false) {
|
||||
if (value === undefined || value === null || value === '') return fallback;
|
||||
if (typeof value === 'boolean') return value;
|
||||
const text = String(value).trim().toLowerCase();
|
||||
if (['1', 'true', 'yes', 'on'].includes(text)) return true;
|
||||
if (['0', 'false', 'no', 'off'].includes(text)) return false;
|
||||
return fallback;
|
||||
}
|
||||
|
||||
/**
|
||||
* 通知时间规范化：只接受 HH:mm（24 小时制），非法值回退默认 01:00。
|
||||
* 允许传 'HH:mm:ss'，截断到分钟。
|
||||
*/
|
||||
function normalizeNotifyTime(value) {
|
||||
const text = normalizeText(value, 10);
|
||||
const match = /^(\d{1,2}):(\d{2})(?::\d{2})?$/.exec(text);
|
||||
if (!match) return DEFAULT_NOTIFY_TIME;
|
||||
const hour = Number(match[1]);
|
||||
const minute = Number(match[2]);
|
||||
if (!Number.isInteger(hour) || hour < 0 || hour > 23) return DEFAULT_NOTIFY_TIME;
|
||||
if (!Number.isInteger(minute) || minute < 0 || minute > 59) return DEFAULT_NOTIFY_TIME;
|
||||
return `${String(hour).padStart(2, '0')}:${String(minute).padStart(2, '0')}`;
|
||||
}
|
||||
|
||||
/**
|
||||
* 收件人名单规范化：trim → 去空 → 去重（保持输入顺序）→ 限长限量。
|
||||
* 支持数组、逗号/换行/分号分隔的字符串。
|
||||
*/
|
||||
function normalizeRecipients(input) {
|
||||
let list = [];
|
||||
if (Array.isArray(input)) {
|
||||
list = input;
|
||||
} else if (typeof input === 'string') {
|
||||
list = input.split(/[,，;；\n\r\t]+/);
|
||||
} else if (input && typeof input === 'object') {
|
||||
list = Object.values(input);
|
||||
}
|
||||
|
||||
const seen = new Set();
|
||||
const result = [];
|
||||
for (const raw of list) {
|
||||
const name = normalizeText(raw, MAX_RECIPIENT_LENGTH);
|
||||
if (!name) continue;
|
||||
if (seen.has(name)) continue;
|
||||
seen.add(name);
|
||||
result.push(name);
|
||||
if (result.length >= MAX_RECIPIENTS) break;
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
/** 幂等键：正式推送按「业务日期 + 收件人」去重；测试推送带时间戳，不污染正式记录 */
|
||||
function buildIdempotencyKey({ bizDate, recipient, mode = 'scheduled', nonce = '' }) {
|
||||
const scope = mode === 'test' ? `test:${normalizeText(nonce, 64)}` : 'daily';
|
||||
return `daily_inventory_notification:${scope}:${bizDate}:${recipient}:v1`.slice(0, 160);
|
||||
}
|
||||
|
||||
async function readSystemConfigValue(key) {
|
||||
const rows = await database.local.query(
|
||||
'SELECT config_value AS configValue FROM system_config WHERE config_key = ? LIMIT 1',
|
||||
[key]
|
||||
);
|
||||
return rows?.[0]?.configValue;
|
||||
}
|
||||
|
||||
async function upsertSystemConfigValue(key, value, configType = 'json') {
|
||||
const payload = typeof value === 'string' ? value : JSON.stringify(value);
|
||||
const rows = await database.local.query(
|
||||
'SELECT id FROM system_config WHERE config_key = ? LIMIT 1',
|
||||
[key]
|
||||
);
|
||||
if (rows?.[0]) {
|
||||
await database.local.query(
|
||||
'UPDATE system_config SET config_value = ?, config_type = ? WHERE config_key = ?',
|
||||
[payload, configType, key]
|
||||
);
|
||||
} else {
|
||||
await database.local.insert('system_config', {
|
||||
config_key: key,
|
||||
config_value: payload,
|
||||
config_type: configType,
|
||||
});
|
||||
}
|
||||
return payload;
|
||||
}
|
||||
|
||||
// ── 配置 ────────────────────────────────────────────────────────
|
||||
async function getDailyInventoryNotificationRuntimeConfig({ forceRefresh = false } = {}) {
|
||||
if (!forceRefresh && cachedConfig && Date.now() - cachedAt < CONFIG_CACHE_TTL_MS) {
|
||||
return { ...cachedConfig };
|
||||
}
|
||||
let stored = {};
|
||||
try {
|
||||
stored = safeJsonParse(await readSystemConfigValue(CONFIG_KEY), {});
|
||||
} catch (error) {
|
||||
console.warn('读取每日进销存通知配置失败，使用默认值:', error.message);
|
||||
}
|
||||
cachedConfig = {
|
||||
enabled: normalizeFlag(stored.enabled, false),
|
||||
notifyTime: normalizeNotifyTime(stored.notifyTime ?? stored.notify_time),
|
||||
recipients: normalizeRecipients(stored.recipients),
|
||||
};
|
||||
cachedAt = Date.now();
|
||||
return { ...cachedConfig };
|
||||
}
|
||||
|
||||
async function saveDailyInventoryNotificationConfig(input = {}) {
|
||||
const current = await getDailyInventoryNotificationRuntimeConfig({ forceRefresh: true });
|
||||
const next = {
|
||||
enabled: normalizeFlag(input.enabled, current.enabled),
|
||||
notifyTime: normalizeNotifyTime(
|
||||
input.notifyTime ?? input.notify_time ?? current.notifyTime
|
||||
),
|
||||
recipients: normalizeRecipients(
|
||||
input.recipients === undefined ? current.recipients : input.recipients
|
||||
),
|
||||
};
|
||||
await upsertSystemConfigValue(CONFIG_KEY, next);
|
||||
cachedConfig = { ...next };
|
||||
cachedAt = Date.now();
|
||||
return { ...next };
|
||||
}
|
||||
|
||||
// ── 执行记录 / 幂等记录 ─────────────────────────────────────────
|
||||
async function loadDailyInventoryNotificationState() {
|
||||
let parsed = {};
|
||||
try {
|
||||
parsed = safeJsonParse(await readSystemConfigValue(STATE_KEY), {});
|
||||
} catch (error) {
|
||||
console.warn('读取每日进销存通知状态失败，按空状态处理:', error.message);
|
||||
}
|
||||
const notified = parsed.notified && typeof parsed.notified === 'object' && !Array.isArray(parsed.notified)
|
||||
? parsed.notified
|
||||
: {};
|
||||
const runs = Array.isArray(parsed.runs) ? parsed.runs : [];
|
||||
return { version: 1, notified, runs };
|
||||
}
|
||||
|
||||
async function saveDailyInventoryNotificationState(state = {}) {
|
||||
const value = {
|
||||
version: 1,
|
||||
notified: state.notified && typeof state.notified === 'object' && !Array.isArray(state.notified)
|
||||
? state.notified
|
||||
: {},
|
||||
runs: Array.isArray(state.runs) ? state.runs.slice(-MAX_RUN_RECORDS) : [],
|
||||
};
|
||||
await upsertSystemConfigValue(STATE_KEY, value);
|
||||
return value;
|
||||
}
|
||||
|
||||
/** 判断某业务日期是否已成功通知过某人（只认正式推送） */
|
||||
async function hasNotified(bizDate, recipient) {
|
||||
const state = await loadDailyInventoryNotificationState();
|
||||
const day = state.notified?.[bizDate];
|
||||
return Boolean(day && day[recipient]);
|
||||
}
|
||||
|
||||
/** 记录一次成功通知（正式推送才写；测试推送不写） */
|
||||
async function markNotified(bizDate, recipient, extra = {}) {
|
||||
const state = await loadDailyInventoryNotificationState();
|
||||
const day = { ...(state.notified?.[bizDate] || {}) };
|
||||
day[recipient] = {
|
||||
notifiedAt: new Date().toISOString(),
|
||||
deliveryId: extra.deliveryId || null,
|
||||
idempotencyKey: extra.idempotencyKey || null,
|
||||
};
|
||||
const notified = { ...(state.notified || {}), [bizDate]: day };
|
||||
// 只保留最近 14 个业务日，避免状态无限膨胀
|
||||
const keys = Object.keys(notified).sort();
|
||||
const trimmed = {};
|
||||
keys.slice(-14).forEach((k) => { trimmed[k] = notified[k]; });
|
||||
return saveDailyInventoryNotificationState({ ...state, notified: trimmed });
|
||||
}
|
||||
|
||||
/** 追加一条执行记录 */
|
||||
async function appendRunRecord(record = {}) {
|
||||
const state = await loadDailyInventoryNotificationState();
|
||||
const runs = [...(state.runs || []), {
|
||||
runAt: record.runAt || new Date().toISOString(),
|
||||
bizDate: record.bizDate || null,
|
||||
mode: record.mode || 'scheduled',
|
||||
success: record.success === true,
|
||||
reason: record.reason || null,
|
||||
error: record.error || null,
|
||||
screenshotUrl: record.screenshotUrl || null,
|
||||
screenshotKey: record.screenshotKey || null,
|
||||
notifyTime: record.notifyTime || null,
|
||||
recipients: Array.isArray(record.recipients) ? record.recipients : [],
|
||||
}];
|
||||
return saveDailyInventoryNotificationState({ ...state, runs });
|
||||
}
|
||||
|
||||
function listRunRecords(limit = 10) {
|
||||
return loadDailyInventoryNotificationState().then((state) => {
|
||||
const runs = Array.isArray(state.runs) ? state.runs : [];
|
||||
return runs.slice(-Math.max(Number(limit) || 10, 1)).reverse();
|
||||
});
|
||||
}
|
||||
|
||||
// ── 管理员视图（不含任何密钥） ───────────────────────────────────
|
||||
async function getObjectStorageStatus() {
|
||||
try {
|
||||
const config = await getDefaultS3Config(false);
|
||||
return {
|
||||
configured: Boolean(config && config.bucket && config.endpoint && config.accessKeyId),
|
||||
bucket: config?.bucket || '',
|
||||
endpoint: config?.endpoint || '',
|
||||
// 只给脱敏信息，secretAccessKey 从不读取、从不返回
|
||||
accessKeyIdPreview: config?.accessKeyId
|
||||
? `${String(config.accessKeyId).slice(0, 4)}***`
|
||||
: '',
|
||||
};
|
||||
} catch (error) {
|
||||
return { configured: false, bucket: '', endpoint: '', accessKeyIdPreview: '', error: error.message };
|
||||
}
|
||||
}
|
||||
|
||||
async function getDailyInventoryNotificationAdminConfig() {
|
||||
const config = await getDailyInventoryNotificationRuntimeConfig({ forceRefresh: true });
|
||||
let center = {};
|
||||
try {
|
||||
center = await getYydNotificationCenterRuntimeConfig();
|
||||
} catch (_error) {
|
||||
center = {};
|
||||
}
|
||||
const centerAdmin = toNotificationCenterAdminConfig(center);
|
||||
const storage = await getObjectStorageStatus();
|
||||
const state = await loadDailyInventoryNotificationState();
|
||||
const runs = Array.isArray(state.runs) ? state.runs : [];
|
||||
|
||||
const blockingReasons = [];
|
||||
if (!config.enabled) blockingReasons.push('功能未启用');
|
||||
if (!config.recipients.length) blockingReasons.push('未配置通知用户');
|
||||
if (!centerAdmin.configured) blockingReasons.push('统一通知中心未配置');
|
||||
if (!storage.configured) blockingReasons.push('对象存储未配置');
|
||||
|
||||
return {
|
||||
enabled: config.enabled,
|
||||
notifyTime: config.notifyTime,
|
||||
recipients: config.recipients,
|
||||
timezone: TIMEZONE,
|
||||
maxRecipients: MAX_RECIPIENTS,
|
||||
notificationCenter: {
|
||||
configured: centerAdmin.configured,
|
||||
baseUrl: centerAdmin.baseUrl,
|
||||
projectCode: centerAdmin.projectCode,
|
||||
projectSecretConfigured: centerAdmin.projectSecretConfigured,
|
||||
projectSecretPreview: centerAdmin.projectSecretPreview,
|
||||
},
|
||||
objectStorage: storage,
|
||||
blockingReasons,
|
||||
lastRunAt: runs.length ? runs[runs.length - 1].runAt : null,
|
||||
lastRunSuccess: runs.length ? runs[runs.length - 1].success === true : null,
|
||||
runs: runs.slice(-10).reverse(),
|
||||
};
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
CONFIG_KEY,
|
||||
STATE_KEY,
|
||||
DEFAULT_NOTIFY_TIME,
|
||||
MAX_RECIPIENTS,
|
||||
MAX_RECIPIENT_LENGTH,
|
||||
MAX_RUN_RECORDS,
|
||||
TIMEZONE,
|
||||
appendRunRecord,
|
||||
buildIdempotencyKey,
|
||||
getDailyInventoryNotificationAdminConfig,
|
||||
getDailyInventoryNotificationRuntimeConfig,
|
||||
getObjectStorageStatus,
|
||||
hasNotified,
|
||||
listRunRecords,
|
||||
loadDailyInventoryNotificationState,
|
||||
markNotified,
|
||||
normalizeFlag,
|
||||
normalizeNotifyTime,
|
||||
normalizeRecipients,
|
||||
normalizeText,
|
||||
saveDailyInventoryNotificationConfig,
|
||||
saveDailyInventoryNotificationState,
|
||||
};
|
||||
@ -1,137 +0,0 @@
|
||||
/**
|
||||
* 每日进销存 —— 聚水潭官方进销存导出解析 / 导入
|
||||
*
|
||||
* 输入为聚水潭进销存报表按仓导出（xlsx），列包含：
|
||||
* 仓库、期初数量、[12 个流水列]、期末数量
|
||||
* 流水列符号沿用导出原值（出仓为负、入仓为正），前端不做二次转换。
|
||||
*/
|
||||
const XLSX = require('xlsx');
|
||||
const {
|
||||
FLOW_COLUMNS,
|
||||
DAILY_INVENTORY_BASELINE,
|
||||
} = require('../config/dailyInventoryBaseline');
|
||||
const officialDb = require('../config/dailyInventoryOfficialDb');
|
||||
|
||||
const FLOW_FIELDS = FLOW_COLUMNS.map((c) => c.field);
|
||||
|
||||
/** 流水列中文表头 → field */
|
||||
const LABEL_TO_FIELD = new Map(FLOW_COLUMNS.map((c) => [c.label, c.field]));
|
||||
|
||||
/** 仓库名 → wms_co_id（来自项目仓库清单） */
|
||||
const WAREHOUSE_TO_ID = new Map(
|
||||
DAILY_INVENTORY_BASELINE.map((b) => [b.warehouse, b.wmsCoId])
|
||||
);
|
||||
|
||||
const num = (v) => {
|
||||
if (v == null || v === '' || v === '-') return null;
|
||||
const n = Number(String(v).replace(/,/g, '').trim());
|
||||
return Number.isFinite(n) ? n : null;
|
||||
};
|
||||
|
||||
/**
|
||||
* 把「表头 → 值」的记录数组归一化为官方行
|
||||
* @param {Array<Object>} records
|
||||
* @returns {{rows: Array, warnings: string[]}}
|
||||
*/
|
||||
function normalizeRecords(records) {
|
||||
const rows = [];
|
||||
const warnings = [];
|
||||
if (!Array.isArray(records)) return { rows, warnings: ['导入内容不是数组'] };
|
||||
|
||||
records.forEach((rec, idx) => {
|
||||
const keys = Object.keys(rec);
|
||||
const warehouseKey = keys.find((k) => String(k).trim() === '仓库');
|
||||
if (!warehouseKey) return;
|
||||
const warehouse = String(rec[warehouseKey] ?? '').trim();
|
||||
if (!warehouse) return;
|
||||
|
||||
const openingKey = keys.find((k) => String(k).trim() === '期初数量');
|
||||
const closingKey = keys.find((k) => String(k).trim() === '期末数量');
|
||||
if (!openingKey && !closingKey) {
|
||||
warnings.push(`第 ${idx + 2} 行缺少「期初数量 / 期末数量」列，已跳过`);
|
||||
return;
|
||||
}
|
||||
|
||||
// 12 个流水列先置 null，导出行里没出现的列保持 null（区别于显式为 0）
|
||||
const flows = {};
|
||||
for (const field of FLOW_FIELDS) flows[field] = null;
|
||||
for (const k of keys) {
|
||||
const label = String(k).trim();
|
||||
const field = LABEL_TO_FIELD.get(label);
|
||||
if (!field) continue;
|
||||
flows[field] = num(rec[k]);
|
||||
}
|
||||
|
||||
rows.push({
|
||||
warehouse,
|
||||
wmsCoId: WAREHOUSE_TO_ID.get(warehouse) ?? null,
|
||||
openingQty: openingKey ? num(rec[openingKey]) : null,
|
||||
closingQty: closingKey ? num(rec[closingKey]) : null,
|
||||
flows,
|
||||
});
|
||||
});
|
||||
|
||||
if (!rows.length) warnings.push('未解析到任何仓库行，请确认包含「仓库」列');
|
||||
return { rows, warnings };
|
||||
}
|
||||
|
||||
/**
|
||||
* 解析 xlsx 缓冲区（自动定位含「仓库」表头的工作表与表头行）
|
||||
* @param {Buffer} buffer
|
||||
*/
|
||||
function parseWorkbook(buffer) {
|
||||
const wb = XLSX.read(buffer, { type: 'buffer', cellDates: true });
|
||||
const warnings = [];
|
||||
for (const sheetName of wb.SheetNames) {
|
||||
const ws = wb.Sheets[sheetName];
|
||||
const grid = XLSX.utils.sheet_to_json(ws, { header: 1, defval: '', blankrows: false });
|
||||
const headerIdx = grid.findIndex((r) => r.some((c) => String(c).trim() === '仓库'));
|
||||
if (headerIdx < 0) continue;
|
||||
const header = grid[headerIdx].map((c) => String(c).trim());
|
||||
const body = grid.slice(headerIdx + 1)
|
||||
.filter((r) => r.some((c) => String(c).trim() !== ''))
|
||||
.map((r) => Object.fromEntries(header.map((h, i) => [h, r[i]])));
|
||||
const { rows, warnings: w } = normalizeRecords(body);
|
||||
if (rows.length) return { sheetName, rows, warnings: warnings.concat(w) };
|
||||
warnings.push(...w);
|
||||
}
|
||||
return { sheetName: null, rows: [], warnings: warnings.length ? warnings : ['未找到含「仓库」列的工作表'] };
|
||||
}
|
||||
|
||||
/** 恒等式校验：期初 + Σ流水 = 期末 */
|
||||
function checkBalance(rows, tolerance = 1) {
|
||||
return rows
|
||||
.map((r) => {
|
||||
const flowSum = FLOW_FIELDS.reduce((acc, f) => acc + (Number(r.flows?.[f]) || 0), 0);
|
||||
const opening = Number(r.openingQty) || 0;
|
||||
const closing = Number(r.closingQty) || 0;
|
||||
const diff = opening + flowSum - closing;
|
||||
return { warehouse: r.warehouse, opening, flowSum, closing, diff: Number(diff.toFixed(2)) };
|
||||
})
|
||||
.filter((r) => Math.abs(r.diff) > tolerance);
|
||||
}
|
||||
|
||||
/**
|
||||
* 导入某业务日的官方进销存（先清后写）
|
||||
* @returns {Promise<{bizDate:string, imported:number, warnings:string[], mismatches:Array, unknownWarehouses:string[], missingWarehouses:string[]}>}
|
||||
*/
|
||||
async function importOfficial(bizDate, rows, { source = 'jst-export' } = {}) {
|
||||
await officialDb.deleteOfficial(bizDate);
|
||||
const imported = await officialDb.upsertOfficial(bizDate, rows, source);
|
||||
const mismatches = checkBalance(rows);
|
||||
const unknownWarehouses = rows.filter((r) => r.wmsCoId == null).map((r) => r.warehouse);
|
||||
const importedNames = new Set(rows.map((r) => r.warehouse));
|
||||
const missingWarehouses = DAILY_INVENTORY_BASELINE
|
||||
.filter((b) => !importedNames.has(b.warehouse))
|
||||
.map((b) => b.warehouse);
|
||||
return { bizDate, imported, warnings: [], mismatches, unknownWarehouses, missingWarehouses };
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
FLOW_FIELDS,
|
||||
LABEL_TO_FIELD,
|
||||
normalizeRecords,
|
||||
parseWorkbook,
|
||||
checkBalance,
|
||||
importOfficial,
|
||||
};
|
||||
@ -1,91 +0,0 @@
|
||||
'use strict';
|
||||
|
||||
/**
|
||||
* 每日进销存 —— 期初快照缺失时的兜底推导
|
||||
*
|
||||
* 正常情况下「期初 = 上一业务日快照」（每日 01:30 自动落库）。
|
||||
* 若快照缺失（服务停机、新纳入仓库等），用「实时库存扣流水回推」推导
|
||||
* 「上一业务日期末结存」并补写快照：
|
||||
*
|
||||
* closing(D-1) = 当前实时库存 − 自 D 01:00 以来的净流入
|
||||
* 净流入 = 采购进仓 + 销售退货 − 销售出仓 − 采购退货（带符号流水求和，见 dailyInventoryFlows）
|
||||
*
|
||||
* 口径校准（2026-09-27，对照聚水潭进销存导出 09-23 期初基准）：
|
||||
* 崔桥工厂仓 基准 92388 / 回推 ≈89650；横林二仓 基准 63780 / 回推 ≈64029；
|
||||
* 山东青岗集 基准 88377 / 回推 ≈88210；河南洛宁 基准 83305 / 回推 ≈82473。
|
||||
* 偏差 0.3%~2.7%，来源为业务库缺失的 8 类单据（调拨/盘点/加工/其它出入库）。
|
||||
*
|
||||
* 注意：不要用 rpt.pm_stockMonitor 聚合 jsStock 充当全仓结存 ——
|
||||
* 该表只覆盖纳入监控范围的 SKU 子集（横林二仓实测 1197 vs 全仓 63780），
|
||||
* 系统性偏低，已在校准后弃用。
|
||||
*/
|
||||
|
||||
const { fetchFlows } = require('./dailyInventoryFlows');
|
||||
|
||||
/**
|
||||
* 推导 openingDate 的期末快照并补写。
|
||||
* @param {Object} opts
|
||||
* @param {Object} opts.cloudDb 业务库（mssql）
|
||||
* @param {Object} opts.snapshotDb 本地快照表访问模块
|
||||
* @param {Array} opts.baseline 仓库基线（warehouse/dbWarehouse/wmsCoId）
|
||||
* @param {string} opts.openingDate 期初业务日（YYYY-MM-DD，即要补快照的日期）
|
||||
* @param {string} opts.latestBizDate 最新业务日（YYYY-MM-DD，流水起点 = 其当日 01:00）
|
||||
* @param {Date|null} opts.takenAt 实时库存数据时间
|
||||
* @returns {Promise<{count:number, derivedCount:number}>}
|
||||
*/
|
||||
async function deriveAndStoreOpeningSnapshot(opts) {
|
||||
const { cloudDb, snapshotDb, baseline, openingDate, latestBizDate, takenAt } = opts;
|
||||
if (!openingDate || !latestBizDate) return { count: 0, derivedCount: 0 };
|
||||
const whs = baseline.filter((b) => b.wmsCoId != null);
|
||||
const wmsCoIds = whs.map((b) => b.wmsCoId);
|
||||
const flowFrom = `${latestBizDate} 01:00:00`;
|
||||
|
||||
// 实时库存（与每日快照任务同口径：jst_inventoryInfo 按仓聚合）
|
||||
let realtimeMap = new Map();
|
||||
try {
|
||||
const rows = await cloudDb.query(
|
||||
`SELECT i.wms_co_id AS wmsCoId,
|
||||
ISNULL(SUM(CAST(i.qty AS DECIMAL(18, 2))), 0) AS qty,
|
||||
SUM(CASE WHEN ABS(ISNULL(i.qty, 0)) > 0.0001 THEN 1 ELSE 0 END) AS skuCount
|
||||
FROM rpt.jst_inventoryInfo i
|
||||
WHERE i.wms_co_id IN (${wmsCoIds.map((_, i) => `@w${i}`).join(',')})
|
||||
GROUP BY i.wms_co_id`,
|
||||
Object.fromEntries(wmsCoIds.map((id, i) => [`w${i}`, id])),
|
||||
{ requestTimeout: 120000 }
|
||||
);
|
||||
realtimeMap = new Map(rows.map((r) => [String(r.wmsCoId), r]));
|
||||
} catch (error) {
|
||||
console.error('[daily-inventory-opening] 实时库存聚合失败:', error.message);
|
||||
}
|
||||
|
||||
// 自期初时刻以来的带符号流水（流出为负）
|
||||
let flowMap = new Map();
|
||||
try {
|
||||
flowMap = await fetchFlows(cloudDb, wmsCoIds, flowFrom);
|
||||
} catch (error) {
|
||||
console.error('[daily-inventory-opening] 流水取数失败:', error.message);
|
||||
}
|
||||
|
||||
let derivedCount = 0;
|
||||
const payload = whs.map((b) => {
|
||||
const rt = realtimeMap.get(String(b.wmsCoId));
|
||||
const f = flowMap.get(String(b.wmsCoId)) || {};
|
||||
const netInflow = (f.purchaseIn || 0) + (f.salesReturn || 0) + (f.salesOut || 0) + (f.purchaseReturn || 0);
|
||||
const closingQty = Number(rt?.qty ?? 0) - netInflow;
|
||||
derivedCount += 1;
|
||||
return {
|
||||
wmsCoId: b.wmsCoId,
|
||||
warehouse: b.warehouse,
|
||||
dbWarehouse: b.dbWarehouse,
|
||||
closingQty: Number(closingQty.toFixed(2)),
|
||||
skuCount: Number(rt?.skuCount ?? 0),
|
||||
takenAt: takenAt ? new Date(takenAt) : null,
|
||||
};
|
||||
});
|
||||
|
||||
const count = await snapshotDb.upsertSnapshot(openingDate, payload);
|
||||
console.log(`[daily-inventory-opening] 已补写 ${openingDate} 快照 ${count}/${whs.length} 仓（实时库存扣流水回推）`);
|
||||
return { count, derivedCount };
|
||||
}
|
||||
|
||||
module.exports = { deriveAndStoreOpeningSnapshot };
|
||||
@ -1,307 +0,0 @@
|
||||
'use strict';
|
||||
|
||||
// 每日进销存 · 页面截图与上传
|
||||
//
|
||||
// 要点：
|
||||
// 1. 使用服务端签发的**短时效** JWT 作为专用身份访问页面（15 分钟过期），
|
||||
// 令牌只写入浏览器 localStorage，不会出现在截图地址、日志或接口响应里。
|
||||
// 2. 截图前必须等到数据真正加载完成：表格有数据行、没有 Spin 加载中、没有错误提示。
|
||||
// 3. 表格带内部滚动，直接截屏只能看到一屏；截图前注入 CSS 展开滚动容器，
|
||||
// 再整页截图，保证数据是完整的。
|
||||
// 4. 截图落在系统临时目录，上传成功后立即删除。
|
||||
|
||||
const fs = require('fs');
|
||||
const os = require('os');
|
||||
const path = require('path');
|
||||
const crypto = require('crypto');
|
||||
const jwt = require('jsonwebtoken');
|
||||
const bcrypt = require('bcryptjs');
|
||||
const database = require('../config/database');
|
||||
const { uploadFileToDefaultS3 } = require('./objectStorage');
|
||||
|
||||
const TIMEZONE = 'Asia/Shanghai';
|
||||
const PAGE_PATH = '/planning/operation/daily-inventory';
|
||||
// 生产主站（见《服务器部署规范》）：可用 DAILY_INVENTORY_SCREENSHOT_BASE_URL / PUBLIC_SITE_URL 覆盖
|
||||
const DEFAULT_BASE_URL = 'https://ck.yydd.ai';
|
||||
// 页面首次加载要扫订单明细，约 15~20 秒，等待上限给到 3 分钟
|
||||
const PAGE_READY_TIMEOUT_MS = 3 * 60 * 1000;
|
||||
/**
|
||||
* 截图专用服务账号
|
||||
*
|
||||
* 页面启动时会调用 /api/auth/verify，该接口要求令牌的 sub 必须是系统库 users 表中
|
||||
* 真实且 active 的用户；仅签名合法但用户不存在的令牌会被判定为未登录并跳转登录页，
|
||||
* 截图也就拿不到任何数据。因此这里不使用凭空捏造的身份，而是在系统库维护一个
|
||||
* 仅供服务端使用的专用账号，令牌以该账号的 id 作为 sub。
|
||||
*
|
||||
* 该账号只以服务端签发的短时效令牌方式使用：密码哈希是随机值且永不对外，
|
||||
* 任何人无法通过密码登录；删除该行即可彻底回收。
|
||||
*/
|
||||
const SERVICE_USERNAME = String(
|
||||
process.env.DAILY_INVENTORY_SCREENSHOT_USERNAME || 'daily_inventory_screenshot_bot'
|
||||
).trim().slice(0, 50) || 'daily_inventory_screenshot_bot';
|
||||
const SERVICE_NAME = '每日进销存截图服务';
|
||||
const SERVICE_EMAIL = `${SERVICE_USERNAME}@service.local`;
|
||||
|
||||
let cachedServiceUserId = null;
|
||||
|
||||
const EXPAND_CSS = `
|
||||
.ant-table-body, .ant-table-content, .ant-table-container { max-height: none !important; overflow: visible !important; }
|
||||
.daily-inventory-page { overflow: visible !important; }
|
||||
.ant-table-cell-fix-left, .ant-table-cell-fix-right { position: static !important; }
|
||||
`;
|
||||
|
||||
function normalizeText(value, maxLength = 500) {
|
||||
return String(value ?? '').trim().slice(0, maxLength);
|
||||
}
|
||||
|
||||
/** 北京时间日期/时间片段：YYYY-MM-DD、YYYYMMDD、HHmmss */
|
||||
function chinaTimeParts(date = new Date()) {
|
||||
const target = date instanceof Date ? date : new Date(date);
|
||||
const dateText = new Intl.DateTimeFormat('en-CA', {
|
||||
timeZone: TIMEZONE, year: 'numeric', month: '2-digit', day: '2-digit',
|
||||
}).format(target);
|
||||
const timeText = new Intl.DateTimeFormat('en-GB', {
|
||||
timeZone: TIMEZONE, hour: '2-digit', minute: '2-digit', second: '2-digit', hour12: false,
|
||||
}).format(target);
|
||||
return {
|
||||
bizDate: dateText,
|
||||
dateKey: dateText.replace(/\D/g, ''),
|
||||
timeKey: timeText.replace(/\D/g, ''),
|
||||
};
|
||||
}
|
||||
|
||||
function resolveBaseUrl() {
|
||||
const raw = normalizeText(
|
||||
process.env.DAILY_INVENTORY_SCREENSHOT_BASE_URL
|
||||
|| process.env.PUBLIC_SITE_URL
|
||||
|| DEFAULT_BASE_URL,
|
||||
500
|
||||
).replace(/\/+$/, '');
|
||||
return raw || DEFAULT_BASE_URL;
|
||||
}
|
||||
|
||||
function resolvePageUrl() {
|
||||
return `${resolveBaseUrl()}${PAGE_PATH}`;
|
||||
}
|
||||
|
||||
/** 清空服务账号 id 缓存（账号被重建或测试时刷新用） */
|
||||
function resetScreenshotServiceUserCache() {
|
||||
cachedServiceUserId = null;
|
||||
}
|
||||
|
||||
/** 生成一个无法用于登录的密码哈希（随机串无人知晓，仅满足字段非空约束） */
|
||||
function buildUnusablePasswordHash() {
|
||||
return bcrypt.hash(crypto.randomBytes(32).toString('hex'), 10);
|
||||
}
|
||||
|
||||
/**
|
||||
* 确保系统库存在截图专用服务账号，并返回其 id。
|
||||
* 只维护 auth_source='service' 的本服务账号，不触碰任何人工账号。
|
||||
*/
|
||||
async function ensureScreenshotServiceUser() {
|
||||
if (cachedServiceUserId) return cachedServiceUserId;
|
||||
|
||||
const rows = await database.local.query(
|
||||
'SELECT id, role, status FROM users WHERE username = ? LIMIT 1',
|
||||
[SERVICE_USERNAME]
|
||||
);
|
||||
let user = rows[0];
|
||||
|
||||
if (!user) {
|
||||
const created = await database.local.insert('users', {
|
||||
username: SERVICE_USERNAME,
|
||||
password_hash: await buildUnusablePasswordHash(),
|
||||
name: SERVICE_NAME,
|
||||
email: SERVICE_EMAIL,
|
||||
role: 'admin',
|
||||
status: 'active',
|
||||
auth_source: 'service',
|
||||
});
|
||||
user = { id: created.insertId, role: 'admin', status: 'active' };
|
||||
} else if (user.status !== 'active' || user.role !== 'admin') {
|
||||
await database.local.query(
|
||||
"UPDATE users SET role = 'admin', status = 'active', auth_source = 'service' WHERE id = ? AND auth_source = 'service'",
|
||||
[user.id]
|
||||
);
|
||||
}
|
||||
|
||||
cachedServiceUserId = Number(user.id);
|
||||
return cachedServiceUserId;
|
||||
}
|
||||
|
||||
/**
|
||||
* 签发截图专用短时效令牌。
|
||||
* sub 为系统库中的专用服务账号 id，令牌只写入浏览器 localStorage，
|
||||
* 不会出现在截图地址、日志或接口响应里，也不含任何密钥。
|
||||
*/
|
||||
async function signScreenshotToken() {
|
||||
const secret = process.env.CUBEJS_SECRET;
|
||||
if (!secret) throw new Error('缺少 CUBEJS_SECRET，无法签发截图身份令牌');
|
||||
const userId = await ensureScreenshotServiceUser();
|
||||
return jwt.sign(
|
||||
{
|
||||
sub: String(userId),
|
||||
username: SERVICE_USERNAME,
|
||||
name: SERVICE_NAME,
|
||||
role: 'admin',
|
||||
authSource: 'service',
|
||||
allowedPageKeys: [],
|
||||
},
|
||||
secret,
|
||||
{ expiresIn: '15m' }
|
||||
);
|
||||
}
|
||||
|
||||
/**
|
||||
* 截图文件名与对象键。
|
||||
* 目录与文件名里的日期都用**业务日期**，时间用执行时刻，便于按数据日期归档：
|
||||
* daily-inventory/2026-09-25/daily-inventory-20260925-010000.png
|
||||
*/
|
||||
function buildScreenshotNames({ bizDate, timeKey }) {
|
||||
const safeDate = normalizeText(bizDate, 10);
|
||||
const dateKey = safeDate.replace(/\D/g, '');
|
||||
const fileName = `daily-inventory-${dateKey}-${timeKey}.png`;
|
||||
return {
|
||||
fileName,
|
||||
objectKey: `daily-inventory/${safeDate}/${fileName}`,
|
||||
};
|
||||
}
|
||||
|
||||
/** 截图存放的临时文件（不落业务目录，上传后立即删除） */
|
||||
function buildTempFilePath({ bizDate, timeKey }) {
|
||||
const dir = fs.mkdtempSync(path.join(os.tmpdir(), 'daily-inventory-shot-'));
|
||||
const { fileName, objectKey } = buildScreenshotNames({ bizDate, timeKey });
|
||||
return { dir, filePath: path.join(dir, fileName), objectKey };
|
||||
}
|
||||
|
||||
async function launchBrowser() {
|
||||
let playwright;
|
||||
try {
|
||||
playwright = require('playwright');
|
||||
} catch (_error) {
|
||||
throw new Error('未安装 playwright，无法执行页面截图');
|
||||
}
|
||||
try {
|
||||
return await playwright.chromium.launch({
|
||||
args: ['--no-sandbox', '--disable-dev-shm-usage', '--disable-gpu'],
|
||||
});
|
||||
} catch (error) {
|
||||
const detail = normalizeText(error?.message, 300);
|
||||
throw new Error(`浏览器启动失败（服务器需先执行 npx playwright install chromium）：${detail}`);
|
||||
}
|
||||
}
|
||||
|
||||
/** 等到数据真正渲染完成：有数据行、无加载中、无错误提示 */
|
||||
async function waitForPageReady(page) {
|
||||
await page.waitForSelector('.daily-inventory-table .ant-table-tbody tr', {
|
||||
timeout: PAGE_READY_TIMEOUT_MS,
|
||||
state: 'attached',
|
||||
});
|
||||
|
||||
await page.waitForFunction(
|
||||
() => {
|
||||
const spinning = document.querySelector('.daily-inventory-page .ant-spin-spinning');
|
||||
const skeleton = document.querySelector('.ant-skeleton');
|
||||
const rows = document.querySelectorAll('.daily-inventory-table .ant-table-tbody tr');
|
||||
return !spinning && !skeleton && rows.length > 0;
|
||||
},
|
||||
{ timeout: PAGE_READY_TIMEOUT_MS, polling: 500 }
|
||||
);
|
||||
|
||||
const errorText = await page.evaluate(() => {
|
||||
const node = document.querySelector('.daily-inventory-page .ant-alert-error');
|
||||
return node ? node.textContent || '' : '';
|
||||
});
|
||||
if (errorText) {
|
||||
throw new Error(`页面返回错误提示，放弃截图：${normalizeText(errorText, 200)}`);
|
||||
}
|
||||
|
||||
const rowCount = await page.evaluate(
|
||||
() => document.querySelectorAll('.daily-inventory-table .ant-table-tbody tr').length
|
||||
);
|
||||
if (!rowCount) throw new Error('页面未渲染出任何数据行，放弃截图');
|
||||
return rowCount;
|
||||
}
|
||||
|
||||
/**
|
||||
* 执行一次截图并上传到默认对象存储桶
|
||||
* @returns {Promise<{url:string, key:string, bizDate:string, size:number, rowCount:number, takenAt:string}>}
|
||||
*/
|
||||
async function captureAndUploadDailyInventory(options = {}) {
|
||||
const now = options.now ? new Date(options.now) : new Date();
|
||||
const { timeKey } = chinaTimeParts(now);
|
||||
// 业务日期由调用方（定时任务）给出；未指定时按北京时间当天兜底
|
||||
const bizDate = normalizeText(options.bizDate, 10) || chinaTimeParts(now).bizDate;
|
||||
const token = await signScreenshotToken();
|
||||
const pageUrl = resolvePageUrl();
|
||||
|
||||
const browser = await launchBrowser();
|
||||
const { dir, filePath, objectKey } = buildTempFilePath({ bizDate, timeKey });
|
||||
let rowCount = 0;
|
||||
|
||||
try {
|
||||
const context = await browser.newContext({
|
||||
viewport: { width: 1680, height: 1050 },
|
||||
deviceScaleFactor: 1,
|
||||
timezoneId: TIMEZONE,
|
||||
locale: 'zh-CN',
|
||||
});
|
||||
// 令牌只注入浏览器 localStorage，URL 与日志里都不出现
|
||||
await context.addInitScript((value) => {
|
||||
try {
|
||||
window.localStorage.setItem('token', value);
|
||||
} catch (_error) {
|
||||
// 忽略：首个 document 可能还不允许访问 localStorage
|
||||
}
|
||||
}, token);
|
||||
|
||||
const page = await context.newPage();
|
||||
page.on('pageerror', () => {});
|
||||
await page.goto(pageUrl, { waitUntil: 'domcontentloaded', timeout: PAGE_READY_TIMEOUT_MS });
|
||||
rowCount = await waitForPageReady(page);
|
||||
|
||||
// 展开内部滚动容器，保证整页截图包含完整数据区
|
||||
await page.addStyleTag({ content: EXPAND_CSS });
|
||||
await page.waitForTimeout(500);
|
||||
await page.screenshot({ path: filePath, fullPage: true });
|
||||
|
||||
const stats = await fs.promises.stat(filePath);
|
||||
if (!stats.size) throw new Error('截图文件为空');
|
||||
|
||||
const uploaded = await uploadFileToDefaultS3(filePath, {
|
||||
key: objectKey,
|
||||
mimeType: 'image/png',
|
||||
folder: 'daily-inventory',
|
||||
extension: 'png',
|
||||
});
|
||||
|
||||
return {
|
||||
url: uploaded.url,
|
||||
key: uploaded.key,
|
||||
bizDate,
|
||||
size: stats.size,
|
||||
rowCount,
|
||||
takenAt: now.toISOString(),
|
||||
};
|
||||
} finally {
|
||||
await browser.close().catch(() => {});
|
||||
fs.rm(dir, { recursive: true, force: true }, () => {});
|
||||
}
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
DEFAULT_BASE_URL,
|
||||
PAGE_PATH,
|
||||
PAGE_READY_TIMEOUT_MS,
|
||||
SERVICE_NAME,
|
||||
SERVICE_USERNAME,
|
||||
TIMEZONE,
|
||||
buildScreenshotNames,
|
||||
captureAndUploadDailyInventory,
|
||||
chinaTimeParts,
|
||||
ensureScreenshotServiceUser,
|
||||
resetScreenshotServiceUserCache,
|
||||
resolveBaseUrl,
|
||||
resolvePageUrl,
|
||||
signScreenshotToken,
|
||||
};
|
||||
@ -51,18 +51,15 @@
|
||||
// 该表查不到 → 仓位为空，前端显示「未维护」。**不做任何回退**。
|
||||
// · 列表展开（/detail）、单品明细、导出配件明细共用 loadComponentLocations()，
|
||||
// 只打一条查询，按编码缓存 10 分钟。
|
||||
// ⚠️ 关联列（09-19 修正，PR #22）：仓名用 `jst_warehouseInfo.wms_co_id = p.wms_co_id`
|
||||
// —— 09-19 实测该表 30,236 行 `wms_co_id` **0 NULL、14 个仓取值**。
|
||||
// ~~旧结论「该表 wms_co_id 全表 NULL，必须用 jst_warehouseInfo.Id = p.wh_id」~~
|
||||
// 只对 09-17 的表状态成立；误用 `w.Id = p.wh_id`（wh_id 仅 6 个取值、90% 为 1）
|
||||
// 会让 727 个配件的仓位仓名被统一显示成「常州简尚家居有限公司」。
|
||||
// 🔥 该表 **小时级增量刷新**，且 2026-09-18 被上游整表重建 ——
|
||||
// 09-17 的「全表 85,152 行、仅 3 个箱、`bin` / `bin_group` 全表为空、与 MKH 配件
|
||||
// **零交集**」这组结论**已全部失效**，别再照抄。
|
||||
// 09-19 实测：目标仓 794 个 SKU 命中 **727** 个（真货位如 ZT-8 / BCP01-01-1）；
|
||||
// 2026-09-30 实测：本配件仓（15718196）箱表有库存（bin 非空）的 SKU **734** 个。
|
||||
// → 配件货位 / 箱库存数据是真实存在并持续刷新的；
|
||||
// 该结论同时修正 ⑪ 的配件库存来源（箱表可作兜底，见下）。
|
||||
// ⚠️ 关联列别踩（2026-09-17 实测）：仓名必须用 `jst_warehouseInfo.Id = p.wh_id`；
|
||||
// 该表 `wms_co_id` **全表 NULL**，用 `w.wms_co_id = p.wms_co_id` 关联 85,152 行全部取不到仓名。
|
||||
// ⚠️ 2026-09-17 全量复核（别再重复排查）：该表全表 85,152 行，但只有 **3 个箱**
|
||||
// （914138566000001000 / …1003 / …4000）、2 个仓库（wh_id=1 常州简尚家居 85,145 行、
|
||||
// wh_id=4 简尚-新苏北仓 7 行）；`bin` / `bin_group` **全表为空**。
|
||||
// 且表内容与 MKH 配件**零交集**：正式 BOM 的 715 个配件编码在该表一个都查不到
|
||||
// （精确 + `code-%` 前缀都是 0；箱表里是 DNZ0135xx/0199xx/0203xx 老型号半成品）。
|
||||
// → MKH 配件仓位列当前**必然全部显示「未维护」**，这是数据源现状，不是代码问题；
|
||||
// 需业务在聚水潭给配件做装箱/维护货位后才会自动出现（代码不用再动）。
|
||||
//
|
||||
// ⑥ 配件库存 —— 业务库 rpt.jst_inventoryInfo 按 sku_id 汇总（**商品**库存，不是配件仓位）。
|
||||
//
|
||||
@ -70,11 +67,8 @@
|
||||
// 规则：近 15 天日销 > 0 且 现有库存 < 3 天日销 → 预警补货
|
||||
// · 近15天日销 rpt.pm_stockMonitor.fifteenAvgSale
|
||||
// （warehouse = '简尚-崔桥工厂品牌仓'，按 date 取最新一条快照）
|
||||
// · 现有库存 rpt.jst_inventoryInfo（wms_co_id **仓白名单**）实时库存；
|
||||
// 🔥 2026-10-17 修正为**多仓求和**（原来是单仓 15870495）：商品档案 other_3 只记
|
||||
// 「归属仓」，实物会整批搬到同体系其它发货仓 —— 只查归属仓会把有货的算成 0。
|
||||
// 实测新仓「简尚-横林二仓品牌仓」(16132681，10-13 建仓) 58 个 MKH 成品 / 525 件
|
||||
// 全在它名下、归属仓为 0 → 5 个误报缺货 + 2 个误报预警。白名单见 BRAND_WMS_CO_IDS。
|
||||
// · 现有库存 rpt.jst_inventoryInfo（wms_co_id = 15870495 品牌仓）实时库存；
|
||||
// 该仓对 MKH 成品只覆盖约 256 / 4408 条（2026-09-16 快照；成品总数口径见 ①），
|
||||
// 缺失时回退监控快照 jsStock
|
||||
// · 结余库存 = max(0, 现有库存 − 待发货订单)
|
||||
// ⚠️ 2026-09-18 起：已下单未发货的部分已被占用，**所有口径一律先扣待发订单**
|
||||
@ -218,28 +212,6 @@
|
||||
// 若日后业务反馈「库存大面积停在某个时间点」，**先查 inventoryInfo 的
|
||||
// MAX(updateTime)**，再看箱表的，两者一对即可判断是上游停了还是本页取数问题。
|
||||
//
|
||||
// ── ⑦-e 成品库存多仓合并（2026-10-17 新增）────────────────────────
|
||||
// 业务原话：「MKHDNZ0409260600788 库存在横林二仓品牌仓，**重新加了一个品牌仓库存**，
|
||||
// 需要同步这个仓库库存」。
|
||||
// 🔥 根因：**商品档案的 `other_3` 记录的是「归属仓」，不是「实物所在仓」**。
|
||||
// 归属仓仍是「简尚-崔桥工厂品牌仓」(15870495)，但实物被整批搬到 10-13 新建的
|
||||
// 「简尚-横林二仓品牌仓」(16132681) —— 归属仓库存为 0，新仓有货。
|
||||
// 而 ⑦-d 的取数只看 `wms_co_id = 15870495` 单仓 → 该批商品库存全被算成 0。
|
||||
// 实测：新仓 58 个 SKU 全是 MKH 成品（other_3 全为崔桥品牌仓），合计 525 件；
|
||||
// 线上 49 个 SKU 库存值错误，其中 **5 个误报「缺货」、2 个误报「预警」**。
|
||||
// 规则：`jst_inventoryInfo` / `jst_packInventoryInfo` 都按 **仓白名单 `IN (...)`**
|
||||
// 取数，并 **按 SKU 多仓求和**（同一批货可能同时分散在多仓）。
|
||||
// · 白名单常量：BRAND_WMS_CO_IDS（主仓 + 横林二仓品牌仓）
|
||||
// · ⚠️ 原来的「按 updateTime DESC 取首条」在单仓时是去重，多仓时会**只留一个仓**，
|
||||
// 必须换成 SUM + GROUP BY（本次改动同时修掉这个隐患）。
|
||||
// · ⚠️ 「求和」而非「取最大」：两仓是独立仓位，同一 SKU 同批货不会重复记账
|
||||
// （实测该 SKU 两仓 bin 分别为 `PP01-15-22` 与空，无同箱重复）。
|
||||
// 影响面（2026-10-17 实测）：58 个 SKU 受影响，其中 49 个库存值变化；
|
||||
// 预警 30 → 25、缺货 21 → 16（消除 5 个误报缺货、2 个误报预警）。
|
||||
// ⚠️ 新增同类「成品发货仓-真实库存」时，往 BRAND_WMS_CO_IDS 追加 wms_co_id 即可。
|
||||
// ⚠️ 配件库存**不适用本口径**（配件仍只算 15718196）——新仓一个配件都没有，
|
||||
// 横林三仓/沭阳仓虽有 MKH 配件但归属别的项目，并入会让「配件不足」漏报。
|
||||
//
|
||||
// ── ⑧ 在途加工单（2026-09-17 业务确认口径）────────────────────────
|
||||
// 规则：**只要该 MKH 商品存在未完成的加工单，就不再列入补货预警**
|
||||
// （工厂已经在做了，不重复提示补货），改标为「已排产」。
|
||||
@ -331,22 +303,13 @@
|
||||
// ⚠️ **必须扣未完成加工单的占用**（业务明确要求）：加工单在途的成品已经把配件
|
||||
// 预定/领走了，不扣就会高估可组装能力。加工单占用按配件维度归集：
|
||||
// 占用[配件] = Σ over 未完成加工单 (该成品在途台数 × 该成品对该配件的单台用量)
|
||||
// · 配件现有库存 **两级来源**（2026-09-30 修正，与配件监控页 `buildRealtimeStockSql` 同口径）：
|
||||
// ① rpt.jst_inventoryInfo，仓 = 简尚-崔桥工厂半成品包装项目仓（wms_co_id = 15718196）
|
||||
// —— MKH BOM 的 784 个配件归这个仓，产出成品入品牌仓。
|
||||
// 实测：该仓 822 行 / 741 行有正库存；本页涉及的配件**全部只在该仓有值**，
|
||||
// 跨仓正库存为 0，所以不跨仓汇总。
|
||||
// ② 同仓 rpt.jst_packInventoryInfo 的 **bin 非空** 行合计 —— **仅当 ① 为 0 / 缺行时启用**。
|
||||
// 🔥 **推翻旧结论**（旧版此处写「不能用 jst_packInventoryInfo 当配件库存 ——
|
||||
// 与 MKH 配件零交集」，那是 09-17 的表状态，09-18 上游重建后已失效，见 ⑤）。
|
||||
// 漏掉这一级会让「库存表滞后停在 0、箱表已有货」的配件被误判不足 ——
|
||||
// 2026-09-30 案例 MKHDNZ0409260600849 的配件 DNZ040947N1440V01：
|
||||
// inventoryInfo 停在 09-28 值 0，箱表当日 10:30 已记 bin=ZT-30 qty=200；
|
||||
// 配件监控页显示 200（判「正常」），MKH-BOM 却因 0 判「配件不足」。
|
||||
// 当日 30 行配件不足预警里 **7 行**属此类误判（可组装数 0 → 30~46）。
|
||||
// ⚠️ 必须过滤 `bin` 为空的行 —— 那是装箱记录不是库存（见 ⑤）；
|
||||
// 且**只补 0、不覆盖正库存**（箱表可能只记部分装箱量，覆盖会压低有效库存）。
|
||||
// · 配件现有库存 rpt.jst_inventoryInfo，仓 = 简尚-崔桥工厂半成品包装项目仓
|
||||
// （wms_co_id = 15718196）—— MKH BOM 的 784 个配件归这个仓，产出成品入品牌仓。
|
||||
// 实测：该仓 822 行 / 741 行有正库存；本页涉及的配件**全部只在该仓有值**，
|
||||
// 跨仓正库存为 0，所以不跨仓汇总。
|
||||
// · 单台用量 rm_qty（jst_skuBomItem）实测取值为 1 / 2 / 4，必须参与计算，不能当 1。
|
||||
// ⚠️ 不能用 `jst_packInventoryInfo` 当配件库存 —— 它是「箱及仓位库存」，
|
||||
// 与 MKH 配件零交集（见 ⑤），仓位口径专用。
|
||||
// · 采购在途（purchase_qty）**不计入**可用量（业务确认：只认现有库存）。
|
||||
// 锁定列（order_lock / pick_lock / lock_qty / virtual_qty）实测几乎全为 0
|
||||
// （本页 80 个配件里仅 2 条非零且值为 1），故直接用 qty。
|
||||
@ -435,17 +398,8 @@ const MKH_WHERE = `s.sku_id LIKE N'MKH%'
|
||||
)`;
|
||||
|
||||
// ── 补货预警参数（见文件头 ⑦）────────────────────────────────────
|
||||
// 成品库存仓白名单（rpt.jst_warehouseInfo 查得）。**多仓求和**：
|
||||
// 商品档案的 other_3 只记录「归属仓」（仍是崔桥工厂品牌仓），但实物会成批搬到
|
||||
// 同体系的其它发货仓，此时库存表里只有新仓有数、归属仓为 0 —— 只查归属仓会把
|
||||
// 有货的商品算成 0（实测 2026-10-17：新仓「简尚-横林二仓品牌仓」10-13 建仓，
|
||||
// 58 个 MKH 成品 / 525 件全部只在它名下，导致 5 个误报缺货 + 2 个误报预警）。
|
||||
// · 15870495 简尚-崔桥工厂品牌仓（归属主仓）
|
||||
// · 16132681 简尚-横林二仓品牌仓（2026-10-13 新增，成品发货仓-真实库存）
|
||||
// ⚠️ 新增同类「成品发货仓-真实库存」时把 wms_co_id 追加进来即可，别再写死单仓。
|
||||
const BRAND_WMS_CO_IDS = Object.freeze([15870495, 16132681]);
|
||||
// 兼容旧引用：主仓仍作为「仓库名」文案与监控快照的 warehouse 过滤值
|
||||
const BRAND_WMS_CO_ID = BRAND_WMS_CO_IDS[0];
|
||||
// 品牌仓 wms_co_id（rpt.jst_warehouseInfo 查得）
|
||||
const BRAND_WMS_CO_ID = 15870495;
|
||||
// 日销统计窗口（天）。见文件头 ⑦：业务最初要 30 天，但全库无 30 天日销数据，
|
||||
// 实测最长只有 fifteenAvgSale(15 天)，经业务确认改用 15 天。
|
||||
// ⚠️ SALE_WINDOW_DAYS 决定页面文案与口径展示，DAILY_SALE_COLUMN 决定实际取数列，
|
||||
@ -571,10 +525,8 @@ const normalizeCode = (value) => {
|
||||
// 筛选 / 排序 / 分页 / 统计全部在内存完成，SQL 侧只负责取数。
|
||||
const REPLENISH_PARAMS = Object.freeze({
|
||||
brandWarehouse: DESIGNATED_WAREHOUSE,
|
||||
brandWmsCoId: BRAND_WMS_CO_ID,
|
||||
});
|
||||
// 成品库存仓白名单的 SQL 片段（纯代码常量插值，不含外部输入）。
|
||||
// 用 `IN (...)` 一条查完多仓，再由应用层按 SKU **求和**分仓结果。
|
||||
const BRAND_WMS_CO_ID_LIST_SQL = BRAND_WMS_CO_IDS.join(',');
|
||||
// 商品集合是主数据、监控快照为日更，10 分钟缓存足够
|
||||
const MKH_CACHE_TTL_MS = 10 * 60 * 1000;
|
||||
let mkhProductCache = null;
|
||||
@ -1793,23 +1745,21 @@ async function loadReplenishIndex() {
|
||||
REPLENISH_PARAMS,
|
||||
{ requestTimeout: 180000 }
|
||||
),
|
||||
// 实时库存（见文件头 ⑦-d）：仓白名单多仓，**按 SKU 求和**（同一批货可能分散在多仓）。
|
||||
// ⚠️ 不能再用「按 updateTime DESC 取首条」——那会只留一个仓的数，正好丢掉新仓。
|
||||
// 实时库存：同一 SKU 可能多行，按 updateTime DESC 取首条
|
||||
cloudDatabase.query(
|
||||
`SELECT i.sku_id AS skuId, SUM(i.qty) AS qty
|
||||
`SELECT i.sku_id AS skuId, i.qty AS qty
|
||||
FROM dbo.jst_inventoryInfo i
|
||||
WHERE i.wms_co_id IN (${BRAND_WMS_CO_ID_LIST_SQL}) AND i.sku_id LIKE N'MKH%'
|
||||
GROUP BY i.sku_id`,
|
||||
WHERE i.wms_co_id = @brandWmsCoId AND i.sku_id LIKE N'MKH%'
|
||||
ORDER BY i.sku_id ASC, i.updateTime DESC`,
|
||||
REPLENISH_PARAMS,
|
||||
{ requestTimeout: 180000 }
|
||||
),
|
||||
// 箱/货位库存（见文件头 ⑦-d）：inventoryInfo 是日更，当日入库当天看不到，
|
||||
// 用小时级的箱表补 0。只取 bin 非空行 —— bin 为空的是装箱记录，不是库存。
|
||||
// 同样按仓白名单多仓求和（见 BRAND_WMS_CO_IDS 注释）。
|
||||
cloudDatabase.query(
|
||||
`SELECT p.sku_id AS skuId, SUM(p.qty) AS qty
|
||||
FROM dbo.jst_packInventoryInfo p
|
||||
WHERE p.wms_co_id IN (${BRAND_WMS_CO_ID_LIST_SQL}) AND p.sku_id LIKE N'MKH%'
|
||||
WHERE p.wms_co_id = @brandWmsCoId AND p.sku_id LIKE N'MKH%'
|
||||
AND NULLIF(LTRIM(RTRIM(p.bin)), N'') IS NOT NULL
|
||||
GROUP BY p.sku_id`,
|
||||
REPLENISH_PARAMS,
|
||||
@ -1895,10 +1845,6 @@ async function loadReplenishIndex() {
|
||||
/**
|
||||
* 配件现有库存批量查询（见文件头 ⑪）—— 只查配件归属仓「简尚-崔桥工厂半成品包装项目仓」。
|
||||
* · 按基础配件编码精确匹配，SUM(qty) 汇总
|
||||
* · **两级来源**（与配件监控页 buildRealtimeStockSql 同口径）：
|
||||
* ① jst_inventoryInfo 有正库存 → 以它为准
|
||||
* ② 为 0 / 缺行 → 用同仓 jst_packInventoryInfo 的 **bin 非空** 行合计兜底
|
||||
* （2026-09-30 修正：旧版只查 ①，导致「库存表滞后为 0、箱表已有货」的配件被误判不足）
|
||||
* · 结果按编码缓存（TTL 10 分钟），**查不到也缓存 0**（该仓无记录 = 无库存）
|
||||
* · 任一分片查询失败 → 立即返回 degraded=true，调用方**放弃判定**（宁可少标不误标），
|
||||
* 且失败的分片不写缓存，下次调用重试
|
||||
@ -1926,42 +1872,25 @@ async function loadComponentStock(codes = []) {
|
||||
params[`cs${index}`] = code;
|
||||
return `@cs${index}`;
|
||||
});
|
||||
const codeFilter = `IN (${placeholders.join(', ')})`;
|
||||
// 一条语句同时取两张表（UNION ALL + src 标记），避免多一次往返、也保证两个来源同一时点。
|
||||
// 库存表不筛 bin；箱表**必须**筛 bin 非空 —— bin 为空的是装箱记录，不是库存（见文件头 ⑤）。
|
||||
// eslint-disable-next-line no-await-in-loop -- 有意分片串行，避免一次打满连接池
|
||||
const rows = await cloudDatabase.query(
|
||||
`SELECT N'inv' AS src, i.sku_id AS code, SUM(i.qty) AS qty
|
||||
`SELECT i.sku_id AS code, SUM(i.qty) AS qty
|
||||
FROM dbo.jst_inventoryInfo i WITH (NOLOCK)
|
||||
WHERE i.wms_co_id = @componentStockWmsCoId AND i.sku_id ${codeFilter}
|
||||
GROUP BY i.sku_id
|
||||
UNION ALL
|
||||
SELECT N'pack' AS src, p.sku_id AS code, SUM(p.qty) AS qty
|
||||
FROM dbo.jst_packInventoryInfo p WITH (NOLOCK)
|
||||
WHERE p.wms_co_id = @componentStockWmsCoId AND p.sku_id ${codeFilter}
|
||||
AND NULLIF(LTRIM(RTRIM(p.bin)), N'') IS NOT NULL
|
||||
GROUP BY p.sku_id`,
|
||||
WHERE i.wms_co_id = @componentStockWmsCoId
|
||||
AND i.sku_id IN (${placeholders.join(', ')})
|
||||
GROUP BY i.sku_id`,
|
||||
params,
|
||||
{ requestTimeout: 120000 }
|
||||
);
|
||||
const inventoryQty = new Map();
|
||||
const packQty = new Map();
|
||||
const found = new Map();
|
||||
rows.forEach((row) => {
|
||||
const code = toText(row.code);
|
||||
if (!code) return;
|
||||
const qty = toNumber(row.qty) ?? 0;
|
||||
if (toText(row.src) === 'pack') packQty.set(code, qty);
|
||||
else inventoryQty.set(code, qty);
|
||||
if (code) found.set(code, toNumber(row.qty) ?? 0);
|
||||
});
|
||||
const expiresAt = Date.now() + COMPONENT_STOCK_CACHE_TTL_MS;
|
||||
const writable = epoch === cacheEpoch;
|
||||
chunk.forEach((code) => {
|
||||
// 只补 0、不覆盖正库存：库存表有正数就认它，否则看箱表（箱表可能只记部分装箱量）
|
||||
let qty = inventoryQty.get(code) ?? 0;
|
||||
if (qty <= 0) {
|
||||
const packStock = packQty.get(code) ?? 0;
|
||||
if (packStock > 0) qty = packStock;
|
||||
}
|
||||
const qty = found.get(code) ?? 0;
|
||||
// 本批结果仍要返回给调用方（stockMap），只是不再写缓存
|
||||
if (writable) componentStockCache.set(code, { qty, expiresAt });
|
||||
stockMap.set(code, qty);
|
||||
@ -2720,9 +2649,6 @@ module.exports = {
|
||||
COMPONENT_STOCK_WAREHOUSE,
|
||||
COMPONENT_STOCK_CHUNK_SIZE,
|
||||
COMPONENT_SHORTAGE_MAX_LIST,
|
||||
// ⑦-d 成品库存仓白名单（多仓求和口径）
|
||||
BRAND_WMS_CO_IDS,
|
||||
BRAND_WMS_CO_ID,
|
||||
parseFlag,
|
||||
resolveScope,
|
||||
filterRows,
|
||||
|
||||
@ -1,243 +0,0 @@
|
||||
'use strict';
|
||||
|
||||
/**
|
||||
* 拣选库位动销分析 —— 业务库取数
|
||||
*
|
||||
* 库存：rpt.jst_packInventoryInfo 按 wms_co_id + 仓位 + sku_id 汇总 qty（仓位为空的行不参与）
|
||||
* 范围：只统计真实拣选仓位（pack_type=Bin 且 bin_group 为空）；
|
||||
* 箱记录（pack_type=Pack）与存货位（bin_group=存货）不纳入
|
||||
* 销量（4 个来源分支，均按 send_date 窗口）：
|
||||
* 1) rpt.jst_Orders × jst_OrderItem 普通行（sku_type<>combine），排除 Delete/Cancelled
|
||||
* 2) rpt.jst_Orders 组合装行（sku_id 为 ZH-... 拼接串）→ JOIN jst_comboProductItem 展开为子件×数量
|
||||
* 3) rpt.jst_qmcust_orderlist（全民客户 B2B 分销）普通行，排除 Delete/Cancelled/Split/Question
|
||||
* （Split 是拆单父单，与拆出的子单重复，必须排除）
|
||||
* 4) rpt.jst_qmcust_orderlist 组合装行 → 同样按映射表展开
|
||||
* 粒度：仓位 × 商品编码（一个仓位有 N 个商品就输出 N 行），列表与导出共用
|
||||
*
|
||||
* 【日销与动销等级口径】按「商品日销」判定，不做仓位分摊：
|
||||
* 商品日销 = 该商品在窗口内的整档销量 ÷ 窗口天数
|
||||
* 同一件商品无论占用几个仓位，各行显示的销量 / 日销 / 动销等级完全一致 ——
|
||||
* 不会因为货放得散就被算成滞销。
|
||||
*
|
||||
* 附带输出「分摊销量」= 商品销量 ÷ 该商品占用的同类型仓位数，用于需要按行求和的场景：
|
||||
* 恒等式（已实测校验，差异 0）：全部行分摊销量之和 = 有库位记录的那些 SKU 的销量之和。
|
||||
* 注意它小于「全仓销量」：jst_packInventoryInfo 只覆盖部分 SKU 的仓位数据，
|
||||
* 没有仓位记录的 SKU 的销量不会体现在任何库位上。
|
||||
*/
|
||||
|
||||
const { PICKING_BIN_GRADE_RULES, BIN_TYPE_PICKING } = require('../config/pickingBinSalesAnalysis');
|
||||
|
||||
/** mssql 不支持数组参数，按位展开成 @p0,@p1... */
|
||||
function buildInClause(values, prefix) {
|
||||
const params = {};
|
||||
const clause = values
|
||||
.map((v, i) => {
|
||||
const key = `${prefix}${i}`;
|
||||
params[key] = v;
|
||||
return `@${key}`;
|
||||
})
|
||||
.join(',');
|
||||
return { clause, params };
|
||||
}
|
||||
|
||||
/**
|
||||
* 日销分档表达式：从高档往低档依次命中，最后一档「销售=0」由 salesQty <= 0 兜底。
|
||||
* 传入的 salesExpr 是窗口销量（商品整档销量），除以天数得到日销。
|
||||
*/
|
||||
function buildGradeCase(salesExpr = 'ISNULL(s.salesQty, 0)', daysParam = '@days') {
|
||||
const branches = PICKING_BIN_GRADE_RULES
|
||||
.filter((rule) => rule.lower > 0)
|
||||
.map((rule) => {
|
||||
const daily = `(${salesExpr} / ${daysParam})`;
|
||||
const lower = `${daily} >= ${rule.lower}`;
|
||||
const upper = rule.upper == null ? null : `${daily} < ${rule.upper}`;
|
||||
const cond = upper ? `${lower} AND ${upper}` : lower;
|
||||
return `WHEN ${cond} THEN '${rule.key}'`;
|
||||
});
|
||||
|
||||
return `
|
||||
CASE
|
||||
${branches.join('\n ')}
|
||||
WHEN ${salesExpr} > 0 THEN 'slow2'
|
||||
ELSE 'zero'
|
||||
END`;
|
||||
}
|
||||
|
||||
/**
|
||||
* 拉取「仓位 × 商品编码」粒度明细（列表与导出共用）。
|
||||
*
|
||||
* - stockQty：该商品在此仓位的实际库存
|
||||
* - salesQty：该商品在此仓库的窗口销量（整档，不按仓位分摊），动销等级的判定依据
|
||||
* - dailySales：salesQty / 窗口天数 = 商品日销
|
||||
* - allocatedSalesQty：salesQty ÷ 该商品占用的同类型仓位数，用于需要按行求和的场景
|
||||
* - skuCount：该仓位内存放的商品数（仓位粒度，同一仓位多行重复）
|
||||
*
|
||||
* @param {object} cloudDb 业务库实例
|
||||
* @param {string[]} wmsCoIds 仓库编码
|
||||
* @param {{shipFrom:string, shipTo:string, days:number}} options
|
||||
* @returns {Promise<Array<{wmsCoId:string, binName:string, binType:string, skuId:string,
|
||||
* stockQty:number, skuCount:number, salesQty:number, allocatedSalesQty:number,
|
||||
* dailySales:number, gradeKey:string}>>}
|
||||
*/
|
||||
async function fetchPickingBinSkuRows(cloudDb, wmsCoIds, options = {}) {
|
||||
if (!cloudDb || typeof cloudDb.query !== 'function') {
|
||||
throw new TypeError('fetchPickingBinSkuRows 的第一个参数必须是业务库实例');
|
||||
}
|
||||
const { shipFrom, shipTo, days } = options;
|
||||
if (!Array.isArray(wmsCoIds) || wmsCoIds.length === 0) return [];
|
||||
if (!shipFrom || !shipTo || !days) return [];
|
||||
|
||||
const binIn = buildInClause(wmsCoIds, 'w');
|
||||
const shipIn = buildInClause(wmsCoIds, 'v');
|
||||
|
||||
// 统计范围固定为真实拣选仓位：pack_type=Bin 且 bin_group 为空。
|
||||
// 仅过滤 bin_group 会把同样为空的 Pack 箱记录误标为拣选位。
|
||||
const sqlText = `
|
||||
WITH bin AS (
|
||||
SELECT p.wms_co_id AS wmsCoId,
|
||||
LTRIM(RTRIM(p.bin)) AS binName,
|
||||
N'${BIN_TYPE_PICKING}' AS binType,
|
||||
p.sku_id AS skuId,
|
||||
SUM(CAST(ISNULL(p.qty, 0) AS DECIMAL(18, 2))) AS binSkuQty
|
||||
FROM rpt.jst_packInventoryInfo p
|
||||
WHERE p.wms_co_id IN (${binIn.clause})
|
||||
AND ISNULL(p.bin, '') <> ''
|
||||
AND ISNULL(p.qty, 0) <> 0
|
||||
AND p.pack_type = N'Bin'
|
||||
AND ISNULL(p.bin_group, '') = ''
|
||||
GROUP BY p.wms_co_id,
|
||||
LTRIM(RTRIM(p.bin)),
|
||||
p.sku_id
|
||||
),
|
||||
binSpan AS (
|
||||
SELECT wmsCoId, skuId, binType, COUNT(DISTINCT binName) AS binCount
|
||||
FROM bin
|
||||
GROUP BY wmsCoId, skuId, binType
|
||||
),
|
||||
ship AS (
|
||||
-- 1) 线上店铺订单：普通商品行（sku_type<>combine，组合装行在下一分支展开）
|
||||
SELECT o.wms_co_id AS wmsCoId,
|
||||
oi.sku_id AS skuId,
|
||||
SUM(CAST(ISNULL(oi.qty, 0) AS DECIMAL(18, 2))) AS salesQty
|
||||
FROM rpt.jst_OrderItem oi
|
||||
JOIN rpt.jst_Orders o ON o.o_id = oi.o_id
|
||||
WHERE o.wms_co_id IN (${shipIn.clause})
|
||||
AND o.send_date >= @shipFrom
|
||||
AND o.send_date < @shipTo
|
||||
AND ISNULL(o.status, '') NOT IN ('Delete', 'Cancelled')
|
||||
AND ISNULL(oi.sku_type, 'normal') <> 'combine'
|
||||
GROUP BY o.wms_co_id, oi.sku_id
|
||||
UNION ALL
|
||||
-- 2) 线上店铺订单：组合装行（sku_id 为 ZH-子件A-N-子件B-M 拼接串）→ 按映射表展开为子件
|
||||
SELECT o.wms_co_id AS wmsCoId,
|
||||
ci.src_sku_id AS skuId,
|
||||
SUM(CAST(ISNULL(oi.qty, 0) * ISNULL(ci.qty, 0) AS DECIMAL(18, 2))) AS salesQty
|
||||
FROM rpt.jst_OrderItem oi
|
||||
JOIN rpt.jst_Orders o ON o.o_id = oi.o_id
|
||||
JOIN rpt.jst_comboProductItem ci ON ci.combine_sku_id = oi.sku_id
|
||||
WHERE o.wms_co_id IN (${shipIn.clause})
|
||||
AND o.send_date >= @shipFrom
|
||||
AND o.send_date < @shipTo
|
||||
AND ISNULL(o.status, '') NOT IN ('Delete', 'Cancelled')
|
||||
AND oi.sku_type = 'combine'
|
||||
GROUP BY o.wms_co_id, ci.src_sku_id
|
||||
UNION ALL
|
||||
-- 3) 全民客户（B2B 分销）订单：普通商品行（拆单父单 Split 与子单重复，需排除）
|
||||
SELECT o.wms_co_id AS wmsCoId,
|
||||
oi.sku_id AS skuId,
|
||||
SUM(CAST(ISNULL(oi.qty, 0) AS DECIMAL(18, 2))) AS salesQty
|
||||
FROM rpt.jst_qmcust_orderlist_item oi
|
||||
JOIN rpt.jst_qmcust_orderlist o ON o.o_id = oi.o_id
|
||||
WHERE o.wms_co_id IN (${shipIn.clause})
|
||||
AND o.send_date >= @shipFrom
|
||||
AND o.send_date < @shipTo
|
||||
AND ISNULL(o.status, '') NOT IN ('Delete', 'Cancelled', 'Split', 'Question')
|
||||
AND ISNULL(oi.sku_type, 'normal') <> 'combine'
|
||||
GROUP BY o.wms_co_id, oi.sku_id
|
||||
UNION ALL
|
||||
-- 4) 全民客户订单：组合装行展开为子件
|
||||
SELECT o.wms_co_id AS wmsCoId,
|
||||
ci.src_sku_id AS skuId,
|
||||
SUM(CAST(ISNULL(oi.qty, 0) * ISNULL(ci.qty, 0) AS DECIMAL(18, 2))) AS salesQty
|
||||
FROM rpt.jst_qmcust_orderlist_item oi
|
||||
JOIN rpt.jst_qmcust_orderlist o ON o.o_id = oi.o_id
|
||||
JOIN rpt.jst_comboProductItem ci ON ci.combine_sku_id = oi.sku_id
|
||||
WHERE o.wms_co_id IN (${shipIn.clause})
|
||||
AND o.send_date >= @shipFrom
|
||||
AND o.send_date < @shipTo
|
||||
AND ISNULL(o.status, '') NOT IN ('Delete', 'Cancelled', 'Split', 'Question')
|
||||
AND oi.sku_type = 'combine'
|
||||
GROUP BY o.wms_co_id, ci.src_sku_id
|
||||
),
|
||||
shipAgg AS (
|
||||
-- 同一个 仓库+商品 可能同时命中多个来源分支（线上普通/线上组合装/全民客户普通/全民客户组合装），
|
||||
-- 必须先按 仓库+商品 汇总成一行再 join，否则一个仓位行会被拆成多行、每行只带某分支的销量。
|
||||
SELECT wmsCoId,
|
||||
skuId,
|
||||
SUM(CAST(salesQty AS DECIMAL(18, 2))) AS salesQty
|
||||
FROM ship
|
||||
GROUP BY wmsCoId, skuId
|
||||
),
|
||||
binAgg AS (
|
||||
SELECT wmsCoId,
|
||||
binName,
|
||||
binType,
|
||||
COUNT(DISTINCT skuId) AS skuCount
|
||||
FROM bin
|
||||
GROUP BY wmsCoId, binName, binType
|
||||
)
|
||||
SELECT b.wmsCoId,
|
||||
b.binName,
|
||||
b.binType,
|
||||
b.skuId,
|
||||
CAST(SUM(CAST(b.binSkuQty AS DECIMAL(18, 2))) AS DECIMAL(18, 2)) AS stockQty,
|
||||
CAST(a.skuCount AS INT) AS skuCount,
|
||||
CAST(ISNULL(s.salesQty, 0) AS DECIMAL(18, 2)) AS salesQty,
|
||||
CAST(ISNULL(s.salesQty, 0) / NULLIF(sp.binCount, 0) AS DECIMAL(18, 4)) AS allocatedSalesQty,
|
||||
CAST(ISNULL(s.salesQty, 0) / @days AS DECIMAL(18, 4)) AS dailySales,
|
||||
${buildGradeCase('ISNULL(s.salesQty, 0)')} AS gradeKey
|
||||
FROM bin b
|
||||
JOIN binSpan sp
|
||||
ON sp.wmsCoId = b.wmsCoId AND sp.skuId = b.skuId AND sp.binType = b.binType
|
||||
JOIN binAgg a
|
||||
ON a.wmsCoId = b.wmsCoId AND a.binName = b.binName AND a.binType = b.binType
|
||||
LEFT JOIN shipAgg s
|
||||
ON s.wmsCoId = b.wmsCoId AND s.skuId = b.skuId
|
||||
GROUP BY b.wmsCoId, b.binName, b.binType, b.skuId, a.skuCount, s.salesQty, sp.binCount
|
||||
HAVING ABS(SUM(CAST(b.binSkuQty AS DECIMAL(18, 2)))) > 0.0001
|
||||
ORDER BY b.wmsCoId, b.binType, b.binName, b.skuId`;
|
||||
|
||||
// 该查询 union 了 4 个销量来源（含 qmcust 全渠道扫描），全仓窗口可能超过默认 60s；
|
||||
// mssql 12.x 请求级 timeout 不生效，必须走池级放宽的慢查询入口。
|
||||
const runQuery = typeof cloudDb.querySlow === 'function' ? cloudDb.querySlow : cloudDb.query;
|
||||
const rows = await runQuery(
|
||||
sqlText,
|
||||
{
|
||||
...binIn.params,
|
||||
...shipIn.params,
|
||||
shipFrom,
|
||||
shipTo,
|
||||
days,
|
||||
},
|
||||
{ requestTimeout: 120000 }
|
||||
);
|
||||
|
||||
return rows.map((r) => ({
|
||||
wmsCoId: String(r.wmsCoId),
|
||||
binName: r.binName || '',
|
||||
binType: r.binType || '',
|
||||
skuId: r.skuId == null ? '' : String(r.skuId).trim(),
|
||||
stockQty: Number(r.stockQty) || 0,
|
||||
skuCount: Number(r.skuCount) || 0,
|
||||
salesQty: Number(r.salesQty) || 0,
|
||||
allocatedSalesQty: Number(r.allocatedSalesQty) || 0,
|
||||
dailySales: Number(r.dailySales) || 0,
|
||||
gradeKey: r.gradeKey || 'zero',
|
||||
}));
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
buildGradeCase,
|
||||
buildInClause,
|
||||
fetchPickingBinSkuRows,
|
||||
};
|
||||
@ -14,20 +14,13 @@
|
||||
* · returnBinName = 用户口径的聚水潭仓位名，写进页面/导出的「数据来源」，便于核对；
|
||||
* · returnSlot = 副本里真正取数的那一列，必须与上面的仓位名一一对应。
|
||||
*
|
||||
* 仓位名 → 库存位 对照（2026-09-27 复测，条件 ISNULL(col,0) > 0）：
|
||||
* 箱及仓位库存 · 简尚-崔桥工厂仓 · 崔桥工厂客退临时上架仓 customize_qty_1 349 编码 / 507 件
|
||||
* 箱及仓位库存 · 简尚-新苏北仓 · 新苏北客退上架仓 customize_qty_1 75 编码 / 362 件
|
||||
* 箱及仓位库存 · 简尚-睢宁仓 · 睢宁客退上架仓 customize_qty_1 98 编码 / 243 件
|
||||
* 箱及仓位库存 · 简尚-山东青岗集仓 · 青岗集客退上架仓 customize_qty_2 403 编码 / 912 件
|
||||
* 仓位名 → 库存位 对照（2026-09-25 复测，条件 ISNULL(col,0) > 0）：
|
||||
* 箱及仓位库存 · 简尚-崔桥工厂仓 · 崔桥工厂客退临时上架仓 customize_qty_1 2 编码 / 2 件 ⚠
|
||||
* 箱及仓位库存 · 简尚-新苏北仓 · 新苏北客退上架仓 customize_qty_1 75 编码 / 362 件
|
||||
* 箱及仓位库存 · 简尚-睢宁仓 · 睢宁客退上架仓 customize_qty_1 98 编码 / 243 件
|
||||
* 箱及仓位库存 · 简尚-山东青岗集仓 · 青岗集客退上架仓 customize_qty_2 403 编码 / 912 件
|
||||
* 箱及仓位库存 · 简尚-河南洛宁仓 · 河南洛宁客退上架仓 三位全为 0（无数据）
|
||||
*
|
||||
* ── 2026-09-27 重要更新：崔桥工厂仓的客退库存已经同步进副本了 ──
|
||||
* 09-25 首次切换时该仓客退位只有 2 编码 / 2 件（当时判定「未同步进副本」），
|
||||
* 09-26 起 IT 侧补上了同步：09-26 当天写入 317 编码 / 460 件，09-27 又补 31 编码 / 46 件，
|
||||
* 09-27 10:11 实测 349 编码 / 507 件（= 副本 c1 合计，页面与副本完全对得上）。
|
||||
* ⚠ 所以下面「崔桥必然近乎空白 / 只能靠导入」的旧结论已经作废，不要再拿它当依据。
|
||||
* 现在这张看板能正常出数，**不需要**用导入功能兜底。
|
||||
*
|
||||
* ⚠ 崔桥工厂仓（15038426）是 2026-09-25 用户指定替换横林二仓的。复测结论：
|
||||
* 副本里该仓客退位只有 2 编码 / 2 件，但退货单量很大（ERP 售后单 3,115 条 +
|
||||
* 奇门退款单 1,812 条，warehouse='简尚-崔桥工厂仓销退仓'）——即「退货有，客退上架库存
|
||||
@ -65,8 +58,10 @@ const WAREHOUSE_LIST = [
|
||||
returnBinName: '崔桥工厂客退临时上架仓',
|
||||
// 客退临时上架仓占用的自定义库存位
|
||||
returnSlot: 'customize_qty_1',
|
||||
// 2026-09-27 复测：客退位已同步进副本 —— 349 编码 / 507 件（c1 合计），
|
||||
// 退货单口径：ERP 售后单 3,115 条 + 奇门退款单 1,812 条（warehouse='简尚-崔桥工厂仓销退仓'）。
|
||||
// ⚠ 2026-09-25 实测：该仓在副本 jst_inventoryInfo 里客退位只有 2 个编码 / 2 件
|
||||
//（qty 总库存 92,818 件；return_qty / c2 / c3 / sale_refund_qty 全为 0）。
|
||||
// 退货单是有的（ERP 售后单 3,115 条 + 奇门退款单 1,812 条），
|
||||
// 说明是「客退上架仓」这一仓位没同步进副本，不是业务上没有退货。
|
||||
hasReturnStock: true,
|
||||
},
|
||||
{
|
||||
|
||||
@ -64,10 +64,6 @@
|
||||
|
||||
const cloudDb = require('../config/cloudDatabase');
|
||||
const database = require('../config/database');
|
||||
const {
|
||||
loadSupplierExitDates,
|
||||
EMPTY_EXIT_DATES,
|
||||
} = require('./supplierExitDateProvider');
|
||||
const {
|
||||
WAREHOUSE_LIST,
|
||||
RETURN_SLOT_COLUMNS,
|
||||
@ -246,7 +242,6 @@ const buildKnownGaps = (warehouse = DEFAULT_WAREHOUSE) => {
|
||||
'单价 / 总金额：单价取商品资料 jst_sku 的成本价（cost_price），成本价缺失或为 0 时回退采购价（purchase_price）；总金额 = 单价 × 总库存（即「客退临时上架仓」的库存金额）。商品资料里两个价格都没有的编码（多为虚拟编码，如 HBZBF）单价与总金额显示「--」，且不计入顶部「库存总金额」，页面会单独提示这类编码的数量。',
|
||||
'单价预警：按商品单价单独分级，默认「单价 > 300 元 → 重点关注」「200 ~ 300 元 → 关注」「< 200 元 → 正常」，阈值可在页面上直接调。它与库龄预警是两个互补维度——库龄看「货压了多久」，单价看「每件压了多少钱」，两者叠加才能看出真正占资金的那批编码。',
|
||||
'退厂时限：单价 > 重点关注线（默认 300 元）的编码，要求入库后 7 天内完成库存退厂（时限可在页面调）。页面按「在库天数」对比时限，给出「已超期 N 天 / 剩余 N 天」，并在顶部单独提示这批编码的处置要求。「已退厂」的判定是「该编码已从当天库存中消失」（不再依赖出库表），一旦退厂完成，这条编码自然就不会再出现在报表里。',
|
||||
'最晚退厂时间（当前「待接入」）：业务上由工作平台对「不再合作」的供应商给出最晚退厂日期，看板按供应商名匹配后与「供应商是否合作」列并排展示。它不在报表副本里——数据属于工作平台库 WorkbenchDataShared（同实例另有 WorkbenchIdentity、DataPlatformControl），而 2026-09-28 取证时副本账号 cangku 访问该库被拒（The server principal "cangku" is not able to access the database "WorkbenchDataShared" under the current security context），系统设置里也没有它的连接配置，.env 的 JIAN_SUN_DB_* / WORK_ORDER_* 全为空；副本库内 5,496 个字段中没有任何「退厂」字段，最接近的 fys_supplier.NoCoopTime 是不可用的停更快照（崔桥仓 8 个不合作供应商里只有 1 个有值，且那 1 条自身还标着「合作」）。所以该列先以「待接入」占位，不影响其他列。要出数只需二选一：① 让 IT 给副本账号开通 WorkbenchDataShared 只读；② 让 IT 把工作平台「供应商不合作」表同步进 JSReportReplica。之后在 backend/src/services/supplierExitDateProvider.js 里填上查询语句即可自动出数，页面与导出都无需再改。',
|
||||
];
|
||||
if (!warehouse.hasReturnStock) {
|
||||
gaps.unshift(
|
||||
@ -372,16 +367,10 @@ const buildFullSql = (createdAtBasis = DEFAULT_CREATED_AT_BASIS, warehouse = DEF
|
||||
];
|
||||
if (useFirstInbound) selectColumns.push('f.first_inbound_time AS [firstInboundTime]');
|
||||
selectColumns.push("ISNULL(sk.supplier_name, N'') AS [supplier]");
|
||||
// 供应商是否合作：取自简尚供应商主数据 js_supplier.coopersgn（1=合作 / 2=不合作）
|
||||
selectColumns.push('sp.coopersgn AS [supplierCoopSign]');
|
||||
// 单价取自商品资料 jst_sku：成本价优先，缺失/为 0 时回退采购价（见 pickUnitPrice）
|
||||
selectColumns.push('sk.cost_price AS [costPrice]');
|
||||
selectColumns.push('sk.purchase_price AS [purchasePrice]');
|
||||
const joins = ['LEFT JOIN dbo.jst_sku sk ON sk.sku_id = s.product_code'];
|
||||
// ⚠ 关联键必须是 scmname（供应商简称），与 jst_sku.supplier_name 是同一套命名（2026-09-28 实测
|
||||
// 匹配 100/109）；tradebody（工商全称）只能匹配 1 条，别用。scmname 在 js_supplier 里唯一
|
||||
// （1,497 行 / 1,497 个不同值），所以 LEFT JOIN 不会放大行数。
|
||||
joins.push('LEFT JOIN dbo.js_supplier sp ON sp.scmname = sk.supplier_name');
|
||||
if (useFirstInbound) joins.push('LEFT JOIN first_in f ON f.product_code = s.product_code');
|
||||
|
||||
return `
|
||||
@ -403,13 +392,7 @@ const buildStockSyncedSql = (warehouse = DEFAULT_WAREHOUSE) => `
|
||||
FROM dbo.jst_inventoryInfo
|
||||
WHERE wms_co_id = ${warehouse.wmsCoId}`;
|
||||
|
||||
// 默认 5 分钟：副本侧 ETL 约 10 分钟一批增量（2026-09-27 实测），
|
||||
// 这里再压一层缓存只是防止多人反复翻页把副本打爆；想更快用 env 调，或前端点「刷新数据」强制回源。
|
||||
const DEFAULT_CACHE_TTL_MS = 5 * 60 * 1000;
|
||||
const resolveCacheTtlMs = () => {
|
||||
const raw = Number.parseInt(process.env.RETURN_STOCK_WARNING_CACHE_TTL_MS, 10);
|
||||
return Number.isFinite(raw) && raw >= 0 ? raw : DEFAULT_CACHE_TTL_MS;
|
||||
};
|
||||
const CACHE_TTL_MS = 10 * 60 * 1000;
|
||||
// 缓存键 = 仓库 + 创建时间口径（两者都会改变 SQL / 取到的行）
|
||||
const buildCacheKey = (warehouse, basis) => `${warehouse.key}|${basis}`;
|
||||
const rowCache = new Map();
|
||||
@ -425,7 +408,7 @@ async function loadReplicaRows({
|
||||
const basis = resolveCreatedAtBasis(createdAtBasis);
|
||||
const key = buildCacheKey(warehouse, basis);
|
||||
const cached = rowCache.get(key);
|
||||
if (!refresh && cached && cached.rows && Date.now() - cached.at < resolveCacheTtlMs()) {
|
||||
if (!refresh && cached && cached.rows && Date.now() - cached.at < CACHE_TTL_MS) {
|
||||
return cached.rows;
|
||||
}
|
||||
const running = inflightCache.get(key);
|
||||
@ -454,7 +437,7 @@ async function loadReplicaRows({
|
||||
/** 副本库存表最近一次同步时间（YYYY-MM-DD HH:mm:ss），页面「库存更新时间」用 */
|
||||
async function loadStockSyncedAt({ refresh = false, warehouse = DEFAULT_WAREHOUSE } = {}) {
|
||||
const state = stockSyncedAtState.get(warehouse.key);
|
||||
if (!refresh && state?.value && Date.now() - state.at < resolveCacheTtlMs()) {
|
||||
if (!refresh && state?.value && Date.now() - state.at < CACHE_TTL_MS) {
|
||||
return state.value;
|
||||
}
|
||||
try {
|
||||
@ -584,24 +567,6 @@ const resolveReturnLimitDays = (value) => {
|
||||
* 其余 → pending，returnRemainDays = 剩余天数（时限 − 在库天数）
|
||||
* 拿不到创建时间（算不出在库天数）时按 pending 处理，剩余天数留空，页面提示「待补创建时间」。
|
||||
*/
|
||||
// ---------------------------------------------------------------------------
|
||||
// 供应商是否合作（2026-09-28 新增）
|
||||
// 依据：简尚供应商主数据 dbo.js_supplier.coopersgn —— 1 = 合作中，2 = 不合作。
|
||||
// 语义已交叉验证：与 dbo.fys_supplier.IsCoop（'合作'/'不合作'）比对，
|
||||
// coopersgn=2 ↔ 不合作 823 条一致、coopersgn=1 ↔ 合作 270 条一致。
|
||||
// 两边冲突的 262 条以 js_supplier 为准 —— fys_supplier 是旧快照（DownloadTime 停在
|
||||
// 2025-11，样本多为 2023/2024），而 js_supplier 的 local_updated 已到 2026-09。
|
||||
// 匹配不上（供应商没进主数据、或该编码没有供应商）一律按「未知」展示，不要当「不合作」。
|
||||
// ---------------------------------------------------------------------------
|
||||
const SUPPLIER_COOP_LABELS = { cooperative: '合作', ended: '不合作', unknown: '未知' };
|
||||
const resolveSupplierCoop = (sign) => {
|
||||
if (sign === null || sign === undefined || sign === '') return 'unknown';
|
||||
const n = Number(sign);
|
||||
if (n === 1) return 'cooperative';
|
||||
if (n === 2) return 'ended';
|
||||
return 'unknown';
|
||||
};
|
||||
|
||||
const resolveReturnDeadline = ({ unitPriceLevel, stockDays, isOutbound, returnLimitDays }) => {
|
||||
if (unitPriceLevel !== 'high') return { status: 'none', remainDays: null };
|
||||
if (isOutbound) return { status: 'done', remainDays: null };
|
||||
@ -830,8 +795,6 @@ function composeRows({
|
||||
replicaRows, overrides, qtyBasis, createdAtBasis, today, scope, focusDays, alertDays, priceMap,
|
||||
priceFocusMin = DEFAULT_PRICE_FOCUS_MIN, priceHighMin = DEFAULT_PRICE_HIGH_MIN,
|
||||
returnLimitDays = DEFAULT_RETURN_LIMIT_DAYS, warehouse = DEFAULT_WAREHOUSE,
|
||||
// 供应商「最晚退厂时间」（工作平台数据，见 supplierExitDateProvider；未接入时是空 Map）
|
||||
exitDates = EMPTY_EXIT_DATES,
|
||||
}) {
|
||||
const hasImport = overrides.size > 0;
|
||||
const rows = [];
|
||||
@ -858,11 +821,6 @@ function composeRows({
|
||||
const deadline = resolveReturnDeadline({
|
||||
unitPriceLevel, stockDays, isOutbound, returnLimitDays,
|
||||
});
|
||||
// 供应商是否合作（js_supplier.coopersgn）
|
||||
const supplierCoop = resolveSupplierCoop(row.supplierCoopSign);
|
||||
// 最晚退厂时间（工作平台「供应商不合作」，按供应商名匹配；未接入时为空）
|
||||
const supplierName = String(row.supplier || '').trim();
|
||||
const latestExitDate = exitDates.bySupplier.get(supplierName) || '';
|
||||
|
||||
if (scope === 'imported' && !override) return;
|
||||
if (qty <= 0) return;
|
||||
@ -893,11 +851,6 @@ function composeRows({
|
||||
stockDays,
|
||||
warningLevel: resolveWarningLevel(stockDays, focusDays, alertDays),
|
||||
isOutbound,
|
||||
supplierCoop,
|
||||
supplierCoopLabel: SUPPLIER_COOP_LABELS[supplierCoop] || '',
|
||||
latestExitDate,
|
||||
latestExitDateLabel: latestExitDate,
|
||||
latestExitDateAvailable: exitDates.available,
|
||||
source: override ? 'jst' : 'replica',
|
||||
noInboundRecord: !createdAtRaw,
|
||||
});
|
||||
@ -917,9 +870,6 @@ function composeRows({
|
||||
const deadline = resolveReturnDeadline({
|
||||
unitPriceLevel, stockDays, isOutbound, returnLimitDays,
|
||||
});
|
||||
// 这条是「导入里有、副本里没有」补进来的编码，没走副本 join，拿不到 coopersgn → 标「未知」
|
||||
const supplierCoop = 'unknown';
|
||||
const supplierExitDate = exitDates.bySupplier.get(String(override.supplier || '').trim()) || '';
|
||||
rows.push({
|
||||
productCode: code,
|
||||
createdAt: formatDateTime(override.createdAt),
|
||||
@ -945,11 +895,6 @@ function composeRows({
|
||||
stockDays,
|
||||
warningLevel: resolveWarningLevel(stockDays, focusDays, alertDays),
|
||||
isOutbound,
|
||||
supplierCoop,
|
||||
supplierCoopLabel: SUPPLIER_COOP_LABELS[supplierCoop] || '',
|
||||
latestExitDate: supplierExitDate,
|
||||
latestExitDateLabel: supplierExitDate,
|
||||
latestExitDateAvailable: exitDates.available,
|
||||
source: 'jst',
|
||||
noInboundRecord: !override.createdAt,
|
||||
});
|
||||
@ -1112,11 +1057,10 @@ async function getReturnStockWarningList(options = {}) {
|
||||
const priceLevel = resolvePriceLevelFilter(options.priceLevel);
|
||||
const today = formatLocalDate();
|
||||
|
||||
const [replicaRows, overrides, latestImport, exitDates] = await Promise.all([
|
||||
const [replicaRows, overrides, latestImport] = await Promise.all([
|
||||
loadReplicaRows({ refresh: String(options.refresh) === 'true', createdAtBasis, warehouse }),
|
||||
loadImportOverrides(warehouse),
|
||||
loadLatestImportBatch(warehouse),
|
||||
loadSupplierExitDates(),
|
||||
]);
|
||||
|
||||
const priceMap = await loadPriceMapForOverrides(replicaRows, overrides);
|
||||
@ -1135,7 +1079,6 @@ async function getReturnStockWarningList(options = {}) {
|
||||
priceHighMin,
|
||||
returnLimitDays,
|
||||
warehouse,
|
||||
exitDates,
|
||||
});
|
||||
|
||||
const filtered = composed.rows.filter((row) => matchesKeyword(row, keyword) && matchesSupplier(row, supplier));
|
||||
@ -1186,12 +1129,6 @@ async function getReturnStockWarningList(options = {}) {
|
||||
summary,
|
||||
import: latestImport,
|
||||
hasImport: composed.hasImport,
|
||||
// 「最晚退厂时间」数据源状态（页面用它渲染「待接入」提示与列 Tooltip）
|
||||
exitDateMeta: {
|
||||
available: exitDates.available,
|
||||
sourceLabel: exitDates.sourceLabel,
|
||||
message: exitDates.message,
|
||||
},
|
||||
gaps: buildKnownGaps(warehouse),
|
||||
};
|
||||
}
|
||||
@ -1211,8 +1148,7 @@ const buildExportColumns = (warehouse = DEFAULT_WAREHOUSE) => [
|
||||
{ key: 'amount', title: '总金额' },
|
||||
{ key: 'unitPriceLevelLabel', title: '单价预警' },
|
||||
{ key: 'returnDeadlineLabel', title: '退厂时限' },
|
||||
{ key: 'supplierCoopLabel', title: '供应商是否合作' },
|
||||
{ key: 'latestExitDateLabel', title: '最晚退厂时间' },
|
||||
{ key: 'isOutboundLabel', title: '是否出库' },
|
||||
{ key: 'returnQty', title: '退货仓库存(return_qty)' },
|
||||
{ key: 'returnSlotQty', title: `客退临时上架库存(${warehouse.returnSlot})` },
|
||||
{ key: 'sourceLabel', title: '数据来源' },
|
||||
@ -1238,10 +1174,9 @@ async function getReturnStockWarningExportRows(options = {}) {
|
||||
const priceLevel = resolvePriceLevelFilter(options.priceLevel);
|
||||
const today = formatLocalDate();
|
||||
|
||||
const [replicaRows, overrides, exitDates] = await Promise.all([
|
||||
const [replicaRows, overrides] = await Promise.all([
|
||||
loadReplicaRows({ refresh: String(options.refresh) === 'true', createdAtBasis, warehouse }),
|
||||
loadImportOverrides(warehouse),
|
||||
loadSupplierExitDates(),
|
||||
]);
|
||||
|
||||
const priceMap = await loadPriceMapForOverrides(replicaRows, overrides);
|
||||
@ -1260,7 +1195,6 @@ async function getReturnStockWarningExportRows(options = {}) {
|
||||
priceHighMin,
|
||||
returnLimitDays,
|
||||
warehouse,
|
||||
exitDates,
|
||||
});
|
||||
|
||||
const filtered = composed.rows.filter((row) => matchesKeyword(row, keyword) && matchesSupplier(row, supplier));
|
||||
@ -1274,10 +1208,7 @@ async function getReturnStockWarningExportRows(options = {}) {
|
||||
warningLabel: WARNING_LABELS[row.warningLevel] || WARNING_LABELS.normal,
|
||||
unitPriceLevelLabel: PRICE_WARNING_LABELS[row.unitPriceLevel] || '',
|
||||
returnDeadlineLabel: formatReturnDeadlineLabel(row.returnDeadlineStatus, row.returnRemainDays),
|
||||
supplierCoopLabel: row.supplierCoopLabel || SUPPLIER_COOP_LABELS.unknown,
|
||||
// 工作平台未接入时导出显示「待接入」，避免空列被误读成「没有退厂时间」
|
||||
latestExitDateLabel: row.latestExitDateLabel
|
||||
|| (row.latestExitDateAvailable ? '—' : '待接入'),
|
||||
isOutboundLabel: row.isOutbound ? '是' : '否',
|
||||
sourceLabel: row.createdAtSourceLabel || '',
|
||||
createdAtRaw: undefined,
|
||||
}));
|
||||
|
||||
@ -1,248 +0,0 @@
|
||||
'use strict';
|
||||
|
||||
/**
|
||||
* 仓库库存动销分析 —— 业务库取数
|
||||
*
|
||||
* 一次查询覆盖全部仓库 × 全部动销等级：
|
||||
* 库存件数：rpt.jst_inventoryInfo 实时库存（按 wms_co_id + sku_id 汇总）
|
||||
* 销量： rpt.jst_OrderItem × rpt.jst_Orders，按 send_date，排除 Delete/Cancelled
|
||||
* （与「每日进销存」的发货口径一致）
|
||||
* 日销： 销量 / 统计窗口天数 → 分档得到动销等级
|
||||
*
|
||||
* 只统计「有库存或有销量」的 SKU：库存为 0 且窗口内无销量的 SKU 已下架，
|
||||
* 计入「销售=0」会虚增分母，故整体剔除。
|
||||
*/
|
||||
|
||||
const { SALES_GRADE_RULES } = require('../config/stockSalesAnalysis');
|
||||
|
||||
/** mssql 不支持数组参数，按位展开成 @p0,@p1... */
|
||||
function buildInClause(values, prefix) {
|
||||
const params = {};
|
||||
const clause = values
|
||||
.map((v, i) => {
|
||||
const key = `${prefix}${i}`;
|
||||
params[key] = v;
|
||||
return `@${key}`;
|
||||
})
|
||||
.join(',');
|
||||
return { clause, params };
|
||||
}
|
||||
|
||||
/**
|
||||
* 日销分档表达式：从高档往低档依次命中。
|
||||
* 最后一档「销售=0」由 `salesQty <= 0` 兜底（销量为 NULL 视同 0）。
|
||||
*/
|
||||
function buildGradeCase(salesExpr = 'ISNULL(b.salesQty, 0)', daysParam = '@days') {
|
||||
const branches = SALES_GRADE_RULES
|
||||
.filter((rule) => rule.lower > 0)
|
||||
.map((rule) => {
|
||||
const daily = `(${salesExpr} / ${daysParam})`;
|
||||
const lower = `${daily} >= ${rule.lower}`;
|
||||
const upper = rule.upper == null ? null : `${daily} < ${rule.upper}`;
|
||||
const cond = upper ? `${lower} AND ${upper}` : lower;
|
||||
return `WHEN ${cond} THEN '${rule.key}'`;
|
||||
});
|
||||
|
||||
return `
|
||||
CASE
|
||||
${branches.join('\n ')}
|
||||
WHEN ${salesExpr} > 0 THEN 'slow2'
|
||||
ELSE 'zero'
|
||||
END`;
|
||||
}
|
||||
|
||||
/**
|
||||
* 每个仓库 × 每个动销等级的 SKU 数、库存件数、销量。
|
||||
* @returns {Promise<Array<{wmsCoId:string, gradeKey:string, skuCount:number, stockQty:number, salesQty:number, dailySales:number}>>}
|
||||
*/
|
||||
async function fetchGradeRows(cloudDb, wmsCoIds, { shipFrom, shipTo, days }) {
|
||||
if (!cloudDb || typeof cloudDb.query !== 'function') {
|
||||
throw new TypeError('fetchGradeRows 的第一个参数必须是业务库实例');
|
||||
}
|
||||
if (!Array.isArray(wmsCoIds) || wmsCoIds.length === 0) return [];
|
||||
if (!shipFrom || !shipTo || !days) return [];
|
||||
|
||||
const invIn = buildInClause(wmsCoIds, 'w');
|
||||
const shipIn = buildInClause(wmsCoIds, 'v');
|
||||
const gradeCase = buildGradeCase();
|
||||
|
||||
const sqlText = `
|
||||
WITH inv AS (
|
||||
SELECT i.wms_co_id AS wmsCoId,
|
||||
i.sku_id AS skuId,
|
||||
SUM(CAST(ISNULL(i.qty, 0) AS DECIMAL(18, 2))) AS stockQty
|
||||
FROM rpt.jst_inventoryInfo i
|
||||
WHERE i.wms_co_id IN (${invIn.clause})
|
||||
GROUP BY i.wms_co_id, i.sku_id
|
||||
),
|
||||
ship AS (
|
||||
SELECT o.wms_co_id AS wmsCoId,
|
||||
oi.sku_id AS skuId,
|
||||
SUM(CAST(ISNULL(oi.qty, 0) AS DECIMAL(18, 2))) AS salesQty
|
||||
FROM rpt.jst_OrderItem oi
|
||||
JOIN rpt.jst_Orders o ON o.o_id = oi.o_id
|
||||
WHERE o.wms_co_id IN (${shipIn.clause})
|
||||
AND o.send_date >= @shipFrom
|
||||
AND o.send_date < @shipTo
|
||||
AND ISNULL(o.status, '') NOT IN ('Delete', 'Cancelled')
|
||||
GROUP BY o.wms_co_id, oi.sku_id
|
||||
),
|
||||
base AS (
|
||||
SELECT u.wmsCoId,
|
||||
u.skuId,
|
||||
SUM(u.stockQty) AS stockQty,
|
||||
SUM(u.salesQty) AS salesQty
|
||||
FROM (
|
||||
SELECT wmsCoId, skuId, stockQty, CAST(0 AS DECIMAL(18, 2)) AS salesQty FROM inv
|
||||
UNION ALL
|
||||
SELECT wmsCoId, skuId, CAST(0 AS DECIMAL(18, 2)) AS stockQty, salesQty FROM ship
|
||||
) u
|
||||
GROUP BY u.wmsCoId, u.skuId
|
||||
),
|
||||
graded AS (
|
||||
SELECT b.wmsCoId,
|
||||
b.stockQty,
|
||||
b.salesQty,
|
||||
${gradeCase} AS gradeKey
|
||||
FROM base b
|
||||
WHERE ABS(ISNULL(b.stockQty, 0)) > 0.0001
|
||||
OR ABS(ISNULL(b.salesQty, 0)) > 0.0001
|
||||
)
|
||||
SELECT g.wmsCoId,
|
||||
g.gradeKey,
|
||||
COUNT(*) AS skuCount,
|
||||
CAST(SUM(ISNULL(g.stockQty, 0)) AS DECIMAL(18, 2)) AS stockQty,
|
||||
CAST(SUM(ISNULL(g.salesQty, 0)) AS DECIMAL(18, 2)) AS salesQty,
|
||||
CAST(SUM(ISNULL(g.salesQty, 0) / @days) AS DECIMAL(18, 4)) AS dailySales
|
||||
FROM graded g
|
||||
GROUP BY g.wmsCoId, g.gradeKey`;
|
||||
|
||||
const rows = await cloudDb.query(sqlText, {
|
||||
...invIn.params,
|
||||
...shipIn.params,
|
||||
shipFrom,
|
||||
shipTo,
|
||||
days,
|
||||
}, { requestTimeout: 180000 });
|
||||
|
||||
return rows.map((r) => ({
|
||||
wmsCoId: String(r.wmsCoId),
|
||||
gradeKey: String(r.gradeKey),
|
||||
skuCount: Number(r.skuCount) || 0,
|
||||
stockQty: Number(r.stockQty) || 0,
|
||||
salesQty: Number(r.salesQty) || 0,
|
||||
dailySales: Number(r.dailySales) || 0,
|
||||
}));
|
||||
}
|
||||
|
||||
/**
|
||||
* 「销售=0」档的 SKU 级明细（导出用）。
|
||||
* 口径与 fetchGradeRows 完全一致：同一分档表达式命中 gradeKey='zero'，
|
||||
* 即统计窗口内销量 <= 0 且「有库存或有销量」的 SKU。
|
||||
*
|
||||
* 系统仓位取自 rpt.jst_packInventoryInfo.bin（jst_sku.bin 全为空、库存表无仓位字段）。
|
||||
* 每个仓位独立一行，库存数量按该仓位的实际 qty 统计（各仓位行之和 = SKU 总库存）：
|
||||
* - 有仓位数据的 SKU：按 (wms_co_id, sku_id, bin) 展开，qty=0 的仓位行剔除；
|
||||
* - 无仓位数据的 SKU（仓位表未覆盖的仓库）：保留一行，仓位为空、库存取 SKU 总库存，避免丢数。
|
||||
* @returns {Promise<Array<{wmsCoId:string, skuId:string, skuName:string, binName:string, stockQty:number, salesQty:number}>>}
|
||||
*/
|
||||
async function fetchZeroSaleSkuRows(cloudDb, wmsCoIds, { shipFrom, shipTo, days }) {
|
||||
if (!cloudDb || typeof cloudDb.query !== 'function') {
|
||||
throw new TypeError('fetchZeroSaleSkuRows 的第一个参数必须是业务库实例');
|
||||
}
|
||||
if (!Array.isArray(wmsCoIds) || wmsCoIds.length === 0) return [];
|
||||
if (!shipFrom || !shipTo || !days) return [];
|
||||
|
||||
const invIn = buildInClause(wmsCoIds, 'w');
|
||||
const shipIn = buildInClause(wmsCoIds, 'v');
|
||||
const gradeCase = buildGradeCase();
|
||||
|
||||
const sqlText = `
|
||||
WITH bin AS (
|
||||
SELECT p.wms_co_id AS wmsCoId,
|
||||
p.sku_id AS skuId,
|
||||
LTRIM(RTRIM(p.bin)) AS b,
|
||||
SUM(CAST(ISNULL(p.qty, 0) AS DECIMAL(18, 2))) AS binQty
|
||||
FROM rpt.jst_packInventoryInfo p
|
||||
WHERE ISNULL(p.bin, '') <> ''
|
||||
AND ISNULL(p.qty, 0) <> 0
|
||||
GROUP BY p.wms_co_id, p.sku_id, LTRIM(RTRIM(p.bin))
|
||||
),
|
||||
inv AS (
|
||||
SELECT i.wms_co_id AS wmsCoId,
|
||||
i.sku_id AS skuId,
|
||||
SUM(CAST(ISNULL(i.qty, 0) AS DECIMAL(18, 2))) AS stockQty
|
||||
FROM rpt.jst_inventoryInfo i
|
||||
WHERE i.wms_co_id IN (${invIn.clause})
|
||||
GROUP BY i.wms_co_id, i.sku_id
|
||||
),
|
||||
ship AS (
|
||||
SELECT o.wms_co_id AS wmsCoId,
|
||||
oi.sku_id AS skuId,
|
||||
SUM(CAST(ISNULL(oi.qty, 0) AS DECIMAL(18, 2))) AS salesQty
|
||||
FROM rpt.jst_OrderItem oi
|
||||
JOIN rpt.jst_Orders o ON o.o_id = oi.o_id
|
||||
WHERE o.wms_co_id IN (${shipIn.clause})
|
||||
AND o.send_date >= @shipFrom
|
||||
AND o.send_date < @shipTo
|
||||
AND ISNULL(o.status, '') NOT IN ('Delete', 'Cancelled')
|
||||
GROUP BY o.wms_co_id, oi.sku_id
|
||||
),
|
||||
base AS (
|
||||
SELECT u.wmsCoId,
|
||||
u.skuId,
|
||||
SUM(u.stockQty) AS stockQty,
|
||||
SUM(u.salesQty) AS salesQty
|
||||
FROM (
|
||||
SELECT wmsCoId, skuId, stockQty, CAST(0 AS DECIMAL(18, 2)) AS salesQty FROM inv
|
||||
UNION ALL
|
||||
SELECT wmsCoId, skuId, CAST(0 AS DECIMAL(18, 2)) AS stockQty, salesQty FROM ship
|
||||
) u
|
||||
GROUP BY u.wmsCoId, u.skuId
|
||||
),
|
||||
graded AS (
|
||||
SELECT b.wmsCoId,
|
||||
b.skuId,
|
||||
b.stockQty,
|
||||
b.salesQty,
|
||||
${gradeCase} AS gradeKey
|
||||
FROM base b
|
||||
WHERE ABS(ISNULL(b.stockQty, 0)) > 0.0001
|
||||
OR ABS(ISNULL(b.salesQty, 0)) > 0.0001
|
||||
)
|
||||
SELECT g.wmsCoId,
|
||||
g.skuId,
|
||||
ISNULL(s.name, '') AS skuName,
|
||||
ISNULL(bn.b, '') AS binName,
|
||||
CAST(COALESCE(bn.binQty, g.stockQty) AS DECIMAL(18, 2)) AS stockQty,
|
||||
CAST(g.salesQty AS DECIMAL(18, 2)) AS salesQty
|
||||
FROM graded g
|
||||
LEFT JOIN rpt.jst_sku s ON s.sku_id = g.skuId
|
||||
LEFT JOIN bin bn ON bn.wmsCoId = g.wmsCoId AND bn.skuId = g.skuId
|
||||
WHERE g.gradeKey = 'zero'
|
||||
ORDER BY g.wmsCoId, g.stockQty DESC, g.skuId, bn.b`;
|
||||
|
||||
const rows = await cloudDb.query(sqlText, {
|
||||
...invIn.params,
|
||||
...shipIn.params,
|
||||
shipFrom,
|
||||
shipTo,
|
||||
days,
|
||||
}, { requestTimeout: 180000 });
|
||||
|
||||
return rows.map((r) => ({
|
||||
wmsCoId: String(r.wmsCoId),
|
||||
skuId: String(r.skuId ?? ''),
|
||||
skuName: r.skuName == null ? '' : String(r.skuName),
|
||||
binName: r.binName == null ? '' : String(r.binName),
|
||||
stockQty: Number(r.stockQty) || 0,
|
||||
salesQty: Number(r.salesQty) || 0,
|
||||
}));
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
buildInClause,
|
||||
buildGradeCase,
|
||||
fetchGradeRows,
|
||||
fetchZeroSaleSkuRows,
|
||||
};
|
||||
@ -1,140 +0,0 @@
|
||||
'use strict';
|
||||
|
||||
/**
|
||||
* 「最晚退厂时间」取数（2026-09-28 新增）
|
||||
*
|
||||
* 业务口径：供应商不再合作时，工作平台会给该供应商一个「最晚退厂时间」，
|
||||
* 即它放在仓里的货最后必须拉走的日期，看板上跟「供应商是否合作」列并排展示。
|
||||
*
|
||||
* ── 数据在哪 ──────────────────────────────────────────────────────────────
|
||||
* 工作平台库。副本实例（218.93.9.21:1433）上共有 9 个库：
|
||||
* master / model / msdb / tempdb / SSISDB / JSReportReplica（副本，我们只读它）/
|
||||
* DataPlatformControl / WorkbenchDataShared / WorkbenchIdentity。
|
||||
* 「工作平台」= WorkbenchDataShared（配套身份库 WorkbenchIdentity，控制库 DataPlatformControl）。
|
||||
*
|
||||
* ── 当前为什么是空的（2026-09-28 已逐条取证，别再重复排查）───────────────
|
||||
* ① 副本账号 cangku 访问 WorkbenchDataShared / WorkbenchIdentity / DataPlatformControl
|
||||
* **一律被拒**：The server principal "cangku" is not able to access the database
|
||||
* "WorkbenchDataShared" under the current security context.
|
||||
* ② 系统设置（database_configs）里只有 cloud_database_public（JSReportReplica）与
|
||||
* product_information_database（PostgreSQL），没有工作平台库。
|
||||
* ③ 本机 .env 与生产 /opt/cangku/shared/backend.env 里的 JIAN_SUN_DB_HOST/USER/PASSWORD、
|
||||
* WORK_ORDER_* 全部为空（只留了端口/库名占位）。
|
||||
* ④ 副本库内部没有任何「退厂」字段：5,496 个字段全量搜过，COLUMN_NAME 含「退厂」的为 0；
|
||||
* 最接近的 fys_supplier.NoCoopTime（不合作时间）**不能拿来顶替** —— 它是停更快照
|
||||
* （DownloadTime 多在 2023~2024），崔桥仓 8 个不合作供应商里只有 1 个有值，
|
||||
* 而且那 1 条自身还标着 IsCoop='合作'，自相矛盾。
|
||||
*
|
||||
* ── IT 开通后怎么接（只需改本文件）────────────────────────────────────────
|
||||
* 二选一，改完即生效，页面与导出都会自动出数：
|
||||
* A. 给副本账号授只读：让 IT 执行 `USE WorkbenchDataShared; GRANT SELECT TO [cangku];`
|
||||
* （或建同义词/视图），然后把下面 EXIT_DATE_QUERY 填成跨库查询，例如：
|
||||
* SELECT SupplierName AS supplierName, CONVERT(varchar(10), LatestExitDate, 120) AS exitDate
|
||||
* FROM WorkbenchDataShared.dbo.<供应商不合作表>
|
||||
* B. 让 IT 把「供应商不合作」表同步进 JSReportReplica（像 js_supplier / fys_supplier 那样），
|
||||
* 再把 EXIT_DATE_QUERY 指向副本里的表名。
|
||||
* 查询只需要返回两列：supplierName（供应商名，口径同 js_supplier.scmname / jst_sku.supplier_name，
|
||||
* 即简称）与 exitDate（最晚退厂日期，字符串 'YYYY-MM-DD' 或 datetime 均可）。
|
||||
*
|
||||
* 未接入时本模块恒返回 available=false，页面该列显示「待接入」，不会报错、不影响其他列。
|
||||
*/
|
||||
|
||||
const cloudDb = require('../config/cloudDatabase');
|
||||
|
||||
const SOURCE_LABEL = '工作平台（WorkbenchDataShared）· 供应商不合作';
|
||||
const UNAVAILABLE_MESSAGE = '工作平台库尚未授权，待 IT 开通后自动出数';
|
||||
|
||||
// ---- 接入点（IT 开通后配这两个环境变量即可，不必改代码）--------------------
|
||||
// SUPPLIER_EXIT_DATE_ENABLED=true
|
||||
// SUPPLIER_EXIT_DATE_SQL=<查询语句，需返回 supplierName / exitDate 两列>
|
||||
// 也可以在下面 CODE_* 常量里直接写死（env 优先）。
|
||||
const CODE_EXIT_DATE_ENABLED = false;
|
||||
const CODE_EXIT_DATE_QUERY = '';
|
||||
const ENABLED = process.env.SUPPLIER_EXIT_DATE_ENABLED === 'true' || CODE_EXIT_DATE_ENABLED;
|
||||
const EXIT_DATE_QUERY = process.env.SUPPLIER_EXIT_DATE_SQL || CODE_EXIT_DATE_QUERY;
|
||||
// ---------------------------------------------------------------------------
|
||||
|
||||
const CACHE_TTL_MS = Number.parseInt(process.env.SUPPLIER_EXIT_DATE_CACHE_TTL_MS, 10) >= 0
|
||||
? Number.parseInt(process.env.SUPPLIER_EXIT_DATE_CACHE_TTL_MS, 10)
|
||||
: 30 * 60 * 1000;
|
||||
|
||||
let cache = null; // { at, payload }
|
||||
|
||||
const formatExitDate = (value) => {
|
||||
if (value === null || value === undefined || value === '') return '';
|
||||
if (value instanceof Date) {
|
||||
if (Number.isNaN(value.getTime())) return '';
|
||||
const y = value.getFullYear();
|
||||
const m = String(value.getMonth() + 1).padStart(2, '0');
|
||||
const d = String(value.getDate()).padStart(2, '0');
|
||||
return `${y}-${m}-${d}`;
|
||||
}
|
||||
const text = String(value).trim();
|
||||
if (!text) return '';
|
||||
const match = text.match(/^(\d{4})[-/.](\d{1,2})[-/.](\d{1,2})/);
|
||||
if (!match) return text;
|
||||
return `${match[1]}-${match[2].padStart(2, '0')}-${match[3].padStart(2, '0')}`;
|
||||
};
|
||||
|
||||
/**
|
||||
* 取「供应商 → 最晚退厂时间」映射。
|
||||
* 返回 { available, sourceLabel, message, bySupplier: Map<string, string> }
|
||||
*/
|
||||
async function loadSupplierExitDates() {
|
||||
const describe = () => ({
|
||||
available: false,
|
||||
sourceLabel: SOURCE_LABEL,
|
||||
message: UNAVAILABLE_MESSAGE,
|
||||
bySupplier: new Map(),
|
||||
});
|
||||
|
||||
if (!ENABLED || !EXIT_DATE_QUERY) return describe();
|
||||
if (cache && Date.now() - cache.at < CACHE_TTL_MS) return cache.payload;
|
||||
|
||||
try {
|
||||
const rows = await cloudDb.query(EXIT_DATE_QUERY, {}, { requestTimeout: 120000 });
|
||||
const bySupplier = new Map();
|
||||
(rows || []).forEach((row) => {
|
||||
const name = String(row.supplierName || '').trim();
|
||||
const date = formatExitDate(row.exitDate);
|
||||
if (!name || !date) return;
|
||||
const prev = bySupplier.get(name);
|
||||
// 同一供应商多条时取最晚的日期
|
||||
if (!prev || date > prev) bySupplier.set(name, date);
|
||||
});
|
||||
const payload = {
|
||||
available: true,
|
||||
sourceLabel: SOURCE_LABEL,
|
||||
message: '',
|
||||
bySupplier,
|
||||
};
|
||||
cache = { at: Date.now(), payload };
|
||||
return payload;
|
||||
} catch (error) {
|
||||
// 取不到不算致命：该列留空、页面提示待接入，其余列照常
|
||||
console.warn('[SupplierExitDate] 最晚退厂时间取数失败:', error.message);
|
||||
const payload = {
|
||||
available: false,
|
||||
sourceLabel: SOURCE_LABEL,
|
||||
message: `工作平台库读取失败（${error.message}），该列暂空`,
|
||||
bySupplier: new Map(),
|
||||
};
|
||||
cache = { at: Date.now(), payload };
|
||||
return payload;
|
||||
}
|
||||
}
|
||||
|
||||
const EMPTY_EXIT_DATES = Object.freeze({
|
||||
available: false,
|
||||
sourceLabel: SOURCE_LABEL,
|
||||
message: UNAVAILABLE_MESSAGE,
|
||||
bySupplier: new Map(),
|
||||
});
|
||||
|
||||
module.exports = {
|
||||
loadSupplierExitDates,
|
||||
formatExitDate,
|
||||
EMPTY_EXIT_DATES,
|
||||
EXIT_DATE_SOURCE_LABEL: SOURCE_LABEL,
|
||||
EXIT_DATE_UNAVAILABLE_MESSAGE: UNAVAILABLE_MESSAGE,
|
||||
};
|
||||
@ -1,559 +0,0 @@
|
||||
'use strict';
|
||||
|
||||
/**
|
||||
* 仓储中心 24 小时发货时效（2026-10-20 新增）
|
||||
* ────────────────────────────────────────────────────────────────────────────
|
||||
* 需求（yanhui 2026-10-20）：
|
||||
* MKH-BOM 列表左侧加一栏「仓储中心24小时发货时效」，下列 11 个仓：
|
||||
* 横林二仓 / 横林三仓 / 横林二仓品牌仓 / 崔桥工厂仓 / 崔桥工厂品牌仓 /
|
||||
* 崔桥工厂半成品包装项目仓 / 新苏北仓 / 睢宁仓 / 山东青岗集仓 / 山东品牌仓 / 河南洛宁仓
|
||||
* 从系统库存抓取「已发货订单」与「未发货订单」，按**订单审核时间**分轮核算。
|
||||
* 今天 07:00 前审核的订单 → 13:00 核验；**截止今天 16:00 前审核**的单（含今天之前未发的）→ 18:00 核验；
|
||||
* 昨天及更早审核、至今未发的（历史未发单）两个轮次都算。
|
||||
* （2026-10-20 三次调整：
|
||||
* 二次 —— 核验时刻由 12:00/16:00 改为 13:00/18:00；
|
||||
* 三次 —— ① **窗口按「审核时间」判**（不是创建时间）：业务指出的 9818476
|
||||
* （创建 10-18、审核 10-20 13:06）这类下午才审的单，不能进 13:00 轮；
|
||||
* ② **取消「满 24 小时才算超时」的门槛**：到核验时刻未发即超时；
|
||||
* ③ **历史未发单一律算**，不卡「今天 00:00 起」。
|
||||
* 业务原话：「当天 6:30 到 7 点审核的订单 13:00 核验；当天 7 点到
|
||||
* 16 点审核的订单 18:00 核验；然后再看历史未发的订单」。）
|
||||
* 展示口径：**只显示超时未发**（业务确认）。
|
||||
*
|
||||
* 业务确认的口径（2026-10-20）：
|
||||
* ① 子仓归属主仓 —— **连子仓一起算**（如 横林二仓 含京东自营仓/运营C专用仓 等）
|
||||
* 例外：「京仓-横林二仓京东云仓」业务指定**排除**，不计入任何主仓（见下）
|
||||
* ② 崔桥工厂半成品仓 —— 系统无同名仓，**接入「简尚-崔桥工厂半成品包装项目仓」**（15718196）
|
||||
* ③ 展示结构 —— **只显示超时未发**
|
||||
* ④ 明细列 —— 要同时给「内部单号」(o_id) 与「线上订单号」(so_id)
|
||||
*
|
||||
* ── 数据源 ────────────────────────────────────────────────────────────────
|
||||
* 订单：两张表**店铺互斥，必须都读**（见 mkhBomService 文件头）
|
||||
* rpt.jst_Orders —— 京东 / 拼多多 / 抖音 / 得物 / 唯品会
|
||||
* rpt.jst_qmcust_orderlist —— 天猫 / 淘宝 / 1688
|
||||
* 字段口径（2026-10-20 四次修正，全部以聚水潭「销售出库单」页面为准）：
|
||||
* · 创建时间：**销售出库单的 `created`**（出库单创建时间）
|
||||
* ⚠️ 不是 `order_date`（平台下单时间）；
|
||||
* ⚠️ 更不是 `modified` —— 实测数仓每天凌晨把整批订单的 modified 刷成
|
||||
* 02:2x / 04:3x（样本 9765107 等 7 单全是 10-20 04:39~04:40，
|
||||
* 实际下单在 10-13~10-18），拿它当创建时间会让所有单的时间被抹平；
|
||||
* ⚠️ 也不是 `created/createTime/updateTime`（数仓 5 分钟批量灌库时间戳）。
|
||||
* 待出库的单在出库单表里还没有记录 → 回退 `order_date` 并在接口里标注来源。
|
||||
* · 已出库：销售出库单表能查到该 o_id（有 `io_date`），**或**订单 `send_date`
|
||||
* 非空，**或**订单状态已是 `Sent` / `Delivering`。
|
||||
* · 待出库：以上三条都不满足。
|
||||
* · 发货仓： `wms_co_id`（订单**发货仓**，不是 SKU 的归属仓）
|
||||
* ⚠️ 用户原话「从系统库存抓取」—— 本实现取的是**订单维度**的仓库归属，
|
||||
* 因为 jst_inventoryInfo 只有「某 SKU 在某仓有多少件」，没有订单记录。
|
||||
*
|
||||
* ── 仓库归属（按名称包含匹配，最长匹配优先）────────────────────────────────
|
||||
* `rpt.jst_warehouseInfo` 实测（2026-10-20）：
|
||||
* 横林二仓 15033302 + 15301814/15835893/16040225/16132681
|
||||
* ⚠️ 15197138「京仓-横林二仓京东云仓」**业务指定排除**（见 EXCLUDED_WAREHOUSE_KEYWORDS）
|
||||
* 横林三仓 15043561
|
||||
* 横林二仓品牌仓 16132681（**同时命中也属于「横林二仓」，靠最长匹配优先归到品牌仓**）
|
||||
* 崔桥工厂仓 15038426 + 15301815/16040410
|
||||
* 崔桥工厂品牌仓 15870495
|
||||
* 崔桥工厂半成品包装项目仓 15718196（原名「简尚-崔桥工厂半成品包装项目仓」）
|
||||
* 新苏北仓 15038347 + 15315031/15301812
|
||||
* 睢宁仓 15032603 + 15051907/15051960/15052203/15301813/15386911
|
||||
* 山东青岗集仓 15137523 + 15283033/15406664/15835935/16040432/16129076
|
||||
* 山东品牌仓 15182705
|
||||
* 河南洛宁仓 15539084
|
||||
* ⟹ 仓库 ID → 主仓 的映射**在启动时从库表读取并缓存**（不用手写 ID 常量，
|
||||
* 避免上游新增子仓后要改代码；新增子仓只要名字里带主仓关键词就会自动归入）。
|
||||
* 缓存 TTL 1 小时，可用 clearWarehouseCache() 手动清。
|
||||
*
|
||||
* ── 时效判定 ──────────────────────────────────────────────────────────────
|
||||
* 两个时刻**必须区分**（2026-10-20 二次调整后最容易搞混的地方）：
|
||||
* `verifyHour` —— 几点核验（13:00 / 18:00）。判定「发了没发」「超时多久」都用它。
|
||||
* `windowEndHour` —— 订单窗口上界（07:00 / 16:00）。只核验该时刻**前审核**的单。
|
||||
* 取当前已生效且最晚的那一轮；未到 13:00 时无核验轮次：
|
||||
* 13:00 → 核验「今天 00:00~07:00 审核」的订单 + 历史未发
|
||||
* 18:00 → 核验「截止今天 16:00 前审核」的订单 + 今天之前审核仍未发的（历史未发）
|
||||
* ⚠️ 不是「今天 00:00~16:00」这一个自然日切片，历史未发也在内；
|
||||
* 山东两仓窗口上界 15:00、河南洛宁 13:00（核验时刻仍是 18:00）。
|
||||
* 判定（2026-10-20 三次修正 —— **没有「满 24 小时」门槛**）：
|
||||
* · 超时未出库 = 到核验时刻仍未发货
|
||||
* （出库单表查不到 + `send_time` 为空 + 状态不是 Sent/Delivering）
|
||||
* 🔥 第七版错在加了「创建满 24h 才算超时」，导致 13:00 轮永远
|
||||
* 看不到当天 7 点那批（才等了 6 小时），业务直接打回。
|
||||
* · 已出库 = 出库单表有记录 / send_date 非空 / 状态 Sent、Delivering
|
||||
* · 拆单父单（is_split=1）、被合并单（is_merge=1）**一律排除** ——
|
||||
* 它们自己永不发货，货由子单/主单发出，算进来就是冤枉仓库。
|
||||
* 业务只要「超时未出库」，所以列表只返回待出库的超时单。
|
||||
*
|
||||
* ── 时区 ──────────────────────────────────────────────────────────────────
|
||||
* 订单时间列存的是**东八区本地时间**（实测 `order_date` 与 `created` 相差十几秒，
|
||||
* 均为北京时间）。因此 SQL 里统一用 `CAST(GETDATE() AS date)` 取「今天」，
|
||||
* 服务器与数据库都在东八区；**不要**在 Node 侧用 UTC 日期做判断。
|
||||
*/
|
||||
|
||||
const cloudDatabase = require('../config/cloudDatabase');
|
||||
|
||||
// ── 主仓定义（业务给定的 11 个）──────────────────────────────────────────
|
||||
// keywords：该主仓在 rpt.jst_warehouseInfo.name 里应包含的关键词（任一命中即归属）
|
||||
// 顺序即展示顺序；`match` 用最长关键词优先，所以「横林二仓品牌仓」不会被「横林二仓」抢走。
|
||||
const CENTERS = Object.freeze([
|
||||
{ key: 'HL2', name: '横林二仓', keywords: ['横林二仓'] },
|
||||
{ key: 'HL3', name: '横林三仓', keywords: ['横林三仓'] },
|
||||
{ key: 'HL2_BRAND', name: '横林二仓品牌仓', keywords: ['横林二仓品牌仓'] },
|
||||
{ key: 'CQ', name: '崔桥工厂仓', keywords: ['崔桥工厂仓'] },
|
||||
{ key: 'CQ_BRAND', name: '崔桥工厂品牌仓', keywords: ['崔桥工厂品牌仓'] },
|
||||
// 2026-10-20 二次调整：原先「崔桥工厂半成品仓」在仓库表里没有同名仓，只能留空占位；
|
||||
// 业务指定用「简尚-崔桥工厂半成品包装项目仓」(wms_co_id=15718196, Id=198) 替代接入。
|
||||
// ⚠️ 该 wms_co_id 同时也是配件仓（MKH 配件库存来源），但这里是**订单发货仓**维度，
|
||||
// 统计的是「从该仓发出的订单」，与配件库存口径无关，不要混。
|
||||
{ key: 'CQ_WIP', name: '崔桥工厂半成品包装项目仓', keywords: ['崔桥工厂半成品'] },
|
||||
{ key: 'XSB', name: '新苏北仓', keywords: ['新苏北'] },
|
||||
{ key: 'SN', name: '睢宁仓', keywords: ['睢宁'] },
|
||||
// 🔥 山东两个仓 18:00 轮的窗口更早（15:00 前，不是 16:00）——
|
||||
// 业务 2026-10-20：「山东青岗集仓和山东品牌仓，这 2 个仓库时间不是 16:00 前，
|
||||
// 是 15:00 前订单」。核验时刻仍是 18:00，只是卡单的范围窄一小时。
|
||||
{ key: 'SD_QGJ', name: '山东青岗集仓', keywords: ['山东青岗集'], windowEndHourByRound: { AFTERNOON: 15 } },
|
||||
{ key: 'SD_BRAND', name: '山东品牌仓', keywords: ['山东品牌仓'], windowEndHourByRound: { AFTERNOON: 15 } },
|
||||
// 🔥 河南洛宁仓更早：18:00 轮只看 13:00 前创建的单（业务同一条指令）
|
||||
{ key: 'HN_LN', name: '河南洛宁仓', keywords: ['河南洛宁'], windowEndHourByRound: { AFTERNOON: 13 } },
|
||||
]);
|
||||
|
||||
// 各主仓在某一轮的窗口上界小时。
|
||||
// 返回 null 表示「用轮次默认值」（ROUNDS[].windowEndHour）。
|
||||
// ⚠️ 13:00 轮没有例外，全部按 07:00；只有 18:00 轮有三处更早的上界。
|
||||
function centerWindowEndHour(centerKey, roundKey) {
|
||||
const center = CENTERS.find((c) => c.key === centerKey);
|
||||
const override = center && center.windowEndHourByRound
|
||||
? center.windowEndHourByRound[roundKey]
|
||||
: undefined;
|
||||
return Number.isFinite(override) ? override : null;
|
||||
}
|
||||
|
||||
/** 该主仓在这一轮的窗口上界（'YYYY-MM-DD HH:mm:00'），没有例外就用轮次默认 */
|
||||
function centerWindowEnd(centerKey, round) {
|
||||
const hour = centerWindowEndHour(centerKey, round.key);
|
||||
if (hour === null) return round.windowEnd;
|
||||
return `${round.date} ${String(hour).padStart(2, '0')}:00:00`;
|
||||
}
|
||||
|
||||
// 「横林三仓」与「横林二仓」不含对方，安全；但「崔桥工厂品牌仓」含「崔桥工厂仓」片段，
|
||||
// 靠关键词长度倒序匹配即可（见 resolveCenter）。
|
||||
const SORTED_KEYWORDS = CENTERS
|
||||
.filter((c) => c.keywords.length)
|
||||
.flatMap((c) => c.keywords.map((kw) => ({ kw, center: c })))
|
||||
.sort((a, b) => b.kw.length - a.kw.length);
|
||||
|
||||
// ── 排除仓（业务指定，2026-10-20）──────────────────────────────────────────
|
||||
// 「京仓-横林二仓京东云仓」(wms_co_id=15197138, Id=129) 虽然名字里带「横林二仓」，
|
||||
// 但属于京东云仓代运营，**不纳入横林二仓的时效考核**（业务明确要求排除）。
|
||||
// ⚠️ 用完整片段「横林二仓京东云仓」而不是「京东云仓」：
|
||||
// 仓库表里还有「京仓-崔桥工厂京东云仓」(15283032)、
|
||||
// 「京仓-山东青岗集京东云仓」(15283033)，写短了会把它们一起排掉；
|
||||
// 也不会误伤「简尚-横林二仓京东仓」(16040225) 与「京仓-横林二仓京东自营仓」(15835893)。
|
||||
const EXCLUDED_WAREHOUSE_KEYWORDS = Object.freeze([
|
||||
'横林二仓京东云仓',
|
||||
]);
|
||||
|
||||
// 长关键词优先，避免以后加了「XX京东云仓」被短词抢先
|
||||
const SORTED_EXCLUSIONS = [...EXCLUDED_WAREHOUSE_KEYWORDS].sort((a, b) => b.length - a.length);
|
||||
|
||||
// ── 时效轮次（业务给定，2026-10-20 二次调整）──────────────────────────────
|
||||
// verifyHour ：当天几点开始核验（13:00 / 18:00）
|
||||
// windowEndHour ：只核验「**审核时间**不晚于该时刻」的订单（07:00 / 16:00）
|
||||
// ⚠️ 两者**不是同一个东西**，别再用一个字段兼着当：
|
||||
// 旧实现拿 12:00 同时当核验时刻和窗口上界，导致「12:00 轮」实际把
|
||||
// 07:00~12:00 创建的单也算进来了，与页面上写的「核验 07:00 前」不一致。
|
||||
// ⚠️ 也不能在 windowEnd 之后再叠「满 N 小时」门槛 —— 13:00 轮里 07:00 审核的单
|
||||
// 只等了 6 小时，加门槛就永远不出现在超时列表里（第七版被打回的原因）。
|
||||
const ROUNDS = Object.freeze([
|
||||
{ key: 'NOON', label: '13:00 轮', verifyHour: 13, windowEndHour: 7 },
|
||||
{ key: 'AFTERNOON', label: '18:00 轮', verifyHour: 18, windowEndHour: 16 },
|
||||
]);
|
||||
|
||||
// ── 订单窗口下界（含历史的天数，**业务可调**）────────────────────────────
|
||||
// 业务口径（2026-10-20 三次纠偏）：「截止某时刻创建、至今仍未发货」—— 不按自然日切，
|
||||
// 昨天、前天乃至更早挂着没发的单都要算进来（滚动累积的待发池）。
|
||||
//
|
||||
// ⚠️ 但不能无限往前：rpt 下全是视图、没有索引，扫得越远越慢。2026-10-20 实测
|
||||
// （jst_Orders + jst_qmcust 并行，含已发单的窗口全量）：
|
||||
// 近 7 天 → 约 5s 近 30 天 → 约 45s
|
||||
// 近 90 天 → 约 130s 近 365 天 → 约 500s（基本等于页面卡死）
|
||||
// 所以默认取 30 天：覆盖「今日 + 近一个月累积未发」，兼顾口径与可用性。
|
||||
//
|
||||
// 同时实测 28 个目标仓的**全部未发单**：共 1,228 条，其中近 7 天 257、
|
||||
// 近 30 天 496、近 90 天 792、更早 436（最早 2025-10-24）。
|
||||
// ⟹ 30 天能看到约 40%；要看更久的老单，把下面数字改大，代价是首屏更慢。
|
||||
const HISTORY_LOOKBACK_DAYS = 30;
|
||||
|
||||
// 只排除取消/合并单；Question 仍计入（与 mkhBomService 待发货口径一致）
|
||||
//
|
||||
// 🔥 Split（拆单）：**必须排除**。拆单是「父单被拆成子单」的中间态，父单本身
|
||||
// 不会发货（`send_date` 永远为空），子单才是真正进仓发货的那一单。
|
||||
// 2026-10-20 实测：不加这个条件，一年前的 Split 父单全被算成「超时未发」，
|
||||
// 全库未发 Split 单占比极高 —— 会让页面变成上万条的垃圾列表。
|
||||
// ⚠️ 与 mkhBomService 的差异：那边是「预警今天要发的货」，Split 父单不带真实
|
||||
// 发货需求，被算进去也无害；这边是「考核仓库时效」，误算就要背锅，必须排除。
|
||||
const EXCLUDED_STATUS_SQL = `ISNULL(o.status, N'') NOT IN (N'Cancelled', N'Merged', N'Split')`;
|
||||
|
||||
// ── 「已发货 / 待发货」状态口径（2026-10-20 四次修正，业务反馈数据错误）────
|
||||
// 🔥 之前只排除了 Cancelled/Merged/Split，靠 `send_date IS NULL` 判「未发」，
|
||||
// 实测**大量已发货的单被算成超时未发**（业务一眼就看出来了）。原因有三个：
|
||||
// ① `send_date` 在部分店铺/平台不回写，订单状态已经是 Sent/Delivering，
|
||||
// send_date 却还是 NULL（样本 9838341：Delivering，send_date 空）；
|
||||
// ② 拆单父单 `status` 不是 'Split' 而是 'Delivering'（父单随子单状态走），
|
||||
// `is_split=1` 才是真标记（样本 9838537 就是这样）；
|
||||
// ③ 合并单 `is_merge=1` 同理，被并入主单，自己永不发货。
|
||||
// 订单状态实测分布（2026-10-20，近 7 天，两表合计）：
|
||||
// Sent 61,833 / Cancelled 22,292 / Split 4,927 / Delivering 2,567 /
|
||||
// Question 1,500 / Merged 682 / WaitOuterSent 30 / WaitConfirm 12
|
||||
// ⟹ 判定「已发货」= status ∈ (Sent, Delivering) **或** send_date 非空
|
||||
// **或** 销售出库单表能查到该 o_id（见 OUTBOUND_TABLES）
|
||||
const SHIPPED_STATUS = Object.freeze(['Sent', 'Delivering']);
|
||||
|
||||
// 待出库候选：把「已发货」状态一并排除。判定顺序是
|
||||
// ① SQL 先粗筛（下面这个条件 + send_date IS NULL + 非拆单/合并）
|
||||
// ② Node 侧再查销售出库单表精确剔除（有出库记录 = 其实已出库）
|
||||
// ③ Node 侧再把 Question（疑问单）分流到「业务挂起」，**不计超时**
|
||||
// —— 注意 Question 必须留在候选里，否则统计不出挂起单数；
|
||||
// 它只是不进 orders（超时明细），走 heldCount / heldOrders。
|
||||
const PENDING_STATUS_SQL = `ISNULL(o.status, N'') NOT IN (N'Cancelled', N'Merged', N'Split', N'Sent', N'Delivering')`;
|
||||
|
||||
// 拆单父单 / 被合并单：自己**永不发货**，货由子单或主单发出。
|
||||
// 只排 status 不够（父单状态会跟着子单变成 Delivering），必须看标记位。
|
||||
// ⚠️ is_split / is_merge 是 bit 且可能为 NULL —— 必须 ISNULL 兜底，
|
||||
// 否则 `o.is_split = 0` 会把 NULL 行全部丢掉（实测会少掉大半候选）。
|
||||
const NOT_SPLIT_MERGED_SQL = `ISNULL(o.is_split, 0) = 0 AND ISNULL(o.is_merge, 0) = 0`;
|
||||
|
||||
// ── 销售出库单表（聚水潭「销售出库单」页面的数据来源）──────────────────────
|
||||
// 业务明确要求（2026-10-20）：「已出库 / 待出库」与「创建时间」都以聚水潭
|
||||
// **销售出库单**页面为准，不再用订单表的 send_date 猜。
|
||||
//
|
||||
// 两张表与订单表同构、店铺互斥：
|
||||
// rpt.jst_salesOutboundInfo ← jst_Orders（京东/拼多多/抖音/得物/唯品会），103.7 万行
|
||||
// rpt.jst_qmcust_salesoutbound ← jst_qmcust_orderlist（天猫/淘宝/1688），39.8 万行
|
||||
// 字段口径（2026-10-20 实测确认）：
|
||||
// · `created` —— **出库单创建时间**（业务在聚水潭出库单页面看到的那个），
|
||||
// 时点分布自然（8~23 点均匀，凌晨 4 点有一波补录），可用；
|
||||
// · `io_date` —— **出库时间**（真正发货那一刻）；
|
||||
// · `modified` —— ⚠️ 会被数仓每天凌晨批量刷新（实测全被刷成 02:2x / 04:3x），
|
||||
// 与订单表的 modified 一样**不可当作创建时间**；
|
||||
// · **两张表都只含「已出库」的单**：103.7 万行里 io_date 为 0 条空值。
|
||||
// ⟹ 「待出库」无法从出库单表直接查，只能靠「查不到 = 还没出库」反推。
|
||||
const OUTBOUND_TABLES = Object.freeze({
|
||||
jst_Orders: 'jst_salesOutboundInfo',
|
||||
jst_qmcust_orderlist: 'jst_qmcust_salesoutbound',
|
||||
});
|
||||
|
||||
// ── 聚水潭「订单实时状态」表（2026-10-20 五次修正：按审核时间核算）──────────
|
||||
// 🔥 前面三版的根因都在这里：`jst_Orders.status` / `jst_qmcust_orderlist.status`
|
||||
// 是**下单那一刻的快照**，之后聚水潭侧取消、售后、审核都不会回写。
|
||||
// 实测（2026-10-20）：业务反馈「聚水潭查不到」的 6 单，订单表里
|
||||
// status 全是 `WaitConfirm`，而在本表里真实状态是 **已取消**（发货前售后）；
|
||||
// 另有 1 单真实状态是 **异常**。上一版把它们当成「待出库超时」报了出来。
|
||||
//
|
||||
// `rpt.jst_order_express_details`（402 万行，query_time 准实时，最近一次今天 11:55）
|
||||
// 是聚水潭订单状态的准实时镜像，字段语义（近 30 天实测覆盖率）：
|
||||
// · `order_status_name` —— 聚水潭真实订单状态
|
||||
// 已发货 269,991（send_time 100%）｜已取消 64,440｜异常 6,669
|
||||
// 发货中 2,448（first_oa 99.96%、send_time 0）｜已支付待审核 833
|
||||
// · `first_oa_confirm_time` —— **订单审核时间**（首次 OA 确认）＝ 业务要的起算点
|
||||
// · `last_oa_confirm_time` —— 最后一次审核（重新审核会刷新）
|
||||
// · `send_time` —— **发货时间**（已发货单 100% 有值，未发单必为空）
|
||||
// · `warehouse_name` —— 发货仓名称（可直接套 CENTERS 关键词匹配）
|
||||
// · `logistic_status_name` —— 物流状态（无物流单 / 未揽收 / 运输中 …）
|
||||
// ⚠️ 本表**没有金额**，金额要回订单表按 `o_id = inner_order_id` 取。
|
||||
const ORDER_STATE_TABLE = 'jst_order_express_details';
|
||||
|
||||
// 「发货中」= 已审核、仓库还没发货 —— **唯一该考核仓库的状态**
|
||||
const SHIPPING_STATUS = '发货中';
|
||||
// 「已支付待审核」= 还没审单，仓库根本没接到 → 不计超时（单列为「待审核」）
|
||||
const UNAUDITED_STATUS = '已支付待审核';
|
||||
// 「异常」= 订单异常（缺货/地址/风控等），有审核时间的单列「异常待处理」，不计仓库超时
|
||||
const ABNORMAL_STATUS = '异常';
|
||||
// 不进考核也不展示的状态：已发货（已发）、已取消（业务侧取消/发货前售后）、
|
||||
// 等供销商|外仓发货（不是本仓发）
|
||||
// 🔥 「已取消」（业务口头叫**作废单**）必须排除（2026-10-20 业务定：「作废订单不用考核」）：
|
||||
// 这类单是客户付款后取消 / 发货前售后（标签带「发货前售后」），仓库根本不会发货。
|
||||
// 2026-10-20 实测：近 30 天已取消 64,440 单，量级远大于真正该考核的「发货中」2,448 单，
|
||||
// 漏掉这个排除，整个页面会被作废单淹没。
|
||||
const IGNORED_STATES = Object.freeze(['已发货', '已取消', '等供销商|外仓发货']);
|
||||
|
||||
// ── 起算点：聚水潭「创建时间」──────────────────────────────────────────────
|
||||
// 业务 2026-10-20 最终定版：「起算点是聚水潭的创建时间，不是审核时间」。
|
||||
//
|
||||
// ⚠️ 状态表 `jst_order_express_details` **没有**聚水潭创建时间，必须回订单表补：
|
||||
// · `createdAt`（本表那个 datetime2）—— ❌ **不是**订单创建时间。
|
||||
// 实测比付款晚 1.5~3.5 小时（261019-… pay 21:05:16 / createdAt 次日 00:23:51），
|
||||
// 是**同步落库时间**，用了会把起算点整体推后几小时。
|
||||
// · `pay_time` —— ❌ 付款时间，业务明确说「这一单的创建还是按照付款时间来的」，
|
||||
// 要换掉。
|
||||
// · ✅ `jst_Orders.created` / `jst_qmcust_orderlist.created` —— **聚水潭创建时间**，
|
||||
// 稳定比下单/付款晚 15~30 秒（抽样 00:07:23 → 00:07:41），
|
||||
// 这才是聚水潭订单列表里「创建时间」那一列。
|
||||
//
|
||||
// 性能（2026-10-20 实测 9,676 个候选）：
|
||||
// 只投影 `o_id, created` 两列、分批 200 → jst_Orders **14.5s** + qmcust **2.9s**。
|
||||
// 🔥 千万别顺手把 pay_amount / labels 一起取出来：同样 IN 400 个只要 **38.7s**。
|
||||
const CREATED_SOURCE_TABLES = Object.freeze(['jst_Orders', 'jst_qmcust_orderlist']);
|
||||
// 分批大小：200 实测最快（再大收益递减，再小批数太多）
|
||||
const CREATED_BACKFILL_BATCH = 200;
|
||||
|
||||
// ── 订单表里的「作废」状态：这些单不会由本单发货，必须剔除 ─────────────────
|
||||
// 业务 2026-10-20 反馈 so_id 5127276315127080023（内部单号 9486414）是作废单，
|
||||
// 却出现在超时未发货里。四张表对照后的真相：
|
||||
// · 状态表 jst_order_express_details：order_status_name=**发货中**、send_time 空
|
||||
// ⟹ 只信状态表的话，这单就是「超时未发」—— 我们就是这么误判的；
|
||||
// · 订单表 jst_qmcust_orderlist：status=**Merged**、send_date=2026-09-22 06:54:49；
|
||||
// · 销售出库单：两张表**都有**出库记录（io_date 2026-09-22 10:59:55）。
|
||||
// ⟹ 根因：状态表的 `send_time` 对**被合并单 / 拆单父单不回写**，
|
||||
// 单子早随主单发走了，状态表还停在「发货中」。
|
||||
// ⟹ 所以除了状态表的 send_time，还**必须**回订单表看 status 与合并/拆单标记位，
|
||||
// 以及查销售出库单（业务最早的口径：有出库单 = 已出库）。
|
||||
const VOID_ORDER_STATUS = Object.freeze(['Merged', 'Split', 'Cancelled']);
|
||||
|
||||
// 24 小时发货时效 —— ⚠️ 仅用于**页面命名/路由**，**不参与判定**。
|
||||
// 2026-10-20 三次调整后判定改成「到 13:00 / 18:00 核验时刻仍未发即超时」，
|
||||
// 没有滚动 24 小时窗口（见 SHIP_TIMELINESS_HOURS 的历史误用记录）。
|
||||
const SHIP_TIMELINESS_HOURS = 24;
|
||||
|
||||
const WAREHOUSE_CACHE_TTL_MS = 60 * 60 * 1000;
|
||||
let warehouseCache = { at: 0, rows: [] };
|
||||
|
||||
function toNumber(value) {
|
||||
const n = Number(value);
|
||||
return Number.isFinite(n) ? n : 0;
|
||||
}
|
||||
|
||||
function pad2(n) {
|
||||
return String(n).padStart(2, '0');
|
||||
}
|
||||
|
||||
// 🔥 北京时间（UTC+8）偏移，分钟
|
||||
const BEIJING_OFFSET_MINUTES = 480;
|
||||
|
||||
/**
|
||||
* 取「按北京时间读出来」的当前时刻。
|
||||
*
|
||||
* 🔥 为什么不能直接 `new Date()`（2026-10-21 生产实测踩坑）：
|
||||
* 生产容器 `/etc/timezone = Etc/UTC`（date = UTC），而 MSSQL `GETDATE()` 返回**北京时间**，
|
||||
* mssql 驱动 `useUTC:false` 又把 DB 值构造成「墙钟当 UTC」的 Date。
|
||||
* 于是「服务器 now」比「库里的时间」慢 8 小时 —— **北京时间每天 00:00~08:00，
|
||||
* 服务端取到的「今天」是昨天**，轮次窗口 / 核验时刻整体错位
|
||||
* （实测 08:04 跑 13:00 轮得 overdueUnshipped=3895，本地北京时区同一轮只有 6 单）。
|
||||
*
|
||||
* 做法：把真实时刻平移成一个「本地 getter 读出来正好是北京时间」的 Date，
|
||||
* 这样 `getHours()/getDate()/formatDateTime()` 与库里的字符串可以直接比较。
|
||||
* 本机已是东八区时平移量为 0，行为不变（测试无需改）。
|
||||
*
|
||||
* @param {Date} [base] 真实时刻，默认 `new Date()`
|
||||
* @returns {Date} 本地 getter = 北京时间的 Date
|
||||
*/
|
||||
function beijingNow(base = new Date()) {
|
||||
const shift = BEIJING_OFFSET_MINUTES + base.getTimezoneOffset();
|
||||
return shift === 0 ? base : new Date(base.getTime() + shift * 60 * 1000);
|
||||
}
|
||||
|
||||
/**
|
||||
* 用「关键词最长匹配」把仓库名归到主仓。
|
||||
*
|
||||
* ⚠️ **先判排除、再判归属**：被排除的仓（如「京仓-横林二仓京东云仓」）
|
||||
* 即使名字里带主仓关键词，也直接返回 null —— 它的订单不计入任何主仓。
|
||||
*
|
||||
* @returns {object|null} CENTERS 里的元素；无法归属或被排除返回 null
|
||||
*/
|
||||
function resolveCenter(warehouseName) {
|
||||
if (!warehouseName) return null;
|
||||
const name = String(warehouseName);
|
||||
for (const kw of SORTED_EXCLUSIONS) {
|
||||
if (name.includes(kw)) return null;
|
||||
}
|
||||
for (const item of SORTED_KEYWORDS) {
|
||||
if (name.includes(item.kw)) return item.center;
|
||||
}
|
||||
return null;
|
||||
}
|
||||
|
||||
/**
|
||||
* 拉取仓库表并建立「主仓 → wms_co_id 列表」映射。
|
||||
* 缓存 1 小时；仓库表变更不频繁，且新增子仓会自动被关键词捞到。
|
||||
*/
|
||||
async function loadCenterWarehouseMap(force = false) {
|
||||
const fresh = Date.now() - warehouseCache.at < WAREHOUSE_CACHE_TTL_MS;
|
||||
if (!force && fresh && warehouseCache.rows.length) {
|
||||
return warehouseCache.rows;
|
||||
}
|
||||
// ⚠️ cloudDatabase.query() 直接返回 recordset 数组，不是 {recordset} 对象
|
||||
const rows = (await cloudDatabase.query(
|
||||
`SELECT Id, name, wms_co_id
|
||||
FROM dbo.jst_warehouseInfo`,
|
||||
{},
|
||||
{ requestTimeout: 60000 }
|
||||
)) || [];
|
||||
const byCenter = new Map(CENTERS.map((c) => [c.key, []]));
|
||||
const unmatched = [];
|
||||
const excluded = [];
|
||||
for (const row of rows) {
|
||||
const name = String(row.name || '');
|
||||
// 被业务排除的仓单独记录，方便日后核对「是不是排多了/排少了」
|
||||
if (SORTED_EXCLUSIONS.some((kw) => name.includes(kw))) {
|
||||
excluded.push({ wmsCoId: Number(row.wms_co_id), name });
|
||||
continue;
|
||||
}
|
||||
const center = resolveCenter(name);
|
||||
if (center && byCenter.has(center.key)) {
|
||||
byCenter.get(center.key).push({
|
||||
wmsCoId: Number(row.wms_co_id),
|
||||
warehouseId: Number(row.Id),
|
||||
name,
|
||||
});
|
||||
} else {
|
||||
unmatched.push({ wmsCoId: Number(row.wms_co_id), name });
|
||||
}
|
||||
}
|
||||
const list = CENTERS.map((c) => ({
|
||||
key: c.key,
|
||||
name: c.name,
|
||||
placeholder: Boolean(c.placeholder),
|
||||
warehouses: byCenter.get(c.key) || [],
|
||||
}));
|
||||
warehouseCache = {
|
||||
at: Date.now(),
|
||||
rows: list,
|
||||
unmatchedCount: unmatched.length,
|
||||
excluded,
|
||||
};
|
||||
return list;
|
||||
}
|
||||
|
||||
function clearWarehouseCache() {
|
||||
warehouseCache = { at: 0, rows: [] };
|
||||
}
|
||||
|
||||
/**
|
||||
* 计算「当前已生效」的核验轮次。
|
||||
*
|
||||
* 13:00 之前 → **未到核验时间，返回 null**。
|
||||
* 业务明确要求（2026-10-20 确认）：未到核验时刻不做核验，
|
||||
* 前端显示「未到核验时间」，**不要回填昨天的数据** ——
|
||||
* 昨天已结算的结果留到昨天，拿到今天看容易被当成今天的超时。
|
||||
* 13:00~17:59 → 用 13:00 轮（今天 00:00~07:00 **审核** + 历史未发）
|
||||
* 18:00 之后 → 用 18:00 轮（截止 16:00 前**审核** + 今天之前未发的历史单）
|
||||
*
|
||||
* 🔥 「含历史」是 2026-10-20 业务第三次纠偏：
|
||||
* 原实现把下界卡在「今天 00:00」，只统计当天新单，把昨天及更早挂着没发的
|
||||
* 单全漏掉了。业务口径是「……然后再看历史未发的订单」——
|
||||
* 这是一个滚动累积的待发池，不按自然日切。
|
||||
*
|
||||
* @param {Date} now 北京时间（默认 `beijingNow()`，容器是 UTC 时也安全）
|
||||
* @returns {object|null} null 表示当前不在任何核验时段内
|
||||
*/
|
||||
function resolveActiveRound(now = beijingNow()) {
|
||||
const hour = now.getHours();
|
||||
const minute = now.getMinutes();
|
||||
const minutes = hour * 60 + minute;
|
||||
let active = null;
|
||||
for (const round of ROUNDS) {
|
||||
if (minutes >= round.verifyHour * 60) active = round;
|
||||
}
|
||||
|
||||
// 13:00 前：首轮核验还没开始，不做判定
|
||||
if (!active) return null;
|
||||
|
||||
const y = now.getFullYear();
|
||||
const m = pad2(now.getMonth() + 1);
|
||||
const d = pad2(now.getDate());
|
||||
// 护栏起点（不是业务下界，见 HISTORY_LOOKBACK_DAYS）
|
||||
const floor = new Date(y, now.getMonth(), now.getDate() - HISTORY_LOOKBACK_DAYS);
|
||||
const floorStr = `${floor.getFullYear()}-${pad2(floor.getMonth() + 1)}-${pad2(floor.getDate())} 00:00:00`;
|
||||
return {
|
||||
...active,
|
||||
// deadline = 核验时刻：判「发了没发 / 超时多久」都用它
|
||||
deadline: `${y}-${m}-${d} ${pad2(active.verifyHour)}:00:00`,
|
||||
windowStart: floorStr,
|
||||
// windowEnd = 订单窗口上界：SQL 的取数上界，**不是** deadline
|
||||
windowEnd: `${y}-${m}-${d} ${pad2(active.windowEndHour)}:00:00`,
|
||||
// 含历史未发单 —— 前端据此把「统计窗口 00:00~07:00」改成「截止 07:00 前（含历史）」
|
||||
includeHistory: true,
|
||||
date: `${y}-${m}-${d}`,
|
||||
settled: false,
|
||||
isPreviousDay: false,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* 取「当天两轮」的完整描述（页面顶部展示用），不论是否已到时间。
|
||||
*/
|
||||
function describeRounds(now = beijingNow()) {
|
||||
const y = now.getFullYear();
|
||||
const m = pad2(now.getMonth() + 1);
|
||||
const d = pad2(now.getDate());
|
||||
const date = `${y}-${m}-${d}`;
|
||||
const minutes = now.getHours() * 60 + now.getMinutes();
|
||||
const floor = new Date(y, now.getMonth(), now.getDate() - HISTORY_LOOKBACK_DAYS);
|
||||
const floorStr = `${floor.getFullYear()}-${pad2(floor.getMonth() + 1)}-${pad2(floor.getDate())} 00:00:00`;
|
||||
return ROUNDS.map((r) => ({
|
||||
key: r.key,
|
||||
label: r.label,
|
||||
date,
|
||||
verifyHour: r.verifyHour,
|
||||
deadline: `${date} ${pad2(r.verifyHour)}:00:00`,
|
||||
windowStart: floorStr,
|
||||
windowEnd: `${date} ${pad2(r.windowEndHour)}:00:00`,
|
||||
includeHistory: true,
|
||||
active: minutes >= r.verifyHour * 60,
|
||||
}));
|
||||
}
|
||||
|
||||
/**
|
||||
* 下一轮的核验时刻。
|
||||
*
|
||||
* ⚠️ 2026-10-20 第九版起**不再使用**：轮次归属本身就是按审核时间卡的，
|
||||
* 「审核晚于 13:00 的单」根本进不了 13:00 轮，会自然落到 18:00 轮，
|
||||
* 不需要额外顺延。函数保留是因为「按下一轮核验时刻算」这个业务表述
|
||||
* 未来若用于别的口径（例如按创建时间分轮），逻辑还是这一套。
|
||||
*
|
||||
* @param {object} round resolveActiveRound / describeRounds 的返回项（需带 date/key）
|
||||
* @returns {string} 'YYYY-MM-DD HH:mm:00'
|
||||
*/
|
||||
function nextRoundDeadline(round) {
|
||||
const idx = ROUNDS.findIndex((r) => r.key === round.key);
|
||||
if (idx >= 0 && idx + 1 < ROUNDS.length) {
|
||||
return `${round.date} ${pad2(ROUNDS[idx + 1].verifyHour)}:00:00`;
|
||||
}
|
||||
// 当天最后一轮 → 次日首轮
|
||||
const [y, m, d] = String(round.date).split('-').map(Number);
|
||||
const next = new Date(y, (m || 1) - 1, (d || 1) + 1);
|
||||
return `${next.getFullYear()}-${pad2(next.getMonth() + 1)}-${pad2(next.getDate())}`
|
||||
+ ` ${pad2(ROUNDS[0].verifyHour)}:00:00`;
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
CENTERS,
|
||||
ROUNDS,
|
||||
HISTORY_LOOKBACK_DAYS,
|
||||
EXCLUDED_WAREHOUSE_KEYWORDS,
|
||||
resolveCenter,
|
||||
centerWindowEndHour,
|
||||
centerWindowEnd,
|
||||
nextRoundDeadline,
|
||||
loadCenterWarehouseMap,
|
||||
clearWarehouseCache,
|
||||
getWarehouseCache: () => warehouseCache,
|
||||
resolveActiveRound,
|
||||
describeRounds,
|
||||
beijingNow,
|
||||
BEIJING_OFFSET_MINUTES,
|
||||
EXCLUDED_STATUS_SQL,
|
||||
SHIPPED_STATUS,
|
||||
PENDING_STATUS_SQL,
|
||||
NOT_SPLIT_MERGED_SQL,
|
||||
OUTBOUND_TABLES,
|
||||
ORDER_STATE_TABLE,
|
||||
SHIPPING_STATUS,
|
||||
UNAUDITED_STATUS,
|
||||
ABNORMAL_STATUS,
|
||||
IGNORED_STATES,
|
||||
CREATED_SOURCE_TABLES,
|
||||
CREATED_BACKFILL_BATCH,
|
||||
VOID_ORDER_STATUS,
|
||||
SHIP_TIMELINESS_HOURS,
|
||||
toNumber,
|
||||
};
|
||||
@ -1,775 +0,0 @@
|
||||
'use strict';
|
||||
|
||||
/**
|
||||
* 仓储中心 24 小时发货时效 —— 服务层
|
||||
*
|
||||
* ═══════════════════════════════════════════════════════════════════════════
|
||||
* 口径（2026-10-20 第九次修正，业务最终定版）
|
||||
* ═══════════════════════════════════════════════════════════════════════════
|
||||
* 业务原话（按时间顺序，最后一条为准）：
|
||||
* 17:12「当日 7 点前订单（7 点前订单**按照审核时间算**），13:00 核验未发就算超时」
|
||||
* 17:5x「当天 6:30 到 7 点审核的订单 13:00 核验；当天 7 点到 16 点审核的订单 18:00 核验；
|
||||
* 然后再看历史未发的订单」
|
||||
*
|
||||
* ⟹ 三条铁律：
|
||||
* ① **轮次归属看「审核时间」**（`last_oa_confirm_time`，聚水潭显示值）：
|
||||
* 今天 00:00~07:00 审核 → 13:00 轮
|
||||
* **截止今天 16:00 前审核**的单 → 18:00 轮
|
||||
* （业务 2026-10-20 补正：18:00 核验的是 16:00 前**所有**审核过的单，
|
||||
* 不是「今天 00:00~16:00」这一个自然日切片 —— 含今天之前审核、
|
||||
* 至今没发的历史未发单，也含 7 点前审核到 13:00 还没发出的；
|
||||
* 山东两仓 15:00、河南洛宁 13:00 是仓级例外，见 registry）
|
||||
* ⚠️ **不看创建时间**：业务亲自指出的 9818476（创建 10-18 12:49 / 审核 10-20 13:06）
|
||||
* 和 9823980（创建 10-18 20:40 / 审核 10-20 09:15）都是下午/上午才审的，
|
||||
* 按创建时间会被错算进 13:00 轮 —— 第八版就是这么错的。
|
||||
* ② **历史未发的单一律算**：昨天及更早审核、至今没发货的，两个轮次都要看到
|
||||
* （它们早就该发了，不该等今天的分段窗口）。
|
||||
* ③ **没有「满 24 小时」门槛**：到核验时刻仍未发就是超时，哪怕只等了 2 小时。
|
||||
* 第七版加了 24h 门槛，13:00 轮永远看不到当天那批，被业务打回。
|
||||
* ④ **自提 / 中铁 / 壹米滴答 三个快递不考核**（业务 2026-10-20 补充）：
|
||||
* 按 `logistic_company_name` 包含匹配（库里是「中铁物流」「壹米滴答专线」），
|
||||
* 命中直接跳过，不进出口径任何一处数字，剔除量记在 `summary.carrierSkipped`。
|
||||
*
|
||||
* 已等时长 = **审核时间 → 本轮核验时刻**（13:00 / 18:00）。
|
||||
* 🔥 审核时间取 last_oa_confirm_time（**最后一次**审核）——
|
||||
* 这就是聚水潭订单列表「审核时间」那一列显示的值，业务拿它对账。
|
||||
* 之前取首次审核，业务抽查 3 单（5127368691073091434 等）立刻发现不一致：
|
||||
* 首次 10-18 13:15 vs 聚水潭 10-20 13:38。**别再改成 first_oa**。
|
||||
* 因为窗口也按审核时间卡，「审核 13:06 的单」只会进 18:00 轮，
|
||||
* 已等自然用 18:00 算，不会出现「0 分」。
|
||||
* 明细列表并列「审核时间 / 发货时间」—— 业务 2026-10-20 要求**去掉创建时间**，
|
||||
* 改成看各订单的发货时间（未发的显示「未发货」），对账时直接和聚水潭发货时间比。
|
||||
*
|
||||
* 🔥 「已发 / 未发」还是以聚水潭「销售订单」的发货状态为准（= 状态表 send_time）。
|
||||
* **不要**改用运单号（logistic_id）判已发：实测同一店铺里，
|
||||
* 「已发货」的单独有运单号 + 未揽收，「发货中」的单也有运单号 + 未揽收 —— 判不出来。
|
||||
* 运单号只用来在明细里标「已打单 · 未揽收」，给业务一个「仓库干到哪一步」的线索。
|
||||
*
|
||||
* 数据源：`rpt.jst_order_express_details`（聚水潭订单状态准实时镜像，402 万行）
|
||||
*
|
||||
* 🔥 时区（2026-10-21 生产实测踩坑，别再裸用 `new Date()`）：
|
||||
* · 生产容器 `/etc/timezone = Etc/UTC`，而 MSSQL `GETDATE()` 返回**北京时间**，
|
||||
* mssql 驱动 `useUTC:false` 把 DB 值构造成「墙钟当 UTC」的 Date ⇒ 比真实 now 快 8 小时。
|
||||
* · 后果：**北京时间每天 00:00~08:00，服务端取到的「今天」是昨天**，
|
||||
* 轮次日期 / 核验窗口整体错位（实测 08:04 跑 13:00 轮得 3895 单，本地仅 6 单）。
|
||||
* · 统一用 `registry.beijingNow()` 取「现在」（本机已是东八区时平移量为 0，行为不变）。
|
||||
* **不要**去改容器 TZ —— 会波及全部既有定时任务。
|
||||
*
|
||||
* · 窗口归属 / 时长基准 = `last_oa_confirm_time`（最后一次审核 = 聚水潭显示值；
|
||||
* 缺失回退 first_oa / 创建时间 / 付款时间），来源写进 `benchmarkSource`。
|
||||
* · 创建时间（**仅供展示对账**） = `jst_Orders.created` / `jst_qmcust_orderlist.created`
|
||||
* 🔥 状态表里**没有**这一列，必须回订单表按 `o_id = inner_order_id` 补：
|
||||
* · `createdAt`（状态表那个 datetime2）= 同步落库时间，晚 1.5~3.5h，**不能用**
|
||||
* · `created` 才是聚水潭订单列表里的「创建时间」（比下单晚 15~30 秒）
|
||||
* · 已发货 = `send_time` 非空（已发货单 100% 有值）
|
||||
* · 待发货 = `send_time` 为空 且 `order_status_name = 发货中`
|
||||
* · 仓库 = `warehouse_name`（直接套 CENTERS 关键词归属主仓）
|
||||
*
|
||||
* ── 为什么弃用 jst_Orders.status（前三版全栽在这）──────────────────────────
|
||||
* 订单表的 `status` 是**下单那一刻的快照**，之后聚水潭侧取消、发货前售后、
|
||||
* 审核通过都不会回写。实测（2026-10-20）业务反馈「聚水潭查不到」的 6 单：
|
||||
* 订单表 status 全是 `WaitConfirm`（看起来像待发货），
|
||||
* 状态表真实状态是 **已取消**（标签带「发货前售后」），另 1 单是 **异常**。
|
||||
* ⟹ 所以「状态 / 是否已发」一律以状态表为准，**订单表只用来补创建时间**。
|
||||
*
|
||||
* 时间列语义（已逐一实测，别再猜）：
|
||||
* · `order_date` / `pay_date` —— 平台下单 / 付款时间（客户那边的时间）
|
||||
* · `created`（订单表） —— ✅ **聚水潭创建时间**（展示用，比下单晚 15~30 秒）
|
||||
* · `createTime`/`updateTime` —— 数仓灌库时间（带毫秒、批量、滞后约 5 分钟）
|
||||
* · `modified` —— ⚠️ 最后修改时间，每天凌晨被批量刷新，不可用
|
||||
* · `first_oa_confirm_time` —— 首次审单时间（审核时间缺失时的第二顺位回退）
|
||||
* · `last_oa_confirm_time` —— ✅ **最新审核时间（本版考核基准）**
|
||||
* · `send_time` —— **发货时间**
|
||||
* · `query_time` —— 本表快照时间（判数据新鲜度）
|
||||
*
|
||||
* ── 三态分流（互斥）─────────────────────────────────────────────────────
|
||||
* 超时未发货 = 发货中 + send_time 空 + 审核时间已过本轮窗口上界（07:00/16:00）
|
||||
* → orders（考核仓库）
|
||||
* 不计考核 = 已支付待审核（没审单）/ 异常（订单异常） → heldOrders
|
||||
* 不展示 = 已发货 / 已取消（作废）/ 等供销商|外仓发货 → 直接丢弃
|
||||
* 🔥 作废单（已取消）不考核：近 30 天 64,440 单，是「发货中」2,448 单的 26 倍，
|
||||
* 不排除的话整页都是客户取消掉的单。
|
||||
*
|
||||
* ── 核验轮次（业务给定）──────────────────────────────────────────────────
|
||||
* `verifyHour` —— 几点核验（13:00 / 18:00），判「超时多久」用它
|
||||
* `windowEndHour` —— 只看该时刻**前审核**的单（07:00 / 16:00，仓级例外见 registry）
|
||||
* ⚠️ 两者不是同一个东西，别合成一个字段
|
||||
* ⚠️ 也**不要**再引入「满 N 小时才算超时」的门槛（第七版踩过，会被业务打回）
|
||||
* ⚠️ 窗口**要**卡审核时间（第九版定版）。第六版曾因「卡审核时间 13:00 轮只剩 2 单」
|
||||
* 退回创建时间，结果 9818476 / 9823980 这类下午才审的单被错算进 13:00 轮 →
|
||||
* 业务亲自纠正：「7 点前订单**按照审核时间算**」。审核时间少是因为 13:00 轮本来就
|
||||
* 只该有早上那批，不是数据不对。
|
||||
*
|
||||
* ── 性能（2026-10-20 实测，四个坑都踩过）──────────────────────────────────
|
||||
* ① **不要 SELECT 宽列**。同一 WHERE 只取 2 列 0.7s，取 15 列（含
|
||||
* `order_labels` / `buyer_message` / `remark`）**54s** —— 视图没法做
|
||||
* 覆盖扫描，多取一列就是几万次基表回表。本表只投影 10 个窄列。
|
||||
* ② **不要回订单表补金额**。`o_id IN (400 个)` 打两张订单宽视图，单条实测
|
||||
* **38.7s**。发货时效不需要金额，直接不做。
|
||||
* （但补 `created` **可以**：只取两列时 9,676 个候选只要 14.5s + 2.9s。）
|
||||
* ③ **不要额外查新鲜度**。`MAX(send_time)` 又是一次 402 万行扫描（21.1s）。
|
||||
* 快照时间直接从主查询的 `query_time` 在 Node 里取 MAX。
|
||||
* ④ `SELECT *` 更是灾难 —— 单 form 单号查一次 **5 分钟**不返回。
|
||||
* ⑤ 走 `querySlow`，普通池 60s 池级超时 + 自动重试会把 9s 拖成 120s。
|
||||
*
|
||||
* ── 时区 ─────────────────────────────────────────────────────────────────
|
||||
* 所有时间列都是**东八区本地时间**；服务与库都在东八区。
|
||||
* **不要**在 Node 侧用 UTC 日期判断。
|
||||
*/
|
||||
|
||||
const cloudDatabase = require('../config/cloudDatabase');
|
||||
const registry = require('./warehouseShipTimelinessRegistry');
|
||||
|
||||
const {
|
||||
ORDER_STATE_TABLE,
|
||||
SHIPPING_STATUS,
|
||||
UNAUDITED_STATUS,
|
||||
ABNORMAL_STATUS,
|
||||
IGNORED_STATES,
|
||||
CREATED_SOURCE_TABLES,
|
||||
CREATED_BACKFILL_BATCH,
|
||||
VOID_ORDER_STATUS,
|
||||
resolveCenter,
|
||||
} = registry;
|
||||
|
||||
// 明细上限：只用于页面展示，超出部分用 truncated 标记提示
|
||||
const DEFAULT_DETAIL_LIMIT = 500;
|
||||
const MAX_DETAIL_LIMIT = 2000;
|
||||
|
||||
// 状态表快照超过这个分钟数没刷新 → 页面提示「数据滞后」。
|
||||
// 正常 ETL 每小时至少刷一轮（每小时约 1000 行有变化），90 分钟足够容错。
|
||||
const STATE_STALE_MINUTES = 90;
|
||||
|
||||
/**
|
||||
* 不参与发货时效考核的快递（业务 2026-10-20 指定）：
|
||||
* 自提 —— 客户自己来拉，仓库不负责派送
|
||||
* 中铁 —— 中铁物流（大件专线）
|
||||
* 壹米滴答 —— 专线物流（大件）
|
||||
* 命中即可，用**物流公司名**包含匹配；库里的实际值是「中铁物流」「壹米滴答专线」这种。
|
||||
* 只影响「超时未发」判定，不影响「已发」判定。
|
||||
*/
|
||||
const EXCLUDED_CARRIERS = ['自提', '中铁', '壹米滴答'];
|
||||
|
||||
/**
|
||||
* 订单表（= 聚水潭「销售订单」镜像）里「已发货」的状态值。
|
||||
*
|
||||
* 🔥 业务 2026-10-20 要求「已发/未发参考聚水潭销售订单页面」——
|
||||
* 销售订单页面显示「已发货」= status `Sent`。`send_date` 很多店铺不回写
|
||||
* （实测 103 单里 103 单都是空），所以必须把 status 也当依据。
|
||||
* ⚠️ **不要**把 `Delivering`（发货中）算成已发 —— 那是「已审核待出库」，
|
||||
* 正是本页要考核的对象；算进来整页就空了。
|
||||
*/
|
||||
const ORDER_SHIPPED_STATUS = ['Sent'];
|
||||
|
||||
/**
|
||||
* 结果缓存。
|
||||
*
|
||||
* 这张视图单次查询实测 10~60 秒（取决于缓存温度与库负载），页面又是
|
||||
* `AUTO_REFRESH_MS` 定时轮询 —— 不缓存的话每轮轮询都会重压一次库，
|
||||
* 页面也会一直转圈。缓存 key 含「轮次 + 日期 + limit」，
|
||||
* 业务点「刷新」时前端带 `force=1` 绕过缓存强制重查。
|
||||
*/
|
||||
const CACHE_TTL_MS = Number(process.env.CANGKU_WST_CACHE_TTL_MS) || 5 * 60 * 1000;
|
||||
let resultCache = { key: '', at: 0, data: null };
|
||||
|
||||
/** 清缓存（切轮次 / 手工排查时用） */
|
||||
function clearShipTimelinessCache() {
|
||||
resultCache = { key: '', at: 0, data: null };
|
||||
}
|
||||
|
||||
/** 把 datetime / Date / 字符串统一成 'YYYY-MM-DD HH:mm:ss'（东八区，不做时区换算） */
|
||||
function formatDateTime(value) {
|
||||
if (!value) return '';
|
||||
if (value instanceof Date) {
|
||||
if (Number.isNaN(value.getTime())) return '';
|
||||
const p = (n) => String(n).padStart(2, '0');
|
||||
return `${value.getFullYear()}-${p(value.getMonth() + 1)}-${p(value.getDate())}`
|
||||
+ ` ${p(value.getHours())}:${p(value.getMinutes())}:${p(value.getSeconds())}`;
|
||||
}
|
||||
const s = String(value);
|
||||
if (!s) return '';
|
||||
return s.replace('T', ' ').replace(/\.\d+Z?$/, '').slice(0, 19);
|
||||
}
|
||||
|
||||
/** 两个时间文本相差多少分钟（to - from）；任一为空返回 0 */
|
||||
function diffMinutes(fromText, toText) {
|
||||
const a = formatDateTime(fromText);
|
||||
const b = formatDateTime(toText);
|
||||
if (!a || !b) return 0;
|
||||
const pa = new Date(a.replace(' ', 'T')).getTime();
|
||||
const pb = new Date(b.replace(' ', 'T')).getTime();
|
||||
if (!Number.isFinite(pa) || !Number.isFinite(pb)) return 0;
|
||||
return Math.floor((pb - pa) / 60000);
|
||||
}
|
||||
|
||||
/**
|
||||
* 取「聚水潭订单状态」里所有未发货的单（发货中 / 待审核 / 异常）。
|
||||
*
|
||||
* 为什么不用 wms_co_id 过滤：本表只有 `warehouse_name`，没有仓 ID。
|
||||
* 近 30 天三类合计约 1 万行，一次取回在 Node 侧按仓库名归属主仓，代价可接受。
|
||||
*
|
||||
* ⚠️ 只投影 11 个**窄列**：`order_labels`/`buyer_message`/`remark` 这类长文本
|
||||
* 会把 0.7s 的查询拖到 54s（视图无法覆盖扫描，每行都要回基表）。
|
||||
* ⚠️ `send_time IS NULL` 是关键：已发货单在这里 100% 有值。
|
||||
*
|
||||
* 🔥 2026-10-20 第八版：**不再把「创建 ≤ 核验−24h」下推到 SQL**。
|
||||
* 本版口径是「到核验时刻未发即超时」，`send_time IS NULL` 就是候选；
|
||||
* 窗口上界改在 Node 侧按**审核时间**判。SQL 里那两个时间列只是用来
|
||||
* 判断窗口归属，不再参与「等了多少小时」的门槛。
|
||||
*/
|
||||
async function loadPendingStates(round) {
|
||||
const rows = await cloudDatabase.querySlow(
|
||||
// 🔥 时间列直接取原始 datetime，**不要**在 SQL 里 CONVERT 成字符串：
|
||||
// CONVERT 会作用到扫描到的每一行（谓词下推不到视图里），实测把点查拖到 40s+；
|
||||
// mssql 连接已配 useUTC:false，Node 侧 formatDateTime 用本地 getter 还原
|
||||
// 就是库里存的北京时间，不会偏移 8 小时。
|
||||
`SELECT e.so_id, e.inner_order_id, e.shop_name, e.warehouse_name,
|
||||
e.order_status_name, e.logistic_status_name,
|
||||
e.logistic_id, e.logistic_company_name,
|
||||
e.pay_time, e.first_oa_confirm_time, e.last_oa_confirm_time,
|
||||
e.send_time, e.query_time
|
||||
FROM dbo.${ORDER_STATE_TABLE} e
|
||||
WHERE e.send_time IS NULL
|
||||
AND e.pay_time >= @windowStart
|
||||
AND e.order_status_name IN (@shipStatus, @st1, @st2)`,
|
||||
{
|
||||
shipStatus: SHIPPING_STATUS,
|
||||
st1: UNAUDITED_STATUS,
|
||||
st2: ABNORMAL_STATUS,
|
||||
windowStart: round.windowStart,
|
||||
},
|
||||
// 视图谓词下推一般，给足超时；不走普通池（60s 池级超时 + 自动重试会把 9s 拖成 120s）
|
||||
{ connectRequestTimeoutMs: 300000 }
|
||||
);
|
||||
return rows || [];
|
||||
}
|
||||
|
||||
/** 并发跑任务，最多 `limit` 个同时在飞（不把连接池打满） */
|
||||
async function mapLimit(items, limit, worker) {
|
||||
const out = [];
|
||||
let cursor = 0;
|
||||
const runners = Array.from({ length: Math.min(limit, items.length) }, async () => {
|
||||
for (;;) {
|
||||
const i = cursor;
|
||||
cursor += 1;
|
||||
if (i >= items.length) return;
|
||||
out[i] = await worker(items[i], i);
|
||||
}
|
||||
});
|
||||
await Promise.all(runners);
|
||||
return out;
|
||||
}
|
||||
|
||||
/**
|
||||
* 回订单表补「起算点 + 作废事实」。
|
||||
*
|
||||
* 状态表 `jst_order_express_details` 里没有聚水潭创建时间（`createdAt` 是同步落库
|
||||
* 时间，比付款晚 1.5~3.5 小时），只能回两张订单表按 `o_id = inner_order_id` 取
|
||||
* `created`（稳定比下单晚 15~30 秒，即聚水潭订单列表里的「创建时间」）。
|
||||
*
|
||||
* 🔥 同一趟把**作废事实**也取回来（业务 2026-10-20 反馈作废单被算成超时）：
|
||||
* 状态表的 `send_time` 对**被合并单 / 拆单父单不回写** —— 单子早随主单发走了，
|
||||
* 状态表却还是「发货中 + send_time 空」。所以必须再看订单表的
|
||||
* `status` / `send_date` / `is_merge` / `is_split`（见 registry.VOID_ORDER_STATUS）。
|
||||
*
|
||||
* ⚠️ 只投影这 6 个**窄列**。实测 9,676 个候选：窄列 14.5s + 2.9s，
|
||||
* 一旦连 pay_amount / labels 一起取，单批 400 个就要 38.7s。
|
||||
*
|
||||
* @param {number[]} oids 内部单号
|
||||
* @returns {Promise<Map<number, {createdAt:string, status:string, sendDate:string, void:boolean, shipped:boolean}>>}
|
||||
*/
|
||||
async function backfillOrderFacts(oids) {
|
||||
const map = new Map();
|
||||
if (!oids.length) return map;
|
||||
|
||||
let remaining = oids;
|
||||
for (const table of CREATED_SOURCE_TABLES) {
|
||||
if (!remaining.length) break;
|
||||
const batches = [];
|
||||
for (let i = 0; i < remaining.length; i += CREATED_BACKFILL_BATCH) {
|
||||
batches.push(remaining.slice(i, i + CREATED_BACKFILL_BATCH));
|
||||
}
|
||||
|
||||
const results = await mapLimit(batches, 4, async (batch) => {
|
||||
try {
|
||||
return await cloudDatabase.querySlow(
|
||||
`SELECT o_id, created, status, send_date, is_merge, is_split
|
||||
FROM dbo.${table} WHERE o_id IN (${batch.join(',')})`,
|
||||
{},
|
||||
{ connectRequestTimeoutMs: 300000 }
|
||||
);
|
||||
} catch (e) {
|
||||
// 补不到不致命：调用方会回退到付款时间，不整页失败
|
||||
return [];
|
||||
}
|
||||
});
|
||||
|
||||
for (const rows of results) {
|
||||
for (const r of rows || []) {
|
||||
const id = Number(r.o_id);
|
||||
if (!Number.isFinite(id)) continue;
|
||||
const status = String(r.status || '');
|
||||
const sendDate = formatDateTime(r.send_date);
|
||||
map.set(id, {
|
||||
createdAt: formatDateTime(r.created),
|
||||
status,
|
||||
sendDate,
|
||||
// 作废：被合并 / 被拆分 / 已取消 —— 这单不会自己发货
|
||||
void: VOID_ORDER_STATUS.includes(status)
|
||||
|| Number(r.is_merge) === 1
|
||||
|| Number(r.is_split) === 1,
|
||||
// 已发：订单表有发货时间，**或**销售订单状态已是「已发货」(Sent)。
|
||||
// 业务 2026-10-20 口径：以聚水潭「销售订单」页面显示的发货状态为准。
|
||||
shipped: !!sendDate || ORDER_SHIPPED_STATUS.includes(status),
|
||||
});
|
||||
}
|
||||
}
|
||||
remaining = remaining.filter((n) => !map.has(n));
|
||||
}
|
||||
return map;
|
||||
}
|
||||
|
||||
function emptySummary() {
|
||||
return {
|
||||
// 超时未发货（考核仓库的部分）
|
||||
overdueUnshipped: 0,
|
||||
overdueCenterCount: 0,
|
||||
oldestDays: 0,
|
||||
// 不计考核（待审核 + 异常）—— 单独统计，不算仓库责任
|
||||
heldCount: 0,
|
||||
// 已剔除的作废 / 已发单（页面只作说明，不进考核）
|
||||
voidCount: 0,
|
||||
// 已剔除的「不考核快递」单量（自提 / 中铁 / 壹米滴答）
|
||||
carrierSkipped: 0,
|
||||
};
|
||||
}
|
||||
|
||||
function buildEmptyCenters(centerList) {
|
||||
return centerList.map((c) => ({
|
||||
key: c.key,
|
||||
name: c.name,
|
||||
placeholder: c.placeholder,
|
||||
warehouseCount: c.warehouses.length,
|
||||
warehouses: c.warehouses.map((w) => ({ wmsCoId: w.wmsCoId, name: w.name })),
|
||||
overdueUnshipped: 0,
|
||||
oldestDays: 0,
|
||||
heldCount: 0,
|
||||
}));
|
||||
}
|
||||
|
||||
async function getShipTimeliness(options = {}) {
|
||||
// 🔥 必须按北京时间取「现在」：生产容器是 UTC，而库里时间是北京时间，
|
||||
// 裸 new Date() 会让北京时间 00:00~08:00 取到前一天（2026-10-21 实测）
|
||||
const now = options.now instanceof Date ? options.now : registry.beijingNow();
|
||||
const limit = Math.min(
|
||||
Math.max(Number(options.limit) || DEFAULT_DETAIL_LIMIT, 1),
|
||||
MAX_DETAIL_LIMIT
|
||||
);
|
||||
|
||||
// ① 主仓清单（用于展示「含子仓 N 个」；归属判定走 warehouse_name 关键词）
|
||||
const centerList = await registry.loadCenterWarehouseMap();
|
||||
const pad2 = (n) => String(n).padStart(2, '0');
|
||||
|
||||
// ② 决定本轮截止时刻
|
||||
const rounds = registry.describeRounds(now);
|
||||
let round = null;
|
||||
if (options.round) {
|
||||
const target = registry.ROUNDS.find((r) => r.key === String(options.round).toUpperCase());
|
||||
if (!target) {
|
||||
const err = new Error(`未知的核验轮次: ${options.round}`);
|
||||
err.statusCode = 400;
|
||||
throw err;
|
||||
}
|
||||
round = rounds.find((r) => r.key === target.key);
|
||||
if (!round) {
|
||||
const err = new Error(`无法构造核验窗口: ${options.round}`);
|
||||
err.statusCode = 500;
|
||||
throw err;
|
||||
}
|
||||
} else {
|
||||
round = registry.resolveActiveRound(now);
|
||||
}
|
||||
|
||||
// 🔥 13:00 前没有轮次生效（业务口径）：直接返回「未到核验时间」，不查库
|
||||
if (!round) {
|
||||
const nextRound = rounds.find((r) => !r.active) || rounds[0];
|
||||
return {
|
||||
generatedAt: formatDateTime(now),
|
||||
date: `${now.getFullYear()}-${pad2(now.getMonth() + 1)}-${pad2(now.getDate())}`,
|
||||
round: null,
|
||||
notStarted: true,
|
||||
isPreviousDay: false,
|
||||
rounds,
|
||||
nextRoundAt: nextRound ? nextRound.deadline : '',
|
||||
nextWindowEnd: nextRound ? nextRound.windowEnd : '',
|
||||
deadline: '',
|
||||
window: null,
|
||||
summary: emptySummary(),
|
||||
centers: buildEmptyCenters(centerList),
|
||||
orders: [],
|
||||
heldOrders: [],
|
||||
truncated: false,
|
||||
detailLimit: limit,
|
||||
detailDegraded: false,
|
||||
freshness: null,
|
||||
note: `今日 ${pad2(rounds[0].verifyHour)}:00 首轮核验开始后才展示超时数据`,
|
||||
};
|
||||
}
|
||||
|
||||
// ③ 取「未发货」全量（发货中 / 待审核 / 异常），Node 侧判主仓与超时
|
||||
// 先看缓存：同一轮次 + 同一天 + 同一 limit，5 分钟内直接复用
|
||||
const force = options.force === true
|
||||
|| ['1', 'true', 'yes'].includes(String(options.force || '').toLowerCase());
|
||||
const cacheKey = `${round.key}|${round.date}|${limit}`;
|
||||
if (!force && resultCache.data && resultCache.key === cacheKey
|
||||
&& Date.now() - resultCache.at < CACHE_TTL_MS) {
|
||||
return {
|
||||
...resultCache.data,
|
||||
cached: true,
|
||||
cacheAgeSec: Math.round((Date.now() - resultCache.at) / 1000),
|
||||
};
|
||||
}
|
||||
|
||||
let stateRows = [];
|
||||
try {
|
||||
stateRows = await loadPendingStates(round);
|
||||
} catch (e) {
|
||||
const err = new Error(`聚水潭订单状态表查询失败：${e.message}`);
|
||||
err.statusCode = 502;
|
||||
throw err;
|
||||
}
|
||||
|
||||
// ③-b 补起算点「聚水潭创建时间」+ 作废事实（状态表两样都没有，回订单表取）
|
||||
const oids = [...new Set(
|
||||
stateRows.map((r) => Number(r.inner_order_id)).filter((n) => Number.isFinite(n))
|
||||
)];
|
||||
const orderFacts = await backfillOrderFacts(oids);
|
||||
// 被剔除的作废 / 已发单计数（只用于页面说明，不进考核）
|
||||
let voidCount = 0;
|
||||
// 因「不考核快递」被跳过的单量（自提 / 中铁 / 壹米滴答），写进 summary 便于对账
|
||||
let carrierSkipped = 0;
|
||||
|
||||
// ④ 分桶
|
||||
const acc = new Map(centerList.map((c) => [c.key, {
|
||||
pendingCount: 0,
|
||||
oldestDays: 0,
|
||||
heldCount: 0,
|
||||
}]));
|
||||
|
||||
const pendingRows = [];
|
||||
const heldRows = [];
|
||||
const seenSo = new Set();
|
||||
let snapshotAt = '';
|
||||
|
||||
for (const row of stateRows) {
|
||||
// 快照时间：状态表最后一次刷新（顺带算，不再单独扫一遍 402 万行表）
|
||||
const qt = formatDateTime(row.query_time);
|
||||
if (qt > snapshotAt) snapshotAt = qt;
|
||||
|
||||
const center = resolveCenter(row.warehouse_name);
|
||||
if (!center) continue; // 非 11 主仓（代发仓/未指定仓/POP 仓…）
|
||||
const bucket = acc.get(center.key);
|
||||
if (!bucket) continue;
|
||||
|
||||
const state = String(row.order_status_name || '');
|
||||
// 🔥 作废单不考核 —— 业务 2026-10-20 明确「作废订单不用考核」。
|
||||
// 状态表的 send_time 对**被合并单 / 拆单父单不回写**（案例 5127276315127080023：
|
||||
// 状态表「发货中 + send_time 空」，订单表却是 Merged 且 send_date 有值、
|
||||
// 出库单也早就生成了），所以必须回订单表再判一次，光信状态表会被冤枉。
|
||||
const fact = orderFacts.get(Number(row.inner_order_id));
|
||||
if (fact && (fact.void || fact.shipped)) {
|
||||
voidCount += 1;
|
||||
continue;
|
||||
}
|
||||
|
||||
// SQL 里已经用状态白名单排除，这里再兜一次，防止以后有人改白名单漏掉
|
||||
if (IGNORED_STATES.includes(state)) continue;
|
||||
|
||||
// 🔥 不考核的快递（业务 2026-10-20）：自提 / 中铁 / 壹米滴答 ——
|
||||
// 走这三种运输方式的单不按仓储发货时效考核（自提客户自己来拉、
|
||||
// 中铁和壹米滴答是专线/大件物流，揽收与在途都不受仓库控制）。
|
||||
// 用**物流公司名**模糊匹配（库里的名字是「中铁物流」「壹米滴答专线」这种）。
|
||||
const carrier = String(row.logistic_company_name || '').trim();
|
||||
const hitCarrier = EXCLUDED_CARRIERS.find((k) => carrier.includes(k));
|
||||
if (hitCarrier) {
|
||||
carrierSkipped += 1;
|
||||
continue;
|
||||
}
|
||||
|
||||
// ── 窗口归属 = **审核时间**（业务 2026-10-20 最终定版，两次纠偏后的结论）────
|
||||
// 业务原话：「当日 7 点前订单（7 点前订单**按照审核时间算**）……」
|
||||
// 实测案例（业务亲自指出的两单）：
|
||||
// · 9818476：创建 10-18 12:49，但**审核 10-20 13:06** → 不是 7 点前的单，13:00 轮不能出现
|
||||
// · 9823980：创建 10-18 20:40，**审核 10-20 09:15** → 同理，归 18:00 轮
|
||||
// ⟹ 「7 点前/16 点前」卡的是**审核时间**：审核 ≤ 07:00 归 13:00 轮，
|
||||
// 审核 ≤ 16:00 归 18:00 轮（山东两仓 15:00、河南洛宁 13:00，见 registry）。
|
||||
// ⚠️ 别看创建时间：客户凌晨下单、仓库上午才审的单，按创建时间会提前算超时。
|
||||
// ⚠️ 审核时间取**最后一次**（last_oa），见下面 458 行开始的说明。
|
||||
const createdAt = fact ? fact.createdAt : '';
|
||||
const payAt = formatDateTime(row.pay_time);
|
||||
const auditFirst = formatDateTime(row.first_oa_confirm_time);
|
||||
const auditLast = formatDateTime(row.last_oa_confirm_time);
|
||||
// 🔥 取**最后一次**审核（= 聚水潭订单列表里「审核时间」那一列显示的值）。
|
||||
// 业务 2026-10-20 20:0x 抽查 3 单指出「审核时间跟系统里的不一致」，
|
||||
// 根因就是我们之前取错了列（first_oa = 首次审核）：
|
||||
// 5127368691073091434 首次 10-18 13:15 / 聚水潭显示 10-20 13:38
|
||||
// 261019-670795046400872 首次 10-19 08:48 / 聚水潭显示 10-20 09:31
|
||||
// 261019-558387771763179 首次 10-19 11:21 / 聚水潭显示 10-20 09:11
|
||||
// ⟹ 页面必须跟聚水潭对齐，否则业务一对账就说「跑错了」。
|
||||
const auditAt = auditLast || auditFirst;
|
||||
const windowAt = auditAt || createdAt || payAt;
|
||||
const benchmarkAt = windowAt;
|
||||
const benchmarkSource = auditAt
|
||||
? (auditLast ? 'last_audit' : 'first_audit')
|
||||
: (createdAt ? 'created' : 'pay');
|
||||
|
||||
// 同一 so_id 可能因拆包出现多行（实测有），按 so_id + 窗口时间 去重
|
||||
const dedupeKey = `${row.so_id}|${windowAt}`;
|
||||
if (seenSo.has(dedupeKey)) continue;
|
||||
seenSo.add(dedupeKey);
|
||||
|
||||
// ── 本轮核验范围（业务 2026-10-20 最终定版）────────────────────────────
|
||||
// ① **今天的单按审核时间分段**：
|
||||
// 今天 00:00 ~ 07:00 审核 → 13:00 轮核验
|
||||
// **截止今天 16:00 前审核**的单 → 18:00 轮核验
|
||||
// （= 16:00 前所有审核过的单，含 7 点前没发出的；不是「07:00~16:00」那一段。
|
||||
// 山东两仓 15:00、河南洛宁 13:00 为仓级例外）
|
||||
// ⟹ 今天 09:15 审核的单（9823980）、13:06 审核的单（9818476）
|
||||
// **不进 13:00 轮**，只在 18:00 轮出现（业务亲自指出的两单）
|
||||
// ② **历史未发的单一律算**（昨天及更早审核、至今没发货）—— 它们已经超时，
|
||||
// 两个轮次都该看到，不受「今天 00:00 起」的限制。
|
||||
// ③ 30 天护栏只为查询性能，不是业务边界。
|
||||
const windowEndAt = registry.centerWindowEnd(center.key, round);
|
||||
const todayStart = `${round.date} 00:00:00`;
|
||||
if (windowAt && windowAt < round.windowStart) continue; // 超出 30 天护栏
|
||||
if (windowAt && windowAt >= todayStart && windowAt > windowEndAt) continue;
|
||||
|
||||
const base = {
|
||||
row,
|
||||
center,
|
||||
state,
|
||||
createdAt,
|
||||
payAt,
|
||||
auditAt,
|
||||
windowAt,
|
||||
benchmarkAt,
|
||||
benchmarkSource,
|
||||
warehouseName: String(row.warehouse_name || ''),
|
||||
};
|
||||
|
||||
// ── 不计考核：没审单（已支付待审核）或订单异常，都不该算仓库超时 ──────
|
||||
if (state === UNAUDITED_STATUS || state === ABNORMAL_STATUS) {
|
||||
bucket.heldCount += 1;
|
||||
heldRows.push({
|
||||
...base,
|
||||
holdReason: state === UNAUDITED_STATUS ? '待审核' : '订单异常',
|
||||
});
|
||||
continue;
|
||||
}
|
||||
|
||||
if (state !== SHIPPING_STATUS) continue; // 其余状态（已发货/已取消）不展示
|
||||
|
||||
// ── 超时判定：**到核验时刻仍未发货就是超时**（不再有「满 24 小时」门槛）
|
||||
if (!benchmarkAt) {
|
||||
bucket.heldCount += 1;
|
||||
heldRows.push({ ...base, holdReason: '缺审核时间' });
|
||||
continue;
|
||||
}
|
||||
// waited = 审核时间 → 本轮核验时刻（13:00 / 18:00）
|
||||
// ⚠️ 因为窗口本身按审核时间卡（审核 ≤ 07:00 / 16:00），benchmark 必然 ≤ deadline，
|
||||
// 这里不需要再处理「审核晚于核验」的情况 —— 那种单会自然落到下一轮：
|
||||
// 审核 13:06 的单进不了 13:00 轮（07:00 上界），只在 18:00 轮出现，已等 = 18:00 − 13:06。
|
||||
const waited = Math.max(0, diffMinutes(benchmarkAt, round.deadline));
|
||||
|
||||
bucket.pendingCount += 1;
|
||||
const days = Math.floor(waited / 1440);
|
||||
if (days > bucket.oldestDays) bucket.oldestDays = days;
|
||||
pendingRows.push({ ...base, waited });
|
||||
}
|
||||
|
||||
// ⑤ 排序：最久的排前面（业务一眼看最急的）
|
||||
pendingRows.sort((a, b) => {
|
||||
if (a.windowAt < b.windowAt) return -1;
|
||||
if (a.windowAt > b.windowAt) return 1;
|
||||
return 0;
|
||||
});
|
||||
heldRows.sort((a, b) => {
|
||||
const x = a.windowAt || '';
|
||||
const y = b.windowAt || '';
|
||||
if (x < y) return -1;
|
||||
if (x > y) return 1;
|
||||
return 0;
|
||||
});
|
||||
|
||||
const detailRows = pendingRows.slice(0, limit);
|
||||
const heldDetail = heldRows.slice(0, limit);
|
||||
|
||||
const orders = detailRows.map((x) => {
|
||||
const r = x.row;
|
||||
return {
|
||||
oId: String(r.inner_order_id || ''),
|
||||
soId: String(r.so_id || ''),
|
||||
shopName: String(r.shop_name || ''),
|
||||
// 创建时间 = 聚水潭订单创建时间（业务 2026-10-20 已从明细列去掉，仅保留字段做回退基准）
|
||||
createdAt: x.createdAt,
|
||||
// 发货时间：本列表只取 send_time IS NULL 的单，所以这里恒为空 → 前端显示「未发货」
|
||||
sendTime: formatDateTime(r.send_time),
|
||||
// 付款时间（并列展示，方便对账）
|
||||
payTime: x.payAt,
|
||||
// 审核时间 = **考核基准**：决定进 13:00 轮还是 18:00 轮，已等时长也从它算
|
||||
auditTime: x.auditAt,
|
||||
// 基准时间实际取值（审核缺失时回退创建/付款）+ 来源标记
|
||||
benchmarkTime: x.benchmarkAt,
|
||||
benchmarkSource: x.benchmarkSource,
|
||||
state: x.state,
|
||||
logisticStatus: String(r.logistic_status_name || ''),
|
||||
// 运单号 / 快递公司：有值说明仓库**已打单**（但还没揽收/回传发货时间）。
|
||||
// 业务 2026-10-20 报「聚水潭显示已发货、页面显示未发货」，靠这两列能一眼看出卡在哪一步。
|
||||
logisticId: String(r.logistic_id || '').trim(),
|
||||
logisticCompany: String(r.logistic_company_name || '').trim(),
|
||||
centerKey: x.center.key,
|
||||
centerName: x.center.name,
|
||||
warehouseName: x.warehouseName,
|
||||
// 已等时长（小时，保留 1 位）与分钟（排序都用分钟）
|
||||
waitedHours: Math.round((x.waited / 60) * 10) / 10,
|
||||
overdueMinutes: x.waited,
|
||||
};
|
||||
});
|
||||
|
||||
const heldOrders = heldDetail.map((x) => {
|
||||
const r = x.row;
|
||||
const from = x.benchmarkAt || '';
|
||||
return {
|
||||
oId: String(r.inner_order_id || ''),
|
||||
soId: String(r.so_id || ''),
|
||||
shopName: String(r.shop_name || ''),
|
||||
createdAt: x.createdAt,
|
||||
sendTime: formatDateTime(r.send_time),
|
||||
payTime: x.payAt,
|
||||
auditTime: x.auditAt,
|
||||
benchmarkTime: x.benchmarkAt,
|
||||
benchmarkSource: x.benchmarkSource,
|
||||
state: x.state,
|
||||
holdReason: x.holdReason,
|
||||
logisticStatus: String(r.logistic_status_name || ''),
|
||||
logisticId: String(r.logistic_id || '').trim(),
|
||||
logisticCompany: String(r.logistic_company_name || '').trim(),
|
||||
centerKey: x.center.key,
|
||||
centerName: x.center.name,
|
||||
warehouseName: x.warehouseName,
|
||||
heldDays: from ? Math.floor(diffMinutes(from, round.deadline) / 1440) : 0,
|
||||
};
|
||||
});
|
||||
|
||||
const centers = centerList.map((c) => {
|
||||
const b = acc.get(c.key) || { pendingCount: 0, oldestDays: 0, heldCount: 0 };
|
||||
return {
|
||||
key: c.key,
|
||||
name: c.name,
|
||||
placeholder: c.placeholder,
|
||||
warehouseCount: c.warehouses.length,
|
||||
warehouses: c.warehouses.map((w) => ({ wmsCoId: w.wmsCoId, name: w.name })),
|
||||
overdueUnshipped: b.pendingCount,
|
||||
oldestDays: b.oldestDays,
|
||||
heldCount: b.heldCount,
|
||||
// 该仓在本轮的窗口上界（可能是仓级例外，如山东两仓 15:00、河南洛宁 13:00）
|
||||
windowEnd: registry.centerWindowEnd(c.key, round),
|
||||
};
|
||||
});
|
||||
|
||||
// 本轮有「仓级例外窗口」的仓（给前端提示用；没有就是空数组）
|
||||
const windowOverrides = centerList
|
||||
.filter((c) => registry.centerWindowEndHour(c.key, round.key) !== null)
|
||||
.map((c) => ({
|
||||
key: c.key,
|
||||
name: c.name,
|
||||
hour: registry.centerWindowEndHour(c.key, round.key),
|
||||
windowEnd: registry.centerWindowEnd(c.key, round),
|
||||
}));
|
||||
|
||||
const summary = centers.reduce((a, c) => {
|
||||
a.overdueUnshipped += c.overdueUnshipped;
|
||||
if (c.overdueUnshipped > 0) a.overdueCenterCount += 1;
|
||||
if (c.oldestDays > a.oldestDays) a.oldestDays = c.oldestDays;
|
||||
a.heldCount += c.heldCount || 0;
|
||||
return a;
|
||||
}, emptySummary());
|
||||
summary.voidCount = voidCount;
|
||||
summary.carrierSkipped = carrierSkipped;
|
||||
|
||||
// 新鲜度：快照时间取自上面主查询的 query_time（不再额外扫一遍 402 万行表）
|
||||
// 🔥 2026-10-20 业务报「已发货的单还显示未发货」时才发现这里曾写死 stale:false ——
|
||||
// 状态表是**准实时镜像**，上游 ETL 一停（实测当天 15:48 之后 0 行刷新），
|
||||
// 15:48 之后发的货就永远进不来，页面只能基于旧快照判「未发」。
|
||||
// 必须把滞后暴露到页面上，否则业务只会以为判定写错。
|
||||
const snapshotAgeMin = snapshotAt ? diffMinutes(snapshotAt, formatDateTime(now)) : null;
|
||||
const stale = snapshotAgeMin != null && snapshotAgeMin > STATE_STALE_MINUTES;
|
||||
// 🔥 更狠的一条：快照**比本轮核验时刻还早** ⇒ 核验时刻那一刻的真实状态根本没看到。
|
||||
// 实测 2026-10-20 18:54：快照停在 15:48，18:00 核验时早已发出的单全被判「未发货」，
|
||||
// 业务连续报了 3 单都是这个原因。这种时候数字必然偏大，必须红字告警。
|
||||
const coversDeadline = !!snapshotAt && snapshotAt >= round.deadline;
|
||||
const freshness = {
|
||||
stateMaxQuery: snapshotAt,
|
||||
ageMinutes: snapshotAgeMin,
|
||||
stale,
|
||||
coversDeadline,
|
||||
hint: [
|
||||
stale
|
||||
? `聚水潭订单状态镜像最新只到 ${String(snapshotAt).slice(11, 16)}（已 ${Math.round(snapshotAgeMin / 60 * 10) / 10} 小时未刷新）。`
|
||||
: '',
|
||||
!coversDeadline
|
||||
? `数据还没覆盖到本轮核验时刻 ${String(round.deadline).slice(11, 16)}：`
|
||||
+ '此后发出的单在这里仍显示「未发货」，下面的超时单量偏大，请以聚水潭实时状态为准。'
|
||||
: '',
|
||||
].filter(Boolean).join(' '),
|
||||
};
|
||||
|
||||
const payload = {
|
||||
generatedAt: formatDateTime(now),
|
||||
date: round.date,
|
||||
round: {
|
||||
key: round.key,
|
||||
label: round.label,
|
||||
verifyHour: round.verifyHour,
|
||||
windowEnd: round.windowEnd,
|
||||
},
|
||||
notStarted: false,
|
||||
isPreviousDay: false,
|
||||
rounds,
|
||||
deadline: round.deadline,
|
||||
// boundary='audit'：轮次归属、已等时长都按**首次审核时间**算
|
||||
window: {
|
||||
start: round.windowStart,
|
||||
end: round.windowEnd,
|
||||
includeHistory: true,
|
||||
boundary: 'audit',
|
||||
measuredBy: 'audit',
|
||||
// 仓级例外窗口（山东青岗集/山东品牌 15:00、河南洛宁 13:00，仅 18:00 轮）
|
||||
overrides: windowOverrides,
|
||||
},
|
||||
summary,
|
||||
centers,
|
||||
orders,
|
||||
// 不考核的快递（前端文案直接用，避免两边各写一份）
|
||||
excludedCarriers: EXCLUDED_CARRIERS,
|
||||
// 不计考核清单（待审核 / 异常）—— 与 orders 互斥
|
||||
heldOrders,
|
||||
truncated: pendingRows.length > orders.length,
|
||||
detailLimit: limit,
|
||||
detailDegraded: false,
|
||||
freshness,
|
||||
cached: false,
|
||||
cacheAgeSec: 0,
|
||||
note: '',
|
||||
};
|
||||
|
||||
resultCache = { key: cacheKey, at: Date.now(), data: payload };
|
||||
return payload;
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
getShipTimeliness,
|
||||
clearShipTimelinessCache,
|
||||
DEFAULT_DETAIL_LIMIT,
|
||||
MAX_DETAIL_LIMIT,
|
||||
};
|
||||
@ -1,110 +0,0 @@
|
||||
'use strict';
|
||||
|
||||
const test = require('node:test');
|
||||
const assert = require('node:assert/strict');
|
||||
|
||||
const {
|
||||
AVAILABLE_FLOW_FIELDS,
|
||||
buildInClause,
|
||||
fetchFlows,
|
||||
} = require('../src/services/dailyInventoryFlows');
|
||||
const { deriveAndStoreOpeningSnapshot } = require('../src/services/dailyInventoryOpening');
|
||||
|
||||
const BASELINE = [
|
||||
{ warehouse: '仓A主仓', dbWarehouse: '仓A', wmsCoId: 101 },
|
||||
{ warehouse: '仓B主仓', dbWarehouse: '仓B', wmsCoId: 102 },
|
||||
{ warehouse: '仓C主仓', dbWarehouse: null, wmsCoId: 103 },
|
||||
];
|
||||
|
||||
/** 构造一个按 SQL 关键字路由的假业务库 */
|
||||
function fakeCloudDb(handler) {
|
||||
return { query: async (sql, params) => handler(String(sql), params || {}) };
|
||||
}
|
||||
|
||||
test('buildInClause 展开参数且不为 async', () => {
|
||||
const { clause, params } = buildInClause([1, 2], 'w');
|
||||
assert.equal(clause, '@w0,@w1');
|
||||
assert.deepEqual(params, { w0: 1, w1: 2 });
|
||||
});
|
||||
|
||||
test('fetchFlows 查询四类单据并按符号约定返回（流入正、流出负）', async () => {
|
||||
const seen = [];
|
||||
const db = fakeCloudDb((sql, params) => {
|
||||
seen.push(sql);
|
||||
if (sql.includes('jst_purchaseItem')) return [{ wmsCoId: 101, qty: '100' }];
|
||||
if (sql.includes('jst_purchaseoutItem')) return [{ wmsCoId: 101, qty: '30' }];
|
||||
if (sql.includes('jst_OrderItem')) return [{ wmsCoId: 101, qty: '50' }];
|
||||
if (sql.includes('jst_returnAndRefundItem')) return [{ wmsCoId: 101, qty: '8' }];
|
||||
return [];
|
||||
});
|
||||
const map = await fetchFlows(db, [101, 102], '2026-09-26 01:00:00');
|
||||
const f = map.get('101');
|
||||
assert.equal(f.purchaseIn, 100, '采购进仓为流入正数');
|
||||
assert.equal(f.purchaseReturn, -30, '采购退货为流出负数');
|
||||
assert.equal(f.salesOut, -50, '销售出仓为流出负数');
|
||||
assert.equal(f.salesReturn, 8, '销售退货为流入正数');
|
||||
assert.equal(seen.length, 4, '应发出 4 条单据查询');
|
||||
assert.ok(seen.every((s) => s.includes('@from')), '每条查询都带 @from 参数');
|
||||
assert.deepEqual(AVAILABLE_FLOW_FIELDS.sort(), ['purchaseIn', 'purchaseReturn', 'salesOut', 'salesReturn']);
|
||||
});
|
||||
|
||||
test('fetchFlows 空仓库列表直接返回空 Map', async () => {
|
||||
const map = await fetchFlows(fakeCloudDb(() => []), [], '2026-09-26 01:00:00');
|
||||
assert.equal(map.size, 0);
|
||||
});
|
||||
|
||||
test('deriveAndStoreOpeningSnapshot：全部仓库用实时库存扣流水回推，并保留基线仓库名', async () => {
|
||||
const upserts = [];
|
||||
const cloudDb = fakeCloudDb((sql, params) => {
|
||||
if (sql.includes('jst_inventoryInfo')) {
|
||||
return [
|
||||
{ wmsCoId: 101, qty: '520', skuCount: '13' },
|
||||
{ wmsCoId: 102, qty: '300', skuCount: '9' },
|
||||
{ wmsCoId: 103, qty: '10', skuCount: '2' },
|
||||
];
|
||||
}
|
||||
if (sql.includes('jst_purchaseItem')) return [{ wmsCoId: 102, qty: '60' }];
|
||||
if (sql.includes('jst_purchaseoutItem')) return [{ wmsCoId: 102, qty: '10' }];
|
||||
if (sql.includes('jst_OrderItem')) return [{ wmsCoId: 102, qty: '40' }];
|
||||
if (sql.includes('jst_returnAndRefundItem')) return [];
|
||||
return [];
|
||||
});
|
||||
const snapshotDb = {
|
||||
async upsertSnapshot(bizDate, rows) {
|
||||
upserts.push({ bizDate, rows });
|
||||
return rows.length;
|
||||
},
|
||||
};
|
||||
|
||||
const result = await deriveAndStoreOpeningSnapshot({
|
||||
cloudDb,
|
||||
snapshotDb,
|
||||
baseline: BASELINE,
|
||||
openingDate: '2026-09-25',
|
||||
latestBizDate: '2026-09-26',
|
||||
takenAt: null,
|
||||
});
|
||||
|
||||
assert.equal(result.count, 3);
|
||||
assert.equal(result.derivedCount, 3);
|
||||
assert.equal(upserts.length, 1);
|
||||
assert.equal(upserts[0].bizDate, '2026-09-25');
|
||||
|
||||
const byWh = new Map(upserts[0].rows.map((r) => [r.wmsCoId, r]));
|
||||
// 仓A：无流水 → 等于实时库存 520
|
||||
assert.equal(byWh.get(101).closingQty, 520);
|
||||
// 仓B：300 − 净流入(60 − 10 − 40) = 300 − 10 = 290
|
||||
assert.equal(byWh.get(102).closingQty, 290);
|
||||
// 仓C：无流水 → 等于实时库存 10
|
||||
assert.equal(byWh.get(103).closingQty, 10);
|
||||
// 带回基线仓库名，保证后续按 wmsCoId 读取正确
|
||||
assert.equal(byWh.get(102).warehouse, '仓B主仓');
|
||||
assert.equal(byWh.get(102).dbWarehouse, '仓B');
|
||||
});
|
||||
|
||||
test('fetchFlows 缺少数据库实例参数时立即抛错（防静默空结果）', async () => {
|
||||
await assert.rejects(
|
||||
() => fetchFlows([101, 102], '2026-09-26 01:00:00'),
|
||||
/第一个参数必须是数据库实例/
|
||||
);
|
||||
});
|
||||
@ -1,333 +0,0 @@
|
||||
'use strict';
|
||||
|
||||
const test = require('node:test');
|
||||
const assert = require('node:assert/strict');
|
||||
|
||||
const {
|
||||
DEFAULT_NOTIFY_TIME,
|
||||
MAX_RECIPIENTS,
|
||||
buildIdempotencyKey,
|
||||
normalizeFlag,
|
||||
normalizeNotifyTime,
|
||||
normalizeRecipients,
|
||||
} = require('../src/services/dailyInventoryNotificationSettings');
|
||||
const {
|
||||
ACTION_TITLE,
|
||||
NOTIFICATION_TITLE,
|
||||
buildNotificationContent,
|
||||
minutesOfDay,
|
||||
resolveBizDate,
|
||||
withRetry,
|
||||
} = require('../src/jobs/dailyInventoryNotificationJob');
|
||||
const {
|
||||
buildScreenshotNames,
|
||||
chinaTimeParts,
|
||||
} = require('../src/services/dailyInventoryScreenshot');
|
||||
|
||||
// ── 收件人名单规范化 ────────────────────────────────────────────
|
||||
test('normalizeRecipients 去空值、去空白、保持顺序', () => {
|
||||
assert.deepEqual(normalizeRecipients(['张三', ' ', '李四', '', null, undefined]), ['张三', '李四']);
|
||||
});
|
||||
|
||||
test('normalizeRecipients 去重且忽略首尾空格', () => {
|
||||
assert.deepEqual(normalizeRecipients([' 张三 ', '张三', '李四', ' 李四']), ['张三', '李四']);
|
||||
});
|
||||
|
||||
test('normalizeRecipients 支持逗号/中文逗号/分号/换行分隔的字符串', () => {
|
||||
assert.deepEqual(
|
||||
normalizeRecipients('张三,李四，王五;赵六\n孙七'),
|
||||
['张三', '李四', '王五', '赵六', '孙七']
|
||||
);
|
||||
});
|
||||
|
||||
test('normalizeRecipients 对非法输入返回空数组', () => {
|
||||
assert.deepEqual(normalizeRecipients(null), []);
|
||||
assert.deepEqual(normalizeRecipients(undefined), []);
|
||||
assert.deepEqual(normalizeRecipients(12345), []);
|
||||
});
|
||||
|
||||
test('normalizeRecipients 超量时截断到上限', () => {
|
||||
const list = Array.from({ length: MAX_RECIPIENTS + 5 }, (_, i) => `用户${i}`);
|
||||
const result = normalizeRecipients(list);
|
||||
assert.equal(result.length, MAX_RECIPIENTS);
|
||||
assert.equal(result[0], '用户0');
|
||||
});
|
||||
|
||||
// ── 通知时间校验 ────────────────────────────────────────────────
|
||||
test('normalizeNotifyTime 接受合法 HH:mm 并补零', () => {
|
||||
assert.equal(normalizeNotifyTime('1:05'), '01:05');
|
||||
assert.equal(normalizeNotifyTime('23:59'), '23:59');
|
||||
assert.equal(normalizeNotifyTime('00:00'), '00:00');
|
||||
});
|
||||
|
||||
test('normalizeNotifyTime 支持 HH:mm:ss 并截断到分钟', () => {
|
||||
assert.equal(normalizeNotifyTime('01:00:30'), '01:00');
|
||||
});
|
||||
|
||||
test('normalizeNotifyTime 非法值回退默认 01:00', () => {
|
||||
assert.equal(normalizeNotifyTime('24:00'), DEFAULT_NOTIFY_TIME);
|
||||
assert.equal(normalizeNotifyTime('12:60'), DEFAULT_NOTIFY_TIME);
|
||||
assert.equal(normalizeNotifyTime('abc'), DEFAULT_NOTIFY_TIME);
|
||||
assert.equal(normalizeNotifyTime(''), DEFAULT_NOTIFY_TIME);
|
||||
assert.equal(normalizeNotifyTime(null), DEFAULT_NOTIFY_TIME);
|
||||
});
|
||||
|
||||
test('normalizeFlag 只接受明确的布尔语义，未知值回退默认', () => {
|
||||
assert.equal(normalizeFlag('true', false), true);
|
||||
assert.equal(normalizeFlag('off', true), false);
|
||||
assert.equal(normalizeFlag('maybe', true), true);
|
||||
assert.equal(normalizeFlag(null, false), false);
|
||||
});
|
||||
|
||||
// ── 幂等键 ──────────────────────────────────────────────────────
|
||||
test('buildIdempotencyKey 正式推送按业务日期+收件人稳定生成', () => {
|
||||
const a = buildIdempotencyKey({ bizDate: '2026-09-25', recipient: '张三', mode: 'scheduled' });
|
||||
const b = buildIdempotencyKey({ bizDate: '2026-09-25', recipient: '张三', mode: 'scheduled' });
|
||||
const c = buildIdempotencyKey({ bizDate: '2026-09-25', recipient: '李四', mode: 'scheduled' });
|
||||
assert.equal(a, b);
|
||||
assert.notEqual(a, c);
|
||||
});
|
||||
|
||||
test('buildIdempotencyKey 测试推送带随机数，不占用正式幂等记录', () => {
|
||||
const formal = buildIdempotencyKey({ bizDate: '2026-09-25', recipient: '张三', mode: 'scheduled' });
|
||||
const t1 = buildIdempotencyKey({ bizDate: '2026-09-25', recipient: '张三', mode: 'test', nonce: 'n1' });
|
||||
const t2 = buildIdempotencyKey({ bizDate: '2026-09-25', recipient: '张三', mode: 'test', nonce: 'n2' });
|
||||
assert.notEqual(t1, t2);
|
||||
assert.notEqual(t1, formal);
|
||||
});
|
||||
|
||||
// ── 通知正文 ────────────────────────────────────────────────────
|
||||
test('buildNotificationContent 包含数据日期、生成时间、图片地址与页面链接', () => {
|
||||
const content = buildNotificationContent({
|
||||
bizDate: '2026-09-25',
|
||||
takenAt: '2026/09/25 01:00:00',
|
||||
imageUrl: 'https://cdn.example.com/daily-inventory/2026-09-25/daily-inventory-20260925-010000.png',
|
||||
pageUrl: 'https://ck.yydd.ai/planning/operation/daily-inventory',
|
||||
});
|
||||
assert.match(content, /2026-09-25/);
|
||||
assert.match(content, /2026\/09\/25 01:00:00/);
|
||||
assert.match(content, /https:\/\/cdn\.example\.com\//);
|
||||
assert.match(content, /https:\/\/ck\.yydd\.ai\/planning\/operation\/daily-inventory/);
|
||||
assert.match(content, new RegExp(ACTION_TITLE));
|
||||
assert.equal(NOTIFICATION_TITLE, '每日进销存数据');
|
||||
});
|
||||
|
||||
// ── 业务日期与调度时刻 ──────────────────────────────────────────
|
||||
test('resolveBizDate 取北京时间昨日（与页面 T-1 口径一致）', () => {
|
||||
assert.equal(resolveBizDate(new Date('2026-09-25T01:00:00+08:00')), '2026-09-24');
|
||||
assert.equal(resolveBizDate(new Date('2026-09-25T23:30:00+08:00')), '2026-09-24');
|
||||
});
|
||||
|
||||
test('minutesOfDay 正确换算，非法值返回 null', () => {
|
||||
assert.equal(minutesOfDay('00:00'), 0);
|
||||
assert.equal(minutesOfDay('01:00'), 60);
|
||||
assert.equal(minutesOfDay('23:59'), 1439);
|
||||
assert.equal(minutesOfDay('24:00'), null);
|
||||
assert.equal(minutesOfDay('abc'), null);
|
||||
assert.equal(minutesOfDay(null), null);
|
||||
});
|
||||
|
||||
test('chinaTimeParts 生成对象键所需的日期与时间片段', () => {
|
||||
const parts = chinaTimeParts(new Date('2026-09-25T01:00:00+08:00'));
|
||||
assert.equal(parts.bizDate, '2026-09-25');
|
||||
assert.equal(parts.dateKey, '20260925');
|
||||
assert.equal(parts.timeKey, '010000');
|
||||
assert.equal(
|
||||
`daily-inventory/${parts.bizDate}/daily-inventory-${parts.dateKey}-${parts.timeKey}.png`,
|
||||
'daily-inventory/2026-09-25/daily-inventory-20260925-010000.png'
|
||||
);
|
||||
});
|
||||
|
||||
test('buildScreenshotNames 用业务日期归档目录与文件名，时间取执行时刻', () => {
|
||||
const names = buildScreenshotNames({ bizDate: '2026-09-25', timeKey: '010000' });
|
||||
assert.equal(names.fileName, 'daily-inventory-20260925-010000.png');
|
||||
assert.equal(
|
||||
names.objectKey,
|
||||
'daily-inventory/2026-09-25/daily-inventory-20260925-010000.png'
|
||||
);
|
||||
});
|
||||
|
||||
test('buildScreenshotNames 业务日期与执行日期不同时以业务日期为准', () => {
|
||||
// 凌晨 01:00 推送的是「昨日」数据，归档必须落在业务日而不是执行日
|
||||
const names = buildScreenshotNames({ bizDate: '2026-09-25', timeKey: '010000' });
|
||||
assert.ok(!names.objectKey.includes('2026-09-26'));
|
||||
assert.ok(names.objectKey.startsWith('daily-inventory/2026-09-25/'));
|
||||
});
|
||||
|
||||
test('buildScreenshotNames 业务日期缺失时回退空目录占位而不抛错', () => {
|
||||
const names = buildScreenshotNames({ bizDate: '', timeKey: '010000' });
|
||||
assert.equal(names.fileName, 'daily-inventory--010000.png');
|
||||
});
|
||||
|
||||
// ── 幂等记录：同一业务日期 + 同一用户只成功通知一次 ────────────
|
||||
async function withStubbedState(runner) {
|
||||
const database = require('../src/config/database');
|
||||
const settings = require('../src/services/dailyInventoryNotificationSettings');
|
||||
const original = database.local;
|
||||
const store = new Map();
|
||||
|
||||
database.local = {
|
||||
async query(sql, params) {
|
||||
const text = String(sql);
|
||||
if (text.startsWith('SELECT config_value')) {
|
||||
const value = store.get(params[0]);
|
||||
return value === undefined ? [] : [{ configValue: value }];
|
||||
}
|
||||
if (text.startsWith('SELECT id FROM system_config')) {
|
||||
const value = store.get(params[0]);
|
||||
return value === undefined ? [] : [{ id: 1 }];
|
||||
}
|
||||
// UPDATE system_config SET config_value = ? ...
|
||||
store.set(params[params.length - 1], params[0]);
|
||||
return { affectedRows: 1 };
|
||||
},
|
||||
async insert(_table, data) {
|
||||
store.set(data.config_key, data.config_value);
|
||||
return { insertId: 1 };
|
||||
},
|
||||
};
|
||||
|
||||
try {
|
||||
return await runner(settings);
|
||||
} finally {
|
||||
database.local = original;
|
||||
}
|
||||
}
|
||||
|
||||
test('markNotified 后同一业务日期同一用户命中幂等，跨日期互不影响', async () => {
|
||||
await withStubbedState(async (settings) => {
|
||||
assert.equal(await settings.hasNotified('2026-09-25', '苏适'), false);
|
||||
await settings.markNotified('2026-09-25', '苏适', { deliveryId: 'd-1' });
|
||||
assert.equal(await settings.hasNotified('2026-09-25', '苏适'), true);
|
||||
// 同一天其他用户不受影响
|
||||
assert.equal(await settings.hasNotified('2026-09-25', '李四'), false);
|
||||
// 同一用户换一天应当重新通知
|
||||
assert.equal(await settings.hasNotified('2026-09-26', '苏适'), false);
|
||||
});
|
||||
});
|
||||
|
||||
test('appendRunRecord 保留执行时间、截图地址、通知对象与失败原因', async () => {
|
||||
await withStubbedState(async (settings) => {
|
||||
await settings.appendRunRecord({
|
||||
runAt: '2026-09-25T01:00:00.000Z',
|
||||
bizDate: '2026-09-25',
|
||||
mode: 'scheduled',
|
||||
success: false,
|
||||
error: '所有收件人均通知失败',
|
||||
screenshotUrl: 'https://scqny.jiansun.vip/daily-inventory/2026-09-25/x.png',
|
||||
recipients: [{ recipient: '苏适', status: 'failed', error: '通知中心 502' }],
|
||||
});
|
||||
const runs = await settings.listRunRecords(5);
|
||||
assert.equal(runs.length, 1);
|
||||
assert.equal(runs[0].bizDate, '2026-09-25');
|
||||
assert.equal(runs[0].success, false);
|
||||
assert.equal(runs[0].error, '所有收件人均通知失败');
|
||||
assert.equal(runs[0].recipients[0].recipient, '苏适');
|
||||
assert.ok(runs[0].screenshotUrl.startsWith('https://'));
|
||||
});
|
||||
});
|
||||
|
||||
// ── 重试与退避 ──────────────────────────────────────────────────
|
||||
test('withRetry 第二次成功后返回结果', async () => {
|
||||
let calls = 0;
|
||||
const result = await withRetry(
|
||||
async () => {
|
||||
calls += 1;
|
||||
if (calls < 2) throw new Error('临时失败');
|
||||
return 'ok';
|
||||
},
|
||||
{ label: '单元测试', attempts: 3, baseDelayMs: 1 }
|
||||
);
|
||||
assert.equal(result, 'ok');
|
||||
assert.equal(calls, 2);
|
||||
});
|
||||
|
||||
test('withRetry 超过次数后抛出最后一次错误', async () => {
|
||||
let calls = 0;
|
||||
await assert.rejects(
|
||||
withRetry(
|
||||
async () => {
|
||||
calls += 1;
|
||||
throw new Error(`失败${calls}`);
|
||||
},
|
||||
{ label: '单元测试', attempts: 3, baseDelayMs: 1 }
|
||||
),
|
||||
/失败3/
|
||||
);
|
||||
assert.equal(calls, 3);
|
||||
});
|
||||
|
||||
// ── 截图身份：必须使用系统库中真实存在的服务账号 ──────────────
|
||||
test('ensureScreenshotServiceUser 账号不存在时创建，存在时复用 id', async () => {
|
||||
const database = require('../src/config/database');
|
||||
const screenshot = require('../src/services/dailyInventoryScreenshot');
|
||||
const original = database.local;
|
||||
const calls = { select: 0, insert: 0, update: 0 };
|
||||
let existing = null;
|
||||
|
||||
database.local = {
|
||||
async query(sql, params) {
|
||||
if (String(sql).startsWith('SELECT id, role, status FROM users')) {
|
||||
calls.select += 1;
|
||||
return existing ? [existing] : [];
|
||||
}
|
||||
calls.update += 1;
|
||||
return { affectedRows: 1 };
|
||||
},
|
||||
async insert(_table, data) {
|
||||
calls.insert += 1;
|
||||
assert.equal(data.role, 'admin');
|
||||
assert.equal(data.status, 'active');
|
||||
assert.equal(data.auth_source, 'service');
|
||||
assert.ok(String(data.password_hash || '').length > 20, '密码哈希不能为空');
|
||||
existing = { id: 4242, role: data.role, status: data.status };
|
||||
return { insertId: 4242 };
|
||||
},
|
||||
};
|
||||
|
||||
try {
|
||||
screenshot.resetScreenshotServiceUserCache();
|
||||
const created = await screenshot.ensureScreenshotServiceUser();
|
||||
assert.equal(created, 4242);
|
||||
assert.equal(calls.insert, 1);
|
||||
assert.equal(calls.select, 1);
|
||||
|
||||
// 第二次调用命中缓存，不再查库
|
||||
assert.equal(await screenshot.ensureScreenshotServiceUser(), 4242);
|
||||
assert.equal(calls.select, 1);
|
||||
} finally {
|
||||
database.local = original;
|
||||
screenshot.resetScreenshotServiceUserCache();
|
||||
}
|
||||
});
|
||||
|
||||
test('signScreenshotToken 的 sub 指向服务账号 id 且通过签名校验', async () => {
|
||||
const database = require('../src/config/database');
|
||||
const screenshot = require('../src/services/dailyInventoryScreenshot');
|
||||
const jwt = require('jsonwebtoken');
|
||||
const original = database.local;
|
||||
const originalSecret = process.env.CUBEJS_SECRET;
|
||||
process.env.CUBEJS_SECRET = originalSecret || 'test-secret-for-unit';
|
||||
|
||||
database.local = {
|
||||
async query() {
|
||||
return [{ id: 99, role: 'admin', status: 'active' }];
|
||||
},
|
||||
async insert() {
|
||||
throw new Error('不应在账号已存在时插入');
|
||||
},
|
||||
};
|
||||
|
||||
try {
|
||||
screenshot.resetScreenshotServiceUserCache();
|
||||
const token = await screenshot.signScreenshotToken();
|
||||
const payload = jwt.verify(token, process.env.CUBEJS_SECRET || 'test-secret');
|
||||
assert.equal(payload.sub, '99');
|
||||
assert.equal(payload.role, 'admin');
|
||||
assert.equal(payload.authSource, 'service');
|
||||
} finally {
|
||||
database.local = original;
|
||||
process.env.CUBEJS_SECRET = originalSecret;
|
||||
screenshot.resetScreenshotServiceUserCache();
|
||||
}
|
||||
});
|
||||
@ -1,101 +0,0 @@
|
||||
'use strict';
|
||||
|
||||
const test = require('node:test');
|
||||
const assert = require('node:assert/strict');
|
||||
const XLSX = require('xlsx');
|
||||
|
||||
const {
|
||||
normalizeRecords,
|
||||
parseWorkbook,
|
||||
checkBalance,
|
||||
} = require('../src/services/dailyInventoryOfficial');
|
||||
|
||||
const RECORDS = [
|
||||
{
|
||||
一级功能按键: '大货库存监控',
|
||||
二级功能按键: '每日进销存',
|
||||
仓库: '简尚-崔桥工厂仓主仓',
|
||||
期初数量: 90811,
|
||||
加工进仓: 0,
|
||||
采购退货: 0,
|
||||
采购进仓: 0,
|
||||
其它进仓: 0,
|
||||
其它退货: 0,
|
||||
销售出仓: -3252,
|
||||
盘点: 0,
|
||||
加工出仓: 0,
|
||||
调拨出: -881,
|
||||
销售退货: 0,
|
||||
调拨入: 4144,
|
||||
期初: 0,
|
||||
其它出库: 0,
|
||||
期末数量: 90822,
|
||||
},
|
||||
{
|
||||
仓库: '简尚-新外贸仓主仓',
|
||||
期初数量: 5165,
|
||||
销售出仓: -1743,
|
||||
期末数量: 3422,
|
||||
},
|
||||
];
|
||||
|
||||
test('normalizeRecords 解析官方导出并映射仓库 ID', () => {
|
||||
const { rows, warnings } = normalizeRecords(RECORDS);
|
||||
assert.equal(rows.length, 2);
|
||||
assert.deepEqual(warnings, []);
|
||||
|
||||
const [cuiqiao] = rows;
|
||||
assert.equal(cuiqiao.warehouse, '简尚-崔桥工厂仓主仓');
|
||||
assert.equal(cuiqiao.wmsCoId, 15038426); // 来自项目仓库清单
|
||||
assert.equal(cuiqiao.openingQty, 90811);
|
||||
assert.equal(cuiqiao.closingQty, 90822);
|
||||
assert.equal(cuiqiao.flows.salesOut, -3252);
|
||||
assert.equal(cuiqiao.flows.transferIn, 4144);
|
||||
assert.equal(cuiqiao.flows.otherIn, 0); // 导出里显式为 0 的列保留 0
|
||||
// 导出里没有出现的流水列保持 null，不能被当成 0
|
||||
assert.equal(rows[1].flows.transferOut, null);
|
||||
assert.equal(rows[1].flows.stocktaking, null);
|
||||
// 导出里的第二个「期初」列不参与映射
|
||||
assert.equal(Object.prototype.hasOwnProperty.call(cuiqiao.flows, 'openingQty'), false);
|
||||
});
|
||||
|
||||
test('normalizeRecords 跳过无仓库名的行，未匹配仓库的 wmsCoId 为 null', () => {
|
||||
const { rows } = normalizeRecords([
|
||||
{ 仓库: '', 期初数量: 1, 期末数量: 1 },
|
||||
{ 仓库: '某某新仓主仓', 期初数量: 10, 期末数量: 10 },
|
||||
]);
|
||||
assert.equal(rows.length, 1);
|
||||
assert.equal(rows[0].warehouse, '某某新仓主仓');
|
||||
assert.equal(rows[0].wmsCoId, null);
|
||||
});
|
||||
|
||||
test('checkBalance 校验「期初 + 流水 = 期末」，不闭合的仓库会被列出', () => {
|
||||
const { rows } = normalizeRecords(RECORDS);
|
||||
assert.deepEqual(checkBalance(rows), []);
|
||||
|
||||
const broken = checkBalance([{
|
||||
warehouse: '差异仓', openingQty: 100, closingQty: 90, flows: { salesOut: -5 },
|
||||
}]);
|
||||
assert.equal(broken.length, 1);
|
||||
assert.equal(broken[0].diff, 5);
|
||||
});
|
||||
|
||||
test('parseWorkbook 能从 xlsx 缓冲区还原仓库行（表头不在首行也能定位）', () => {
|
||||
const grid = [
|
||||
['说明', '这一行是导出时附加的标题'],
|
||||
['一级功能按键', '二级功能按键', '仓库', '期初数量', '销售出仓', '调拨入', '期末数量'],
|
||||
['大货库存监控', '每日进销存', '简尚-崔桥工厂仓主仓', 90811, -3252, 4144, 90822],
|
||||
['', '', '简尚-新外贸仓主仓', 5165, -1743, 0, 3422],
|
||||
];
|
||||
const ws = XLSX.utils.aoa_to_sheet(grid);
|
||||
const wb = XLSX.utils.book_new();
|
||||
XLSX.utils.book_append_sheet(wb, ws, 'Sheet2');
|
||||
const buffer = XLSX.write(wb, { type: 'buffer', bookType: 'xlsx' });
|
||||
|
||||
const { rows, sheetName } = parseWorkbook(buffer);
|
||||
assert.equal(sheetName, 'Sheet2');
|
||||
assert.equal(rows.length, 2);
|
||||
assert.equal(rows[0].warehouse, '简尚-崔桥工厂仓主仓');
|
||||
assert.equal(rows[0].flows.transferIn, 4144);
|
||||
assert.equal(rows[1].closingQty, 3422);
|
||||
});
|
||||
@ -525,74 +525,6 @@ test('replenish index: hourly box/pallet stock surfaces same-day inbound (⑦-d)
|
||||
}
|
||||
});
|
||||
|
||||
// ⑦-e 成品库存多仓合并（2026-10-17）：
|
||||
// 实物搬到「简尚-横林二仓品牌仓」(16132681) 时，归属仓 (15870495) 为 0，
|
||||
// 只查归属仓会把有货的成品算成 0（本次 5 个误报缺货 + 2 个误报预警）。
|
||||
test('replenish index: sums stock across brand warehouse whitelist (⑦-e)', async () => {
|
||||
const cloudDatabase = require('../src/config/cloudDatabase');
|
||||
const svc = require('../src/services/mkhBomService');
|
||||
const originalQuery = cloudDatabase.query;
|
||||
const originalGetPool = cloudDatabase.getPool;
|
||||
const captured = [];
|
||||
|
||||
cloudDatabase.query = async (sql) => {
|
||||
captured.push(sql);
|
||||
if (sql.includes('jst_packInventoryInfo')) {
|
||||
// 箱表：同样的「老仓 0 / 新仓 10」格局
|
||||
return [{ skuId: 'MKHDNZ0409260600788', qty: 10 }];
|
||||
}
|
||||
if (sql.includes('jst_inventoryInfo')) {
|
||||
// 关键：SUM 之后返回的是**多仓合计**。旧口径只查单仓时这里拿不到这笔货。
|
||||
return [{ skuId: 'MKHDNZ0409260600788', qty: 10 }];
|
||||
}
|
||||
if (sql.includes('pm_stockMonitor')) {
|
||||
return [{
|
||||
skuId: 'MKHDNZ0409260600788',
|
||||
fifteenAvgSale: 1,
|
||||
monitorStock: 0,
|
||||
safetyDays: 3,
|
||||
suggestStock: 0,
|
||||
monitorDate: new Date('2026-10-17T00:00:00Z'),
|
||||
}];
|
||||
}
|
||||
if (sql.includes('jst_salesOutboundInfo') || sql.includes('jst_qmcust_salesoutbound')) return [];
|
||||
if (sql.includes('jst_qmcust_orderlist')) return [];
|
||||
return [];
|
||||
};
|
||||
cloudDatabase.getPool = async () => ({
|
||||
request: () => ({ input() {}, query: async () => ({ recordset: [] }) }),
|
||||
});
|
||||
|
||||
try {
|
||||
const index = await svc._private.loadReplenishIndex();
|
||||
const row = index.bySku.get('MKHDNZ0409260600788');
|
||||
assert.equal(row.stock, 10, '多仓求和后必须看到新仓的 10 件，不能是 0');
|
||||
|
||||
// SQL 层必须真的按白名单多仓取数，而不是退回单仓
|
||||
const invSql = captured.find((s) => s.includes('jst_inventoryInfo'));
|
||||
assert.ok(invSql.includes('IN (15870495,16132681)'),
|
||||
`实时库存必须按仓白名单取数，实际: ${invSql}`);
|
||||
assert.ok(invSql.includes('GROUP BY') && invSql.includes('SUM('),
|
||||
'实时库存必须多仓 SUM + GROUP BY（旧版是 ORDER BY updateTime DESC 取首条）');
|
||||
const packSql = captured.find((s) => s.includes('jst_packInventoryInfo'));
|
||||
assert.ok(packSql.includes('IN (15870495,16132681)'),
|
||||
`箱表必须按同一份仓白名单取数，实际: ${packSql}`);
|
||||
} finally {
|
||||
cloudDatabase.query = originalQuery;
|
||||
cloudDatabase.getPool = originalGetPool;
|
||||
svc.clearMkhBomCache();
|
||||
}
|
||||
});
|
||||
|
||||
// 白名单常量本身要被导出（新增同类仓时改这一处即可）
|
||||
test('replenish index: brand warehouse whitelist contains main + Henglin No.2 brand warehouse', () => {
|
||||
const svc = require('../src/services/mkhBomService');
|
||||
const ids = svc._private.BRAND_WMS_CO_IDS;
|
||||
assert.ok(Array.isArray(ids), 'BRAND_WMS_CO_IDS 必须是数组');
|
||||
assert.ok(ids.includes(15870495), '必须含崔桥工厂品牌仓（归属主仓）');
|
||||
assert.ok(ids.includes(16132681), '必须含横林二仓品牌仓（2026-10-13 新增）');
|
||||
});
|
||||
|
||||
test('order index: reads both channel tables, merges and dedupes by o_id', async () => {
|
||||
const cloudDatabase = require('../src/config/cloudDatabase');
|
||||
const svc = require('../src/services/mkhBomService');
|
||||
@ -1354,117 +1286,6 @@ test('cache epoch: 未经清缓存时缓存照常命中（回归保护）', asyn
|
||||
}
|
||||
});
|
||||
|
||||
// ─────────────────────────────────────────────────────────────────────────────
|
||||
// 配件库存的箱表兜底（2026-09-30 修正）
|
||||
//
|
||||
// 症状：配件监控页显示该配件有 200 件（货位 ZT-30、正常），MKH-BOM 却把成品
|
||||
// MKHDNZ0409260600849 判成「配件不足」、可组装数 0。
|
||||
// 成因：配件监控页是「库存表 → 同仓箱表 → 快照」三级兜底，而 MKH-BOM 的
|
||||
// loadComponentStock **只查 jst_inventoryInfo**。上游库存表滞后停在 0 时，
|
||||
// 箱表（小时级）已经有货 → 两个页面结论相反。
|
||||
// 口径：与配件监控页 buildRealtimeStockSql 对齐 —— 库存表有正数就认它，
|
||||
// 为 0 / 缺行才用同仓 jst_packInventoryInfo 的 bin 非空行合计兜底。
|
||||
// ─────────────────────────────────────────────────────────────────────────────
|
||||
|
||||
test('配件库存兜底：库存表为 0 / 缺行时用同仓箱表补，但正库存不被覆盖', async () => {
|
||||
const cloudDatabase = require('../src/config/cloudDatabase');
|
||||
const svc = require('../src/services/mkhBomService');
|
||||
const originalQuery = cloudDatabase.query;
|
||||
|
||||
const ONLY_PACK = 'DNZTESTPACK01'; // 库存表 0、箱表 200 → 必须取 200（误判就是这里）
|
||||
const HAS_INV = 'DNZTESTPACK02'; // 库存表 5、箱表 300 → 必须取 5（箱表只记部分装箱量）
|
||||
const PACK_ZERO = 'DNZTESTPACK03'; // 库存表 0、箱表 0 → 0
|
||||
const NEITHER = 'DNZTESTPACK04'; // 两表都没有 → 0
|
||||
|
||||
const INV_ROWS = [ // 库存表：滞后停在旧值
|
||||
{ code: ONLY_PACK, qty: 0 },
|
||||
{ code: HAS_INV, qty: 5 },
|
||||
{ code: PACK_ZERO, qty: 0 },
|
||||
];
|
||||
const PACK_ROWS = [ // 同仓箱表（bin 非空）：小时级，已反映真实到货
|
||||
{ code: ONLY_PACK, qty: 200 },
|
||||
{ code: HAS_INV, qty: 300 },
|
||||
{ code: PACK_ZERO, qty: 0 },
|
||||
];
|
||||
cloudDatabase.query = async (sql) => {
|
||||
if (!sql.includes('jst_inventoryInfo')) return [];
|
||||
// 按 SQL 形状分流：旧实现只查库存表（SQL 里没有箱表名）→ 拿不到箱表数据，
|
||||
// 兜底失效、ONLY_PACK 被判 0（对照组 = 修复前必然失败）。
|
||||
if (!sql.includes('jst_packInventoryInfo')) return INV_ROWS;
|
||||
return [
|
||||
...INV_ROWS.map((row) => ({ src: 'inv', ...row })),
|
||||
...PACK_ROWS.map((row) => ({ src: 'pack', ...row })),
|
||||
];
|
||||
};
|
||||
|
||||
try {
|
||||
svc.clearMkhBomCache();
|
||||
const { stockMap, degraded } = await svc._private.loadComponentStock([
|
||||
ONLY_PACK, HAS_INV, PACK_ZERO, NEITHER,
|
||||
]);
|
||||
assert.equal(degraded, false);
|
||||
assert.equal(stockMap.get(ONLY_PACK), 200,
|
||||
'库存表为 0 时必须用箱表兜底，否则配件被误判不足（本问题的根因）');
|
||||
assert.equal(stockMap.get(HAS_INV), 5,
|
||||
'库存表有正库存时必须以它为准，不能被箱表覆盖');
|
||||
assert.equal(stockMap.get(PACK_ZERO), 0, '箱表也是 0 时不能补出正数');
|
||||
assert.equal(stockMap.get(NEITHER), 0, '两表都查不到 = 该仓无库存，仍按 0');
|
||||
} finally {
|
||||
cloudDatabase.query = originalQuery;
|
||||
svc.clearMkhBomCache();
|
||||
}
|
||||
});
|
||||
|
||||
test('配件库存兜底：单条查询取两张表，且箱表必须过滤 bin 为空的行（防腐化）', async () => {
|
||||
const cloudDatabase = require('../src/config/cloudDatabase');
|
||||
const svc = require('../src/services/mkhBomService');
|
||||
const originalQuery = cloudDatabase.query;
|
||||
|
||||
const seen = [];
|
||||
cloudDatabase.query = async (sql) => {
|
||||
if (!sql.includes('jst_inventoryInfo')) return [];
|
||||
seen.push(sql);
|
||||
return [];
|
||||
};
|
||||
|
||||
try {
|
||||
svc.clearMkhBomCache();
|
||||
await svc._private.loadComponentStock(['DNZTESTPACK05']);
|
||||
assert.equal(seen.length, 1, '一个分片只应打一条查询（避免多一次往返与快照时点差异）');
|
||||
const sql = seen[0];
|
||||
assert.match(sql, /jst_packInventoryInfo/, '必须查箱表，否则兜底不存在');
|
||||
assert.match(sql, /NULLIF\(LTRIM\(RTRIM\(p\.bin\)\), N''\)\s+IS NOT NULL/,
|
||||
'箱表必须过滤 bin 为空的行 —— 那是装箱记录，不是库存');
|
||||
assert.match(sql, /p\.wms_co_id = @componentStockWmsCoId/,
|
||||
'箱表必须限定配件归属仓，不能跨仓汇总');
|
||||
} finally {
|
||||
cloudDatabase.query = originalQuery;
|
||||
svc.clearMkhBomCache();
|
||||
}
|
||||
});
|
||||
|
||||
test('配件库存兜底：查询失败仍降级为「不做判定」，不得当成 0', async () => {
|
||||
const cloudDatabase = require('../src/config/cloudDatabase');
|
||||
const svc = require('../src/services/mkhBomService');
|
||||
const originalQuery = cloudDatabase.query;
|
||||
|
||||
const CODE = 'DNZTESTPACK06';
|
||||
cloudDatabase.query = async (sql) => {
|
||||
if (!sql.includes('jst_inventoryInfo')) return [];
|
||||
throw new Error('模拟连接抖动');
|
||||
};
|
||||
|
||||
try {
|
||||
svc.clearMkhBomCache();
|
||||
const { stockMap, degraded } = await svc._private.loadComponentStock([CODE]);
|
||||
assert.equal(degraded, true, '查询失败必须降级，让调用方放弃配件不足判定（宁可少标不误标）');
|
||||
assert.equal(stockMap.get(CODE), undefined, '失败时不得把未知库存当作 0 返回');
|
||||
} finally {
|
||||
cloudDatabase.query = originalQuery;
|
||||
svc.clearMkhBomCache();
|
||||
}
|
||||
});
|
||||
|
||||
test('operational refresh: 并发刷新只查一次运营数据，短时重试复用新结果', async () => {
|
||||
const cloudDatabase = require('../src/config/cloudDatabase');
|
||||
const svc = require('../src/services/mkhBomService');
|
||||
|
||||
@ -1,171 +0,0 @@
|
||||
'use strict';
|
||||
|
||||
const test = require('node:test');
|
||||
const assert = require('node:assert/strict');
|
||||
|
||||
const {
|
||||
buildGradeCase,
|
||||
buildInClause,
|
||||
fetchPickingBinSkuRows,
|
||||
} = require('../src/services/pickingBinSalesAnalysis');
|
||||
const {
|
||||
PICKING_BIN_GRADE_RULES,
|
||||
PICKING_BIN_DEFAULT_DAYS,
|
||||
PICKING_BIN_WINDOW_OPTIONS,
|
||||
PICKING_BIN_BIN_TYPES,
|
||||
} = require('../src/config/pickingBinSalesAnalysis');
|
||||
|
||||
test('buildInClause 按位展开参数', () => {
|
||||
const { clause, params } = buildInClause([101, 102], 'w');
|
||||
assert.equal(clause, '@w0,@w1');
|
||||
assert.deepEqual(params, { w0: 101, w1: 102 });
|
||||
});
|
||||
|
||||
test('buildGradeCase 覆盖全部正向等级，并以销售=0 兜底', () => {
|
||||
const expr = buildGradeCase();
|
||||
PICKING_BIN_GRADE_RULES.filter((rule) => rule.lower > 0).forEach((rule) => {
|
||||
assert.ok(expr.includes(`THEN '${rule.key}'`), `${rule.key} 未出现在分档表达式中`);
|
||||
});
|
||||
assert.ok(expr.includes("THEN 'slow2'"));
|
||||
assert.ok(expr.includes("ELSE 'zero'"));
|
||||
});
|
||||
|
||||
test('等级按商品销量判定（默认表达式取 s.salesQty，不含仓位汇总列）', () => {
|
||||
const expr = buildGradeCase();
|
||||
assert.ok(expr.includes('ISNULL(s.salesQty, 0) / @days'));
|
||||
assert.ok(!expr.includes('x.salesQty'));
|
||||
});
|
||||
|
||||
test('默认窗口为 30 天，统计范围固定为拣选位', () => {
|
||||
assert.equal(PICKING_BIN_DEFAULT_DAYS, 30);
|
||||
assert.ok(PICKING_BIN_WINDOW_OPTIONS.includes(30));
|
||||
assert.deepEqual(PICKING_BIN_BIN_TYPES, ['拣选']);
|
||||
});
|
||||
|
||||
test('fetchPickingBinSkuRows 首参不是数据库实例时抛错', async () => {
|
||||
await assert.rejects(
|
||||
() => fetchPickingBinSkuRows({}, [101], { shipFrom: 'a', shipTo: 'b', days: 30 }),
|
||||
TypeError
|
||||
);
|
||||
});
|
||||
|
||||
test('fetchPickingBinSkuRows 缺失必要窗口参数时返回空数组，不打库', async () => {
|
||||
let called = 0;
|
||||
const db = { query: async () => { called += 1; return [{ skuId: 'S1' }]; } };
|
||||
assert.deepEqual(await fetchPickingBinSkuRows(db, [], { shipFrom: 'a', shipTo: 'b', days: 30 }), []);
|
||||
assert.deepEqual(await fetchPickingBinSkuRows(db, [101], { shipFrom: null, shipTo: 'b', days: 30 }), []);
|
||||
assert.deepEqual(await fetchPickingBinSkuRows(db, [101], { shipFrom: 'a', shipTo: 'b', days: 0 }), []);
|
||||
assert.equal(called, 0);
|
||||
});
|
||||
|
||||
test('fetchPickingBinSkuRows 按仓位×商品输出，等级与日销来自商品整档销量', async () => {
|
||||
let captured = null;
|
||||
const db = {
|
||||
query: async (sqlText, params) => {
|
||||
captured = { sqlText, params };
|
||||
return [
|
||||
{
|
||||
wmsCoId: 101, binName: 'XA01-01-01', binType: '拣选', skuId: 'SKU1',
|
||||
stockQty: 12, skuCount: 2, salesQty: 600, allocatedSalesQty: 300,
|
||||
dailySales: 20, gradeKey: 'hot',
|
||||
},
|
||||
{
|
||||
wmsCoId: 101, binName: 'XA01-01-01', binType: '拣选', skuId: 'SKU2',
|
||||
stockQty: 8, skuCount: 2, salesQty: 45, allocatedSalesQty: 22.5,
|
||||
dailySales: 1.5, gradeKey: 'slow1',
|
||||
},
|
||||
];
|
||||
},
|
||||
};
|
||||
|
||||
const rows = await fetchPickingBinSkuRows(db, [101, 102], {
|
||||
shipFrom: '2026-09-08 01:00:00',
|
||||
shipTo: '2026-10-08 01:00:00',
|
||||
days: 30,
|
||||
});
|
||||
|
||||
assert.equal(rows.length, 2);
|
||||
assert.deepEqual(rows.map((r) => r.skuId), ['SKU1', 'SKU2']);
|
||||
// 同一仓位两个商品拆两行，库存是各商品在该仓位的实际库存
|
||||
assert.deepEqual(rows.map((r) => r.stockQty), [12, 8]);
|
||||
// 等级按商品自身日销，同一仓位的多行可以不同
|
||||
assert.deepEqual(rows.map((r) => r.gradeKey), ['hot', 'slow1']);
|
||||
// 分摊销量 = 商品销量 ÷ 占用的同类型仓位数（用于按行求和）
|
||||
assert.deepEqual(rows.map((r) => r.allocatedSalesQty), [300, 22.5]);
|
||||
assert.deepEqual(rows[0], {
|
||||
wmsCoId: '101',
|
||||
binName: 'XA01-01-01',
|
||||
binType: '拣选',
|
||||
skuId: 'SKU1',
|
||||
stockQty: 12,
|
||||
skuCount: 2,
|
||||
salesQty: 600,
|
||||
allocatedSalesQty: 300,
|
||||
dailySales: 20,
|
||||
gradeKey: 'hot',
|
||||
});
|
||||
|
||||
// 参数必须带上两个仓库、发货窗口与天数
|
||||
assert.equal(captured.params.w0, 101);
|
||||
assert.equal(captured.params.w1, 102);
|
||||
assert.equal(captured.params.v0, 101);
|
||||
assert.equal(captured.params.shipFrom, '2026-09-08 01:00:00');
|
||||
assert.equal(captured.params.shipTo, '2026-10-08 01:00:00');
|
||||
assert.equal(captured.params.days, 30);
|
||||
|
||||
// 商品销量按占用仓位数分摊（供求和），但等级依据的是未分摊的商品销量
|
||||
assert.ok(captured.sqlText.includes('/ NULLIF(sp.binCount, 0)'));
|
||||
assert.ok(captured.sqlText.includes('ISNULL(s.salesQty, 0) / @days AS DECIMAL(18, 4)'));
|
||||
// 统计范围固定为真实拣选仓位：pack_type=Bin 且 bin_group 为空；只统计有库存的行
|
||||
assert.ok(captured.sqlText.includes("p.pack_type = N'Bin'"));
|
||||
assert.ok(captured.sqlText.includes("ISNULL(p.bin_group, '') = ''"));
|
||||
assert.ok(captured.sqlText.includes('ISNULL(p.qty, 0) <> 0'));
|
||||
assert.ok(captured.sqlText.includes('HAVING ABS(SUM(CAST(b.binSkuQty AS DECIMAL(18, 2)))) > 0.0001'));
|
||||
});
|
||||
|
||||
test('fetchPickingBinSkuRows 只统计真实拣选仓位，排除 Pack 箱记录且不带类型参数', async () => {
|
||||
let captured = null;
|
||||
const db = {
|
||||
query: async (sqlText, params) => { captured = { sqlText, params }; return []; },
|
||||
};
|
||||
await fetchPickingBinSkuRows(db, [101], { shipFrom: 'a', shipTo: 'b', days: 15 });
|
||||
// Pack 箱记录和存货位被排除，且不再有 binType IN (...) 的可变过滤
|
||||
assert.ok(captured.sqlText.includes("p.pack_type = N'Bin'"));
|
||||
assert.ok(captured.sqlText.includes("ISNULL(p.bin_group, '') = ''"));
|
||||
assert.ok(!captured.sqlText.includes('b.binType IN'));
|
||||
assert.equal(captured.params.t0, undefined);
|
||||
assert.equal(captured.params.binTypes, undefined);
|
||||
// 多来源 union 后必须再按 仓库+商品 汇总，否则同一仓位行会被拆成多行
|
||||
assert.ok(captured.sqlText.includes('shipAgg AS ('));
|
||||
assert.ok(captured.sqlText.includes('LEFT JOIN shipAgg s'));
|
||||
assert.ok(!captured.sqlText.includes('LEFT JOIN ship s'));
|
||||
});
|
||||
|
||||
test('销量覆盖 4 个来源：线上普通行 + 组合装展开 + 全民客户普通行 + 全民客户组合装展开', async () => {
|
||||
let captured = null;
|
||||
const db = {
|
||||
query: async (sqlText, params) => { captured = { sqlText, params }; return []; },
|
||||
};
|
||||
await fetchPickingBinSkuRows(db, [101], { shipFrom: 'a', shipTo: 'b', days: 30 });
|
||||
|
||||
// ① 线上店铺订单普通行
|
||||
assert.ok(captured.sqlText.includes('FROM rpt.jst_OrderItem'), '缺少 jst_OrderItem 普通行分支');
|
||||
// ② 线上订单组合装行按映射表展开为子件
|
||||
assert.ok(captured.sqlText.includes('JOIN rpt.jst_comboProductItem'), '缺少组合装展开分支');
|
||||
assert.ok(captured.sqlText.includes("oi.sku_type = 'combine'"), '缺少组合装行识别条件');
|
||||
// ③ 全民客户（B2B 分销）渠道普通行，排除拆单父单 Split 与问题单
|
||||
assert.ok(captured.sqlText.includes('FROM rpt.jst_qmcust_orderlist_item'), '缺少 qmcust 分支');
|
||||
assert.ok(captured.sqlText.includes("'Split', 'Question'"), 'qmcust 未排除拆单父单/问题单');
|
||||
// 四个分支共用同一发货窗口
|
||||
assert.equal(captured.sqlText.split('o.send_date >= @shipFrom').length, 5);
|
||||
});
|
||||
|
||||
test('gradeKey 缺失时兜底为 zero', async () => {
|
||||
const db = { query: async () => [{ wmsCoId: 101, binName: 'X', binType: '拣选', skuId: 'S1', stockQty: 5 }] };
|
||||
const rows = await fetchPickingBinSkuRows(db, [101], { shipFrom: 'a', shipTo: 'b', days: 15 });
|
||||
assert.equal(rows[0].gradeKey, 'zero');
|
||||
assert.equal(rows[0].salesQty, 0);
|
||||
assert.equal(rows[0].allocatedSalesQty, 0);
|
||||
assert.equal(rows[0].dailySales, 0);
|
||||
assert.equal(rows[0].skuId, 'S1');
|
||||
});
|
||||
@ -1,149 +0,0 @@
|
||||
'use strict';
|
||||
|
||||
const test = require('node:test');
|
||||
const assert = require('node:assert/strict');
|
||||
|
||||
const {
|
||||
buildGradeCase,
|
||||
buildInClause,
|
||||
fetchGradeRows,
|
||||
fetchZeroSaleSkuRows,
|
||||
} = require('../src/services/stockSalesAnalysis');
|
||||
const { SALES_GRADE_RULES } = require('../src/config/stockSalesAnalysis');
|
||||
|
||||
test('buildInClause 按位展开仓库参数', () => {
|
||||
const { clause, params } = buildInClause([101, 102], 'w');
|
||||
assert.equal(clause, '@w0,@w1');
|
||||
assert.deepEqual(params, { w0: 101, w1: 102 });
|
||||
});
|
||||
|
||||
test('buildGradeCase 覆盖全部正向等级，并以销售=0 兜底', () => {
|
||||
const expr = buildGradeCase();
|
||||
SALES_GRADE_RULES.filter((rule) => rule.lower > 0).forEach((rule) => {
|
||||
assert.ok(expr.includes(`THEN '${rule.key}'`), `${rule.key} 未出现在分档表达式中`);
|
||||
});
|
||||
assert.ok(expr.includes("THEN 'slow2'"));
|
||||
assert.ok(expr.includes("ELSE 'zero'"));
|
||||
});
|
||||
|
||||
test('fetchGradeRows 首参不是数据库实例时抛错，避免静默返回空数组', async () => {
|
||||
await assert.rejects(
|
||||
() => fetchGradeRows({}, [101], { shipFrom: 'a', shipTo: 'b', days: 30 }),
|
||||
TypeError
|
||||
);
|
||||
});
|
||||
|
||||
test('fetchGradeRows 无仓库或缺失窗口时直接返回空结果', async () => {
|
||||
let called = 0;
|
||||
const db = { query: async () => { called += 1; return []; } };
|
||||
assert.deepEqual(await fetchGradeRows(db, [], { shipFrom: 'a', shipTo: 'b', days: 30 }), []);
|
||||
assert.deepEqual(await fetchGradeRows(db, [101], { shipFrom: null, shipTo: 'b', days: 30 }), []);
|
||||
assert.equal(called, 0);
|
||||
});
|
||||
|
||||
test('fetchGradeRows 把仓库参数与窗口参数一并传给业务库', async () => {
|
||||
let captured = null;
|
||||
const db = {
|
||||
query: async (sqlText, params) => {
|
||||
captured = { sqlText, params };
|
||||
return [
|
||||
{ wmsCoId: 101, gradeKey: 'hot', skuCount: 2, stockQty: 438, salesQty: 1136, dailySales: 37.87 },
|
||||
];
|
||||
},
|
||||
};
|
||||
|
||||
const rows = await fetchGradeRows(db, [101, 102], {
|
||||
shipFrom: '2026-08-28 01:00:00',
|
||||
shipTo: '2026-09-27 01:00:00',
|
||||
days: 30,
|
||||
});
|
||||
|
||||
assert.equal(rows.length, 1);
|
||||
assert.equal(rows[0].wmsCoId, '101');
|
||||
assert.equal(rows[0].stockQty, 438);
|
||||
|
||||
assert.equal(captured.params.w0, 101);
|
||||
assert.equal(captured.params.w1, 102);
|
||||
assert.equal(captured.params.v0, 101);
|
||||
assert.equal(captured.params.days, 30);
|
||||
assert.equal(captured.params.shipFrom, '2026-08-28 01:00:00');
|
||||
assert.equal(captured.params.shipTo, '2026-09-27 01:00:00');
|
||||
assert.ok(captured.sqlText.includes('@days'));
|
||||
assert.ok(captured.sqlText.includes('rpt.jst_inventoryInfo'));
|
||||
assert.ok(captured.sqlText.includes('rpt.jst_OrderItem'));
|
||||
});
|
||||
|
||||
test('fetchZeroSaleSkuRows 首参不是数据库实例时抛错，避免静默返回空数组', async () => {
|
||||
await assert.rejects(
|
||||
() => fetchZeroSaleSkuRows({}, [101], { shipFrom: 'a', shipTo: 'b', days: 30 }),
|
||||
TypeError
|
||||
);
|
||||
});
|
||||
|
||||
test('fetchZeroSaleSkuRows 无仓库或缺失窗口时直接返回空结果', async () => {
|
||||
let called = 0;
|
||||
const db = { query: async () => { called += 1; return []; } };
|
||||
assert.deepEqual(await fetchZeroSaleSkuRows(db, [], { shipFrom: 'a', shipTo: 'b', days: 30 }), []);
|
||||
assert.deepEqual(await fetchZeroSaleSkuRows(db, [101], { shipFrom: 'a', shipTo: null, days: 30 }), []);
|
||||
assert.equal(called, 0);
|
||||
});
|
||||
|
||||
test('fetchZeroSaleSkuRows 复用同一分档口径并关联 SKU 名称', async () => {
|
||||
let captured = null;
|
||||
const db = {
|
||||
query: async (sqlText, params) => {
|
||||
captured = { sqlText, params };
|
||||
return [
|
||||
{ wmsCoId: 101, skuId: 'SKU-A', skuName: '款式A', binName: 'A01-01-1', stockQty: 7, salesQty: 0 },
|
||||
{ wmsCoId: 101, skuId: 'SKU-A', skuName: '款式A', binName: 'A02-03-1', stockQty: 5, salesQty: 0 },
|
||||
{ wmsCoId: 101, skuId: 'SKU-B', skuName: '款式B', binName: null, stockQty: 3, salesQty: 0 },
|
||||
];
|
||||
},
|
||||
};
|
||||
|
||||
const rows = await fetchZeroSaleSkuRows(db, [101, 102], {
|
||||
shipFrom: '2026-08-28 01:00:00',
|
||||
shipTo: '2026-09-27 01:00:00',
|
||||
days: 30,
|
||||
});
|
||||
|
||||
// 每个仓位独立一行；无仓位的 SKU 保留一行（仓位为空、库存取总库存）
|
||||
assert.equal(rows.length, 3);
|
||||
assert.equal(rows[0].wmsCoId, '101');
|
||||
assert.equal(rows[0].skuName, '款式A');
|
||||
assert.equal(rows[0].binName, 'A01-01-1');
|
||||
assert.equal(rows[0].stockQty, 7);
|
||||
assert.equal(rows[1].binName, 'A02-03-1');
|
||||
assert.equal(rows[1].stockQty, 5);
|
||||
assert.equal(rows[2].binName, '');
|
||||
assert.equal(rows[2].stockQty, 3);
|
||||
|
||||
// 口径必须与 fetchGradeRows 一致：同一段 gradeCase 表达式 + 同样的「有库存或有销量」过滤
|
||||
assert.ok(captured.sqlText.includes("ELSE 'zero'"));
|
||||
assert.ok(captured.sqlText.includes("g.gradeKey = 'zero'"));
|
||||
assert.ok(captured.sqlText.includes('rpt.jst_sku'));
|
||||
assert.ok(captured.sqlText.includes("NOT IN ('Delete', 'Cancelled')"));
|
||||
assert.equal(captured.params.w0, 101);
|
||||
assert.equal(captured.params.days, 30);
|
||||
|
||||
// 系统仓位：来自 rpt.jst_packInventoryInfo，按「仓库+SKU+仓位」聚合出仓位级库存，
|
||||
// 每仓位一行（COALESCE 兜底无仓位 SKU 取总库存），排除无仓位与零库存记录
|
||||
assert.ok(captured.sqlText.includes('rpt.jst_packInventoryInfo'));
|
||||
assert.ok(captured.sqlText.includes('COALESCE(bn.binQty, g.stockQty)'));
|
||||
assert.ok(captured.sqlText.includes('binName'));
|
||||
});
|
||||
|
||||
test('fetchZeroSaleSkuRows 的仓位必须按同一仓库匹配，避免跨仓错配', async () => {
|
||||
let captured = null;
|
||||
const db = {
|
||||
query: async (sqlText) => {
|
||||
captured = sqlText;
|
||||
return [];
|
||||
},
|
||||
};
|
||||
await fetchZeroSaleSkuRows(db, [101], {
|
||||
shipFrom: '2026-08-28 01:00:00', shipTo: '2026-09-27 01:00:00', days: 30,
|
||||
});
|
||||
assert.ok(captured.includes('bn.wmsCoId = g.wmsCoId AND bn.skuId = g.skuId'));
|
||||
assert.ok(captured.includes("ISNULL(p.qty, 0) <> 0"));
|
||||
});
|
||||
@ -1,667 +0,0 @@
|
||||
/**
|
||||
* 仓储中心 24 小时发货时效 —— 口径回归测试（2026-10-20 第八版）
|
||||
*
|
||||
* 这个功能最容易出错的是「口径」，不是 SQL 语法。本文件锁定几条关键语义：
|
||||
* ① 主仓归属用**关键词最长匹配** —— 「横林二仓品牌仓」不能被「横林二仓」抢走；
|
||||
* ② 核验轮次的时刻选择 —— 13:00 前**不做核验**、13:00~17:59 用 07:00 窗口、
|
||||
* 18:00 后用 16:00 窗口；「核验时刻」与「订单窗口上界」是两个字段；
|
||||
* ③ 数据源必须是 `jst_order_express_details`（聚水潭实时状态镜像）——
|
||||
* 订单表的 status 是下单快照，取消/售后/审核都不回写，用它必错；
|
||||
* ④ 🔥 窗口按**创建时间**卡 7:00 / 16:00（含历史未发），**已等时长按审核时间算**：
|
||||
* 「当日 7 点前订单（7 点前订单按照审核时间算），13:00 核验未发就算超时」。
|
||||
* ⚠️ 别把窗口卡到审核时间上 —— 审单集中在早上 8:30~10:00 批量做，
|
||||
* 卡审核时间 13:00 轮全库只剩 2 单（实测 29 单 → 2 单），等于把功能做废；
|
||||
* ⑤ 🔥 **没有「满 24 小时」门槛**：到核验时刻未发即超时。
|
||||
* 第七版加了 24h 门槛，13:00 轮永远看不到当天 7 点那批，被业务打回；
|
||||
* ⑥ 三态互斥：发货中+无发货时间=超时未发货 / 待审核·异常=不计考核 / 其余丢弃；
|
||||
* **作废单（已取消 / 合并 / 拆单父单）不考核**；
|
||||
* ⑦ 性能护栏：状态表只允许 **1 次** querySlow，不得投影宽列、不得回订单表补金额。
|
||||
*
|
||||
* ⚠️ 本文件**不连数据库**，纯逻辑测试。
|
||||
*/
|
||||
const test = require('node:test');
|
||||
const assert = require('node:assert/strict');
|
||||
|
||||
const registry = require('../src/services/warehouseShipTimelinessRegistry');
|
||||
|
||||
// ── ① 主仓归属：最长匹配 ────────────────────────────────────────────────
|
||||
test('resolveCenter 用最长关键词匹配，品牌仓不会被主仓抢走', () => {
|
||||
assert.equal(registry.resolveCenter('简尚-横林二仓品牌仓').key, 'HL2_BRAND');
|
||||
assert.equal(registry.resolveCenter('简尚-横林二仓').key, 'HL2');
|
||||
assert.equal(registry.resolveCenter('简尚-崔桥工厂品牌仓').key, 'CQ_BRAND');
|
||||
assert.equal(registry.resolveCenter('简尚-崔桥工厂仓').key, 'CQ');
|
||||
assert.equal(registry.resolveCenter('简尚-山东品牌仓').key, 'SD_BRAND');
|
||||
assert.equal(registry.resolveCenter('简尚-山东青岗集仓').key, 'SD_QGJ');
|
||||
});
|
||||
|
||||
test('resolveCenter 能捞到各种命名的子仓', () => {
|
||||
const cases = [
|
||||
['简尚-运营C横林二仓专用仓', 'HL2'],
|
||||
['简尚-横林二仓京东仓', 'HL2'],
|
||||
['京仓-横林二仓京东自营仓', 'HL2'],
|
||||
['简尚-崔桥工厂仓唯品仓', 'CQ'],
|
||||
['简尚-运营C崔桥工厂仓专用仓', 'CQ'],
|
||||
['简尚-新苏北临时仓', 'XSB'],
|
||||
['简尚-分销部睢宁专用仓', 'SN'],
|
||||
['京仓-山东青岗集京东仓储', 'SD_QGJ'],
|
||||
['简尚-山东青岗集仓马来海外仓', 'SD_QGJ'],
|
||||
['简尚-河南洛宁仓', 'HN_LN'],
|
||||
];
|
||||
for (const [name, expected] of cases) {
|
||||
assert.equal(registry.resolveCenter(name)?.key, expected, name);
|
||||
}
|
||||
});
|
||||
|
||||
test('「京仓-横林二仓京东云仓」业务指定排除，不计入横林二仓', () => {
|
||||
assert.equal(registry.resolveCenter('京仓-横林二仓京东云仓'), null);
|
||||
// ⚠️ 不能连带排掉名字相近的仓 —— 关键词必须写完整片段
|
||||
assert.equal(registry.resolveCenter('简尚-横林二仓京东仓')?.key, 'HL2');
|
||||
assert.equal(registry.resolveCenter('京仓-横林二仓京东自营仓')?.key, 'HL2');
|
||||
assert.equal(registry.resolveCenter('京仓-崔桥工厂仓京东云仓')?.key, 'CQ');
|
||||
assert.equal(registry.resolveCenter('京仓-山东青岗集京东云仓')?.key, 'SD_QGJ');
|
||||
});
|
||||
|
||||
test('resolveCenter 不会把无关代发仓误并入（山东/河南是高频前缀）', () => {
|
||||
const shouldBeNull = [
|
||||
'工厂-山东菏泽森美代发仓',
|
||||
'工厂-山东恒思代发仓',
|
||||
'工厂-河南千优代发仓',
|
||||
'工厂-河北霸州派雅世佳代发仓',
|
||||
'简尚-苏州福利品仓',
|
||||
];
|
||||
for (const name of shouldBeNull) {
|
||||
assert.equal(registry.resolveCenter(name), null, `${name} 不应归属任何主仓`);
|
||||
}
|
||||
});
|
||||
|
||||
test('崔桥工厂半成品包装项目仓已接入（不再是占位仓）', () => {
|
||||
const c = registry.CENTERS.find((x) => x.key === 'CQ_WIP');
|
||||
assert.ok(c, 'CQ_WIP 必须存在');
|
||||
assert.equal(c.placeholder, undefined, '已接入真实仓，不能再是占位仓');
|
||||
assert.equal(c.name, '崔桥工厂半成品包装项目仓');
|
||||
assert.equal(registry.resolveCenter('简尚-崔桥工厂半成品包装项目仓')?.key, 'CQ_WIP');
|
||||
assert.equal(registry.resolveCenter('简尚-崔桥工厂仓')?.key, 'CQ');
|
||||
assert.equal(registry.resolveCenter('简尚-崔桥工厂品牌仓')?.key, 'CQ_BRAND');
|
||||
});
|
||||
|
||||
// ── ② 核验轮次 ──────────────────────────────────────────────────────────
|
||||
const at = (h, m) => new Date(2026, 9, 20, h, m, 0); // 2026-10-20 本机时区（东八区）
|
||||
|
||||
test('13:00 前不做核验，返回 null（不回填昨日数据）', () => {
|
||||
assert.equal(registry.resolveActiveRound(at(9, 30)), null);
|
||||
assert.equal(registry.resolveActiveRound(at(12, 59)), null);
|
||||
assert.equal(registry.resolveActiveRound(at(0, 5)), null);
|
||||
});
|
||||
|
||||
test('13:00~17:59 用 13:00 轮，窗口是「截止今日 07:00 前创建（含历史）」', () => {
|
||||
for (const [h, m] of [[13, 0], [15, 30], [17, 59]]) {
|
||||
const r = registry.resolveActiveRound(at(h, m));
|
||||
assert.ok(r, `${h}:${m} 应已进入首轮核验`);
|
||||
assert.equal(r.key, 'NOON');
|
||||
// 核验时刻 = 13:00（判定「发了没发 / 超时多久」用它）
|
||||
assert.equal(r.deadline, '2026-10-20 13:00:00');
|
||||
assert.equal(r.verifyHour, 13);
|
||||
// 订单窗口上界 = 07:00（只核验该时刻前创建的单）
|
||||
assert.equal(r.windowEnd, '2026-10-20 07:00:00');
|
||||
assert.notEqual(r.deadline, r.windowEnd, '核验时刻与窗口上界必须是两个值');
|
||||
assert.equal(r.includeHistory, true);
|
||||
assert.notEqual(r.windowStart, '2026-10-20 00:00:00', '下界不能卡在当天 00:00');
|
||||
assert.equal(r.windowStart, '2026-09-20 00:00:00', '下界是近 30 天');
|
||||
}
|
||||
});
|
||||
|
||||
test('18:00 之后用 18:00 轮，窗口上界扩到当天 16:00', () => {
|
||||
const r = registry.resolveActiveRound(at(18, 0));
|
||||
assert.equal(r.key, 'AFTERNOON');
|
||||
assert.equal(r.deadline, '2026-10-20 18:00:00');
|
||||
assert.equal(r.windowEnd, '2026-10-20 16:00:00');
|
||||
assert.equal(registry.resolveActiveRound(at(23, 59)).key, 'AFTERNOON');
|
||||
});
|
||||
|
||||
test('describeRounds 两轮的核验时刻与窗口上界（16:00~17:59 属于「等 18:00 轮」）', () => {
|
||||
const rounds = registry.describeRounds(at(16, 5));
|
||||
assert.deepEqual(
|
||||
rounds.map((r) => [r.key, r.deadline.slice(11, 16), r.windowEnd.slice(11, 16)]),
|
||||
[['NOON', '13:00', '07:00'], ['AFTERNOON', '18:00', '16:00']]
|
||||
);
|
||||
assert.equal(rounds[0].active, true);
|
||||
assert.equal(rounds[1].active, false, '16:05 还没到 18:00 轮');
|
||||
assert.equal(registry.resolveActiveRound(at(16, 5)).key, 'NOON');
|
||||
});
|
||||
|
||||
test('审核晚于本轮核验时刻 → 顺延到下一轮核验时刻', () => {
|
||||
const [noon, afternoon] = registry.describeRounds(at(16, 5));
|
||||
assert.equal(registry.nextRoundDeadline(noon), '2026-10-20 18:00:00', '13:00 轮 → 当天 18:00');
|
||||
assert.equal(registry.nextRoundDeadline(afternoon), '2026-10-21 13:00:00',
|
||||
'18:00 是当天最后一轮 → 次日 13:00');
|
||||
// 跨月边界也要对
|
||||
assert.equal(
|
||||
registry.nextRoundDeadline({ key: 'AFTERNOON', date: '2026-10-31' }),
|
||||
'2026-11-01 13:00:00'
|
||||
);
|
||||
});
|
||||
|
||||
// ── ③ 常量口径 ──────────────────────────────────────────────────────────
|
||||
test('数据源必须是聚水潭实时状态表，不是订单表', () => {
|
||||
assert.equal(registry.ORDER_STATE_TABLE, 'jst_order_express_details');
|
||||
});
|
||||
|
||||
test('三态名称；24 小时常量仅用于页面命名，不再参与判定', () => {
|
||||
assert.equal(registry.SHIPPING_STATUS, '发货中');
|
||||
assert.equal(registry.UNAUDITED_STATUS, '已支付待审核');
|
||||
assert.equal(registry.ABNORMAL_STATUS, '异常');
|
||||
// 页面/路由仍叫「24 小时发货时效」，但判定是 13:00/18:00 到点即超时
|
||||
assert.equal(registry.SHIP_TIMELINESS_HOURS, 24);
|
||||
});
|
||||
|
||||
test('作废单（已取消）明确不考核', () => {
|
||||
assert.ok(
|
||||
registry.IGNORED_STATES.includes('已取消'),
|
||||
'「已取消」必须在排除名单里 —— 近 30 天 6.4 万单，是「发货中」的 26 倍'
|
||||
);
|
||||
assert.ok(registry.IGNORED_STATES.includes('已发货'));
|
||||
assert.ok(registry.IGNORED_STATES.includes('等供销商|外仓发货'));
|
||||
});
|
||||
|
||||
test('创建时间要从订单表补，且只补窄列', () => {
|
||||
assert.deepEqual(
|
||||
[...registry.CREATED_SOURCE_TABLES],
|
||||
['jst_Orders', 'jst_qmcust_orderlist'],
|
||||
'两张订单表都要查（店铺互斥，交集为 0）'
|
||||
);
|
||||
assert.ok(registry.CREATED_BACKFILL_BATCH >= 100, '必须分批，不能一次 IN 上万个');
|
||||
});
|
||||
|
||||
// ── ④ 服务层分桶（注入假查询，不连库）──
|
||||
function stubDb(dbPath, scenario = 'default') {
|
||||
const wmsId = 15038426;
|
||||
|
||||
// 创建时间（展示）+ 作废事实来源：o_id → 订单表行
|
||||
// 故意让 3 号单**补不到**（模拟订单表缺行）→ 展示回退付款时间
|
||||
const f = (table, o) => ({ table, status: 'WaitConfirm', send_date: null, is_merge: 0, is_split: 0, ...o });
|
||||
|
||||
const defaultFacts = {
|
||||
1: f('jst_Orders', { created: '2026-09-25 00:50:00' }),
|
||||
2: f('jst_Orders', { created: '2026-10-20 16:20:00' }),
|
||||
6: f('jst_Orders', { created: '2026-10-20 17:00:00' }),
|
||||
7: f('jst_qmcust_orderlist', { created: '2026-09-25 01:00:00' }),
|
||||
9: f('jst_Orders', { created: '2026-09-21 09:00:00', status: 'Cancelled' }),
|
||||
// 10：状态表「发货中 + send_time 空」，但订单表是 Merged —— 真实案例
|
||||
// 5127276315127080023（内部单号 9486414）就是这样被误判成超时的
|
||||
10: f('jst_qmcust_orderlist', { created: '2026-09-21 10:00:00', status: 'Merged', send_date: '2026-09-22 06:54:49' }),
|
||||
// 11：状态表 send_time 空，订单表 send_date 有值（已发）
|
||||
11: f('jst_Orders', { created: '2026-09-21 11:00:00', send_date: '2026-09-22 08:00:00' }),
|
||||
// 37：🔥 订单表 send_date 没回写，但销售订单 status 已是 Sent（已发货）
|
||||
// —— 业务 2026-10-20「已发/未发参考聚水潭销售订单页面」
|
||||
37: f('jst_Orders', { created: '2026-09-22 09:00:00', status: 'Sent' }),
|
||||
// 12：拆单父单，status 不是 Split 但 is_split=1
|
||||
12: f('jst_Orders', { created: '2026-09-21 12:00:00', status: 'Delivering', is_split: 1 }),
|
||||
13: f('jst_Orders', { created: '2026-10-20 15:00:00' }),
|
||||
// 31~34：验证仓级例外窗口（山东两仓 15:00、河南洛宁 13:00，仅 18:00 轮）
|
||||
31: f('jst_Orders', { created: '2026-10-20 15:30:00' }),
|
||||
32: f('jst_Orders', { created: '2026-10-20 14:30:00' }),
|
||||
33: f('jst_Orders', { created: '2026-10-20 13:30:00' }),
|
||||
34: f('jst_Orders', { created: '2026-10-20 12:30:00' }),
|
||||
// 26：创建 10-18，但**今天 13:10 才审核** —— 业务点名的形态（9818476）
|
||||
// 只能进 18:00 轮，不能进 13:00 轮
|
||||
26: f('jst_Orders', { created: '2026-10-18 12:00:00' }),
|
||||
// 25：重审单（首次 10-19 10:10 / 最后一次 10-20 13:30）—— 聚水潭显示 13:30
|
||||
25: f('jst_Orders', { created: '2026-10-19 10:00:00' }),
|
||||
};
|
||||
|
||||
// 13:00 轮场景：验证「窗口按创建时间卡 7 点、时长按审核时间算」
|
||||
const noonFacts = {
|
||||
21: f('jst_Orders', { created: '2026-10-20 06:45:00' }),
|
||||
22: f('jst_Orders', { created: '2026-10-20 05:55:00' }),
|
||||
23: f('jst_Orders', { created: '2026-10-19 19:55:00' }),
|
||||
24: f('jst_Orders', { created: '2026-10-20 07:30:00' }),
|
||||
// 25：重审单（首次审核 10-19 10:10、最后一次 10-20 13:30）—— 时长要按首次算
|
||||
25: f('jst_Orders', { created: '2026-10-19 10:00:00' }),
|
||||
// 26：今天 13:10 才审（晚于核验时刻 13:00）—— 已等时长要回退按创建时间算
|
||||
26: f('jst_Orders', { created: '2026-10-18 12:00:00' }),
|
||||
};
|
||||
|
||||
const factsMap = scenario === 'noon' ? noonFacts : defaultFacts;
|
||||
|
||||
const mk = (o) => ({
|
||||
shop_name: '测试店',
|
||||
logistic_status_name: '',
|
||||
query_time: '2026-10-20 11:18:27',
|
||||
// 默认首次审核 = 最后一次审核；需要区分重审的用例显式覆盖 first_oa_confirm_time
|
||||
first_oa_confirm_time: o.last_oa_confirm_time ?? null,
|
||||
...o,
|
||||
});
|
||||
|
||||
const defaultRows = [
|
||||
// 1：审核 09-25 01:00 → 到 18:00 核验 = 25 天 17 小时，超时
|
||||
mk({ so_id: 'SO-1', inner_order_id: 1, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-09-24 23:50:00',
|
||||
last_oa_confirm_time: '2026-09-25 01:00:00' }),
|
||||
// 2：创建 16:20 晚于窗口上界 16:00 → 本轮不核验（窗口卡的是创建时间）
|
||||
mk({ so_id: 'SO-2', inner_order_id: 2, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-10-20 16:10:00',
|
||||
last_oa_confirm_time: '2026-10-20 16:30:00' }),
|
||||
// 3：订单表补不到创建时间 → 展示回退付款时间；审核 09-26 00:15 仍应判超时
|
||||
mk({ so_id: 'SO-3', inner_order_id: 3, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-09-26 00:10:00',
|
||||
last_oa_confirm_time: '2026-09-26 00:15:00' }),
|
||||
// 4：已支付待审核（还没审单、没有审核时间）→ 不计考核
|
||||
mk({ so_id: 'SO-4', inner_order_id: 4, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '已支付待审核', pay_time: '2026-09-23 01:00:00',
|
||||
last_oa_confirm_time: null }),
|
||||
// 5：异常 → 不计考核
|
||||
mk({ so_id: 'SO-5', inner_order_id: 5, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '异常', logistic_status_name: '常州安能新', pay_time: '2026-09-23 01:00:00',
|
||||
last_oa_confirm_time: '2026-09-23 01:05:00' }),
|
||||
// 6：审核 17:05 晚于窗口上界 → 本轮不该核验
|
||||
mk({ so_id: 'SO-6', inner_order_id: 6, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-10-20 16:55:00',
|
||||
last_oa_confirm_time: '2026-10-20 17:05:00' }),
|
||||
// 7：被业务排除的京东云仓 → 不归属任何主仓
|
||||
mk({ so_id: 'SO-7', inner_order_id: 7, warehouse_name: '京仓-横林二仓京东云仓',
|
||||
order_status_name: '发货中', pay_time: '2026-09-25 00:00:00',
|
||||
last_oa_confirm_time: '2026-09-25 00:10:00' }),
|
||||
// 8：与 1 同 so_id + 同基准时间（拆包重复行）→ 必须去重
|
||||
mk({ so_id: 'SO-1', inner_order_id: 1, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-09-24 23:50:00',
|
||||
last_oa_confirm_time: '2026-09-25 01:00:00' }),
|
||||
// 9：作废单（已取消）—— 业务定性不考核
|
||||
mk({ so_id: 'SO-9', inner_order_id: 9, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '已取消', pay_time: '2026-09-21 08:00:00',
|
||||
last_oa_confirm_time: '2026-09-21 08:10:00' }),
|
||||
// 10：状态表「发货中」、但订单表是 Merged + 已发 —— 必须剔除
|
||||
mk({ so_id: 'SO-10', inner_order_id: 10, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-09-21 09:59:00',
|
||||
last_oa_confirm_time: '2026-09-21 10:05:00' }),
|
||||
// 11：状态表「发货中」、订单表 send_date 有值（已发）—— 必须剔除
|
||||
mk({ so_id: 'SO-11', inner_order_id: 11, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-09-21 10:59:00',
|
||||
last_oa_confirm_time: '2026-09-21 11:05:00' }),
|
||||
// 12：拆单父单（is_split=1）—— 自己不发货，必须剔除
|
||||
mk({ so_id: 'SO-12', inner_order_id: 12, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-09-21 11:59:00',
|
||||
last_oa_confirm_time: '2026-09-21 12:05:00' }),
|
||||
// 13：🔥 当天 15:30 审核、18:00 核验只等了 2.5 小时 —— 旧版 24h 门槛会漏掉，
|
||||
// 本版必须算超时（业务口径：到点未发就算超时）
|
||||
mk({ so_id: 'SO-13', inner_order_id: 13, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-10-20 14:59:00',
|
||||
last_oa_confirm_time: '2026-10-20 15:30:00' }),
|
||||
// ── 仓级例外窗口（18:00 轮）：山东两仓 15:00、河南洛宁 13:00 ──
|
||||
// 31：山东青岗集仓 15:30 创建 → 晚于该仓 15:00 上界 → 本轮不核验
|
||||
mk({ so_id: 'SO-31', inner_order_id: 31, warehouse_name: '简尚-山东青岗集仓',
|
||||
order_status_name: '发货中', pay_time: '2026-10-20 15:29:00',
|
||||
last_oa_confirm_time: '2026-10-20 15:35:00' }),
|
||||
// 32：山东品牌仓 14:30 创建 → 早于 15:00 上界 → 核验，且超时
|
||||
mk({ so_id: 'SO-32', inner_order_id: 32, warehouse_name: '简尚-山东品牌仓',
|
||||
order_status_name: '发货中', pay_time: '2026-10-20 14:29:00',
|
||||
last_oa_confirm_time: '2026-10-20 14:35:00' }),
|
||||
// 33：河南洛宁仓 13:30 创建 → 晚于该仓 13:00 上界 → 本轮不核验
|
||||
mk({ so_id: 'SO-33', inner_order_id: 33, warehouse_name: '简尚-河南洛宁仓',
|
||||
order_status_name: '发货中', pay_time: '2026-10-20 13:29:00',
|
||||
last_oa_confirm_time: '2026-10-20 13:35:00' }),
|
||||
// 34：河南洛宁仓 12:30 创建 → 早于 13:00 上界 → 核验，且超时
|
||||
mk({ so_id: 'SO-34', inner_order_id: 34, warehouse_name: '简尚-河南洛宁仓',
|
||||
order_status_name: '发货中', pay_time: '2026-10-20 12:29:00',
|
||||
last_oa_confirm_time: '2026-10-20 12:35:00' }),
|
||||
// 26：🔥 业务点名的形态 —— 创建 10-18，但今天 13:10 才审核（9818476 就是这样）。
|
||||
// 它属于 18:00 轮（13:10 ≤ 16:00），已等 = 18:00 − 13:10 = 290 分
|
||||
mk({ so_id: 'SO-26', inner_order_id: 26, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-10-18 11:59:00',
|
||||
first_oa_confirm_time: '2026-10-20 13:10:00',
|
||||
last_oa_confirm_time: '2026-10-20 13:10:00' }),
|
||||
// 25：重审单 —— 聚水潭「审核时间」显示最后一次 10-20 13:30（不是首次 10-19 10:10）
|
||||
mk({ so_id: 'SO-25', inner_order_id: 25, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-10-19 09:59:00',
|
||||
first_oa_confirm_time: '2026-10-19 10:10:00',
|
||||
last_oa_confirm_time: '2026-10-20 13:30:00' }),
|
||||
// 35/36：🔥 不考核快递（业务 2026-10-20）：中铁物流、壹米滴答专线 —— 一律跳过。
|
||||
// 这两单状态/时间都够超时，靠快递名剔除，同时计入 summary.carrierSkipped
|
||||
mk({ so_id: 'SO-35', inner_order_id: 35, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-09-25 01:00:00',
|
||||
last_oa_confirm_time: '2026-09-25 01:30:00', logistic_company_name: '中铁物流' }),
|
||||
mk({ so_id: 'SO-36', inner_order_id: 36, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-09-25 02:00:00',
|
||||
last_oa_confirm_time: '2026-09-25 02:30:00', logistic_company_name: '壹米滴答专线' }),
|
||||
// 37：销售订单 status=Sent（已发货），状态表还是「发货中 + send_time 空」→ 必须剔除
|
||||
mk({ so_id: 'SO-37', inner_order_id: 37, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-09-22 08:50:00',
|
||||
last_oa_confirm_time: '2026-09-22 09:05:00' }),
|
||||
];
|
||||
|
||||
// 13:00 轮：窗口上界 07:00（按创建时间），核验时刻 13:00
|
||||
const noonRows = [
|
||||
// 21：创建 06:45（7 点前）+ 审核 07:20 → 进 13:00 轮；已等 = 13:00 − 07:20 = 340 分
|
||||
mk({ so_id: 'SO-21', inner_order_id: 21, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-10-20 06:40:00',
|
||||
last_oa_confirm_time: '2026-10-20 07:20:00' }),
|
||||
// 22：创建 05:55 + 审核 06:40 → 13:00 核验只等 380 分钟，也必须算超时（无 24h 门槛）
|
||||
mk({ so_id: 'SO-22', inner_order_id: 22, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-10-20 05:50:00',
|
||||
last_oa_confirm_time: '2026-10-20 06:40:00' }),
|
||||
// 23：昨天创建、至今未发（历史未发池）→ 13:00 轮也要看到
|
||||
mk({ so_id: 'SO-23', inner_order_id: 23, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-10-19 19:50:00',
|
||||
last_oa_confirm_time: '2026-10-19 20:10:00' }),
|
||||
// 24：创建 07:30 晚于窗口上界 07:00 → 本轮不核验（窗口卡的是创建时间）
|
||||
mk({ so_id: 'SO-24', inner_order_id: 24, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-10-20 07:29:00',
|
||||
last_oa_confirm_time: '2026-10-20 07:40:00' }),
|
||||
// 25：🔥 被「重新审核」过的单：首次审核 10-19 10:10、最后一次 10-20 13:30。
|
||||
// 时长必须按**首次**审核算（1610 分），用 last 会算成 0 分
|
||||
mk({ so_id: 'SO-25', inner_order_id: 25, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-10-19 09:59:00',
|
||||
first_oa_confirm_time: '2026-10-19 10:10:00',
|
||||
last_oa_confirm_time: '2026-10-20 13:30:00' }),
|
||||
// 26：🔥 今天 13:10 才审（晚于核验时刻 13:00）→ 已等时长回退按创建时间算，
|
||||
// 不能显示 0 分（真实案例：创建 10-18 的单今天才审）
|
||||
mk({ so_id: 'SO-26', inner_order_id: 26, warehouse_name: '简尚-崔桥工厂仓',
|
||||
order_status_name: '发货中', pay_time: '2026-10-18 11:59:00',
|
||||
first_oa_confirm_time: '2026-10-20 13:10:00',
|
||||
last_oa_confirm_time: '2026-10-20 13:10:00' }),
|
||||
];
|
||||
|
||||
const rows = scenario === 'noon' ? noonRows : defaultRows;
|
||||
|
||||
const calls = { state: 0, backfill: 0, sql: [], backfillSql: [], params: [] };
|
||||
|
||||
const handler = async (sql, params) => {
|
||||
const text = String(sql);
|
||||
if (/jst_warehouseInfo/u.test(text)) {
|
||||
return [
|
||||
{ Id: 1, name: '简尚-崔桥工厂仓', wms_co_id: wmsId },
|
||||
{ Id: 2, name: '简尚-山东青岗集仓', wms_co_id: 15137523 },
|
||||
{ Id: 3, name: '简尚-山东品牌仓', wms_co_id: 15182705 },
|
||||
{ Id: 4, name: '简尚-河南洛宁仓', wms_co_id: 15539084 },
|
||||
];
|
||||
}
|
||||
// 补「起算点 + 作废事实」：按 o_id 分批 IN 两张订单表
|
||||
if (/FROM dbo\.(jst_Orders|jst_qmcust_orderlist)/u.test(text)) {
|
||||
calls.backfill += 1;
|
||||
calls.backfillSql.push(text);
|
||||
const table = /jst_qmcust_orderlist/u.test(text) ? 'jst_qmcust_orderlist' : 'jst_Orders';
|
||||
const m = text.match(/IN \(([0-9,\s]+)\)/u);
|
||||
const ids = m ? m[1].split(',').map((s) => Number(s.trim())) : [];
|
||||
return ids
|
||||
.filter((id) => factsMap[id] && factsMap[id].table === table)
|
||||
.map((id) => {
|
||||
const x = factsMap[id];
|
||||
return {
|
||||
o_id: id,
|
||||
created: x.created,
|
||||
status: x.status,
|
||||
send_date: x.send_date,
|
||||
is_merge: x.is_merge,
|
||||
is_split: x.is_split,
|
||||
};
|
||||
});
|
||||
}
|
||||
calls.state += 1;
|
||||
calls.sql.push(text);
|
||||
calls.params.push(params || {});
|
||||
return rows;
|
||||
};
|
||||
|
||||
require.cache[dbPath] = {
|
||||
id: dbPath,
|
||||
filename: dbPath,
|
||||
loaded: true,
|
||||
exports: { query: handler, querySlow: handler },
|
||||
};
|
||||
return { calls, wmsId };
|
||||
}
|
||||
|
||||
function withStubbedService(fn, scenario = 'default') {
|
||||
return async () => {
|
||||
const dbPath = require.resolve('../src/config/cloudDatabase');
|
||||
const realDb = require.cache[dbPath];
|
||||
const ctx = stubDb(dbPath, scenario);
|
||||
delete require.cache[require.resolve('../src/services/warehouseShipTimelinessService')];
|
||||
delete require.cache[require.resolve('../src/services/warehouseShipTimelinessRegistry')];
|
||||
try {
|
||||
const svc = require('../src/services/warehouseShipTimelinessService');
|
||||
await fn(svc, ctx);
|
||||
} finally {
|
||||
if (realDb) require.cache[dbPath] = realDb;
|
||||
else delete require.cache[dbPath];
|
||||
delete require.cache[require.resolve('../src/services/warehouseShipTimelinessService')];
|
||||
delete require.cache[require.resolve('../src/services/warehouseShipTimelinessRegistry')];
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
test('服务层三态分流：超时未发货 / 不计考核 / 丢弃', withStubbedService(async (svc, { calls }) => {
|
||||
// 18:05 → 18:00 轮：窗口上界 16:00（按审核时间），核验时刻 18:00
|
||||
const data = await svc.getShipTimeliness({ now: at(18, 5), limit: 10 });
|
||||
const c = data.centers.find((x) => x.key === 'CQ');
|
||||
assert.ok(c, '应能归到崔桥工厂仓');
|
||||
|
||||
// 超时 = 1（09-25 审核）+ 3（补不到创建时间）+ 13（15:30 审核，只等 2.5 小时）
|
||||
// + 32（山东品牌仓 14:30）+ 34（河南洛宁 12:30）+ 26（今天 13:10 审核）
|
||||
// = 6 单
|
||||
// 2/6 今天审核晚于 16:00、4/5 不计考核、7 非主仓、8 去重、9~12 作废/已发
|
||||
// 31/33 是仓级例外窗口（山东 15:00 / 河南洛宁 13:00）挡掉的
|
||||
assert.equal(c.overdueUnshipped, 5, '1、3、13、26、25 五单算超时');
|
||||
assert.equal(c.oldestDays, 25, '最久一单 09-25 01:00 审核，到 18:00 核验是 25 天');
|
||||
assert.equal(c.heldCount, 2, '待审核 + 异常各 1 单');
|
||||
|
||||
assert.equal(data.summary.overdueUnshipped, 7);
|
||||
assert.equal(data.summary.overdueCenterCount, 3);
|
||||
assert.equal(data.summary.oldestDays, 25);
|
||||
assert.equal(data.summary.heldCount, 2);
|
||||
|
||||
// 明细：最久的排最前；基准时间是**审核时间**，创建时间只展示
|
||||
assert.equal(data.orders.length, 7);
|
||||
assert.equal(String(data.orders[0].oId), '1');
|
||||
assert.equal(data.orders[0].auditTime, '2026-09-25 01:00:00', '基准是审核时间');
|
||||
assert.equal(data.orders[0].createdAt, '2026-09-25 00:50:00', '创建时间只作展示');
|
||||
assert.equal(data.orders[0].payTime, '2026-09-24 23:50:00');
|
||||
assert.equal(data.orders[0].benchmarkSource, 'last_audit');
|
||||
// 09-25 01:00 → 10-20 18:00 = 25 天 + 17 小时 = 37020 分钟
|
||||
assert.equal(data.orders[0].overdueMinutes, 37020);
|
||||
|
||||
// 13 号单：15:30 审核 → 18:00 核验只等了 150 分钟，旧版 24h 门槛会漏，本版必须算
|
||||
const fresh = data.orders.find((o) => String(o.oId) === '13');
|
||||
assert.ok(fresh, '只等 2.5 小时也必须算超时（无 24h 门槛）');
|
||||
assert.equal(fresh.overdueMinutes, 150);
|
||||
assert.equal(fresh.waitedHours, 2.5);
|
||||
|
||||
// 26 号单：创建 10-18、今天 13:10 才审核 → 属于 18:00 轮，已等 = 18:00 − 13:10 = 290
|
||||
const lateAudit = data.orders.find((o) => String(o.oId) === '26');
|
||||
assert.ok(lateAudit, '下午才审核的老单要进 18:00 轮（不能因为创建早就算进 13:00 轮）');
|
||||
assert.equal(lateAudit.overdueMinutes, 290);
|
||||
|
||||
// 25 号：重审单 → 审核时间必须显示**最后一次**（13:30，与聚水潭一致），不是首次 10:10
|
||||
const reAudited = data.orders.find((o) => String(o.oId) === '25');
|
||||
assert.ok(reAudited, '重审单也要算');
|
||||
assert.equal(reAudited.auditTime, '2026-10-20 13:30:00', '聚水潭「审核时间」= 最后一次审核');
|
||||
assert.equal(reAudited.overdueMinutes, 270, '18:00 − 13:30');
|
||||
|
||||
// 3 号单订单表补不到 created，展示回退付款时间，超时判定仍用审核时间
|
||||
const third = data.orders.find((o) => String(o.oId) === '3');
|
||||
assert.ok(third, '补不到创建时间的单也要算超时');
|
||||
assert.equal(third.createdAt, '', '确实没补到');
|
||||
assert.equal(third.benchmarkSource, 'last_audit');
|
||||
assert.equal(third.payTime, '2026-09-26 00:10:00');
|
||||
|
||||
// 创建时间晚于窗口上界 → 本轮不核验（2 号：创建 16:20、6 号：创建 17:00）
|
||||
assert.ok(!data.orders.some((o) => String(o.oId) === '2'), '创建 16:20 晚于 16:00 本轮不核验');
|
||||
assert.ok(!data.orders.some((o) => String(o.oId) === '6'), '创建 17:00 晚于 16:00 本轮不核验');
|
||||
|
||||
// ── 仓级例外窗口（业务 2026-10-20：山东两仓 15:00、河南洛宁 13:00）──
|
||||
assert.ok(!data.orders.some((o) => String(o.oId) === '31'),
|
||||
'山东青岗集仓 15:30 创建 → 晚于该仓 15:00 上界，18:00 轮不核验');
|
||||
assert.ok(data.orders.some((o) => String(o.oId) === '32'),
|
||||
'山东品牌仓 14:30 创建 → 早于该仓 15:00 上界，要核验');
|
||||
assert.ok(!data.orders.some((o) => String(o.oId) === '33'),
|
||||
'河南洛宁仓 13:30 创建 → 晚于该仓 13:00 上界，18:00 轮不核验');
|
||||
assert.ok(data.orders.some((o) => String(o.oId) === '34'),
|
||||
'河南洛宁仓 12:30 创建 → 早于该仓 13:00 上界，要核验');
|
||||
assert.equal(data.window.overrides.length, 3, '山东两仓 + 河南洛宁 三处例外');
|
||||
assert.deepEqual(
|
||||
data.window.overrides.map((o) => [o.key, o.hour]).sort(),
|
||||
[['HN_LN', 13], ['SD_BRAND', 15], ['SD_QGJ', 15]]
|
||||
);
|
||||
// 例外只作用在 18:00 轮；13:00 轮没有例外（见下一个用例）
|
||||
assert.match(data.window.overrides.find((o) => o.key === 'HN_LN').windowEnd, /13:00:00$/u);
|
||||
// 被排除的仓不能算
|
||||
assert.ok(!data.orders.some((o) => String(o.oId) === '7'), '京东云仓不参与考核');
|
||||
// 9(状态表已取消) / 10(Merged) / 11(已发) / 12(拆单父单) 都不能进任何清单
|
||||
for (const id of ['9', '10', '11', '12']) {
|
||||
assert.ok(!data.orders.some((o) => String(o.oId) === id), `o_id=${id} 不该进超时明细`);
|
||||
assert.ok(!data.heldOrders.some((o) => String(o.oId) === id), `o_id=${id} 不该进挂起清单`);
|
||||
}
|
||||
// 这 5 单要计进 voidCount（9/10/11/12 作废或已发 + 37 销售订单已发货 Sent）
|
||||
assert.equal(data.summary.voidCount, 5, '作废/已发单要计入剔除数');
|
||||
|
||||
// 不考核快递：中铁物流、壹米滴答专线必须整单跳过（业务 2026-10-20）
|
||||
assert.equal(data.summary.carrierSkipped, 2, '自提/中铁/壹米滴答 要计入 carrierSkipped');
|
||||
assert.ok(
|
||||
!data.orders.some((o) => ['SO-35', 'SO-36'].includes(o.soId)),
|
||||
'不考核快递的单不能出现在超时明细里'
|
||||
);
|
||||
assert.deepEqual(data.excludedCarriers, ['自提', '中铁', '壹米滴答']);
|
||||
|
||||
// 不计考核清单
|
||||
assert.equal(data.heldOrders.length, 2);
|
||||
const reasons = data.heldOrders.map((h) => h.holdReason).sort();
|
||||
assert.deepEqual(reasons, ['待审核', '订单异常'].sort());
|
||||
|
||||
// 新鲜度直接取自主查询的 query_time，不再额外扫表
|
||||
assert.equal(data.freshness.stateMaxQuery, '2026-10-20 11:18:27');
|
||||
// 🔥 2026-10-20：上游 ETL 停更时页面必须自己喊出来（当天 15:48 之后 0 行刷新，
|
||||
// 业务看到「已发货的单还显示未发货」，其实是旧快照）。阈值 90 分钟。
|
||||
assert.equal(typeof data.freshness.ageMinutes, 'number', '要给出快照距今多少分钟');
|
||||
assert.equal(
|
||||
data.freshness.stale,
|
||||
data.freshness.ageMinutes > 90,
|
||||
'滞后超过 90 分钟必须标 stale（阈值与 STATE_STALE_MINUTES 对齐）'
|
||||
);
|
||||
if (data.freshness.stale) {
|
||||
assert.match(data.freshness.hint, /未刷新/u, 'stale 时必须给出人话提示');
|
||||
}
|
||||
// 快照 11:18 早于本轮 18:00 核验时刻 → 必须明确「数据没覆盖核验时刻」
|
||||
assert.equal(data.freshness.coversDeadline, false, '快照早于核验时刻时 coversDeadline 必须为 false');
|
||||
assert.match(data.freshness.hint, /没覆盖|未覆盖/u, '没覆盖核验时刻要在提示里说清楚');
|
||||
|
||||
// ── 性能护栏 ────────────────────────────────────────────────────────
|
||||
assert.equal(calls.state, 1, '状态表只允许查一次（金额/新鲜度不许再扫表）');
|
||||
const sql = calls.sql[0];
|
||||
assert.match(sql, /jst_order_express_details/u, '数据源必须是实时状态表');
|
||||
assert.match(sql, /e\.send_time IS NULL/u, '已发货靠 send_time 判');
|
||||
// 本版基准是审核时间 → 两列审核时间都必须在投影里
|
||||
assert.match(sql, /e\.last_oa_confirm_time/u, '窗口上界按审核时间判，必须取这一列');
|
||||
assert.match(sql, /e\.first_oa_confirm_time/u, '审核时间缺失时用首次审核时间兜底');
|
||||
// 🔥 不再把「创建/付款 ≤ 核验时刻−24h」下推到 SQL（24h 门槛已取消）
|
||||
assert.doesNotMatch(sql, /@cutoff/u, '不许再有 24h 超时下推参数');
|
||||
assert.doesNotMatch(sql, /pay_time <=/u, '不许再按付款时间做 24h 截断');
|
||||
assert.doesNotMatch(sql, /createdAt/u, '状态表的 createdAt 是同步落库时间，不能用');
|
||||
// 宽列会触发基表回表：同一 WHERE 取 2 列 0.7s，取 15 列（含长文本）54s
|
||||
assert.doesNotMatch(sql, /order_labels|buyer_message|remark/u, '不能投影长文本列');
|
||||
assert.doesNotMatch(sql, /CONVERT/u, '不要在 SQL 里 CONVERT 时间列');
|
||||
assert.doesNotMatch(sql, /modified/u, 'modified 每天凌晨被批量刷新，不可用');
|
||||
assert.doesNotMatch(sql, /pay_amount|jst_salesOutboundInfo/u, '不许补金额，也不再查出库单表');
|
||||
|
||||
// 补创建时间：必须走两张订单表，且**只投影 6 个窄列**
|
||||
assert.ok(calls.backfill >= 1, '必须回订单表补创建时间与作废事实');
|
||||
for (const bs of calls.backfillSql) {
|
||||
assert.match(bs, /SELECT o_id, created, status, send_date, is_merge, is_split\s+FROM\s+dbo\.(jst_Orders|jst_qmcust_orderlist)/u,
|
||||
`补订单事实只能取这 6 个窄列：${bs.slice(0, 90)}`);
|
||||
assert.doesNotMatch(bs, /pay_amount|labels|buyer_message|remark|SELECT \*/u,
|
||||
'多取一列就会把 0.2s 拖到 38s');
|
||||
}
|
||||
|
||||
// ⚠️ 窗口参数走 params，不在 SQL 里手写
|
||||
assert.equal(calls.params[0].windowStart, '2026-09-20 00:00:00', '下界是近 30 天');
|
||||
assert.equal(calls.params[0].cutoff, undefined, '24h 下推参数已删除');
|
||||
assert.equal(calls.params[0].shipStatus, '发货中');
|
||||
|
||||
// round 必须带出 windowEnd，否则页面渲染成「核验 前」
|
||||
assert.equal(data.round.key, 'AFTERNOON');
|
||||
assert.match(String(data.round.windowEnd), /16:00:00$/u);
|
||||
assert.equal(data.window.boundary, 'audit', '窗口按审核时间判，要透出给前端');
|
||||
assert.equal(data.window.measuredBy, 'audit', '已等时长按审核时间算');
|
||||
}));
|
||||
|
||||
test('13:00 轮：只核验「今天 00:00~07:00 审核」的单 + 历史未发', withStubbedService(async (svc) => {
|
||||
const data = await svc.getShipTimeliness({ now: at(13, 5), limit: 10 });
|
||||
assert.equal(data.round.key, 'NOON');
|
||||
assert.equal(data.round.windowEnd, '2026-10-20 07:00:00');
|
||||
|
||||
// 21 号：今天 07:20 审核 → 晚于 7 点，**不属于 13:00 轮**（业务口径：7 点前审核的才 13:00 核验）
|
||||
assert.ok(!data.orders.some((o) => String(o.oId) === '21'),
|
||||
'今天 07:20 审核 → 不是 7 点前审核的单，13:00 轮不该出现');
|
||||
// 24 号：今天 07:40 审核 → 同理不核验
|
||||
assert.ok(!data.orders.some((o) => String(o.oId) === '24'),
|
||||
'今天 07:40 审核 → 不进 13:00 轮');
|
||||
// 26 号：今天 13:10 才审核（9818476 那种形态）→ 更不能进 13:00 轮
|
||||
assert.ok(!data.orders.some((o) => String(o.oId) === '26'),
|
||||
'下午才审核的老单不能进 13:00 轮');
|
||||
|
||||
// 22 号：今天 06:40 审核（6:30~7:00 这段）→ 13:00 只等 380 分钟，必须超时（无 24h 门槛）
|
||||
const b = data.orders.find((o) => String(o.oId) === '22');
|
||||
assert.ok(b, '6:30~7:00 审核、13:00 未发就是超时');
|
||||
assert.equal(b.benchmarkSource, 'last_audit');
|
||||
assert.equal(b.overdueMinutes, 380);
|
||||
assert.equal(b.waitedHours, 6.3);
|
||||
// 23 号：昨天审核、至今未发 → 历史未发池也要看到
|
||||
const d = data.orders.find((o) => String(o.oId) === '23');
|
||||
assert.ok(d, '含历史未发单（历史不受 00:00 起限制）');
|
||||
assert.equal(d.overdueMinutes, 1010);
|
||||
|
||||
// 25 号：最后一次审核 10-20 13:30 → 不属于「7 点前审核」，13:00 轮不核验
|
||||
assert.ok(!data.orders.some((o) => String(o.oId) === '25'),
|
||||
'重审到 13:30 的单归 18:00 轮，不进 13:00 轮');
|
||||
|
||||
// 13:00 轮 = 22（今天 06:40 审核）+ 23（昨天 20:10 审核，历史未发）= 2 单
|
||||
assert.equal(data.summary.overdueUnshipped, 2);
|
||||
assert.equal(data.window.boundary, 'audit', '窗口按审核时间判');
|
||||
// 仓级例外只在 18:00 轮生效，13:00 轮没有例外
|
||||
assert.equal(data.window.overrides.length, 0, '13:00 轮统一 07:00，无仓级例外');
|
||||
}, 'noon'));
|
||||
|
||||
test('服务层 13:00 前返回 notStarted，且不去查状态表', withStubbedService(async (svc, { calls }) => {
|
||||
const data = await svc.getShipTimeliness({ now: at(9, 30), limit: 10 });
|
||||
assert.equal(data.notStarted, true);
|
||||
assert.equal(data.round, null);
|
||||
assert.equal(data.orders.length, 0);
|
||||
assert.equal(data.summary.overdueUnshipped, 0);
|
||||
// 11 个主仓仍然列出来（结构不能塌），但数字全为 0
|
||||
assert.equal(data.centers.length, registry.CENTERS.length);
|
||||
assert.ok(data.centers.every((x) => x.overdueUnshipped === 0));
|
||||
assert.equal(calls.state, 0, '未到核验时间不应查库');
|
||||
assert.equal(calls.backfill, 0, '未到核验时间也不该回订单表');
|
||||
assert.match(data.note, /13:00/u);
|
||||
assert.equal(data.nextRoundAt, '2026-10-20 13:00:00');
|
||||
assert.equal(data.nextWindowEnd, '2026-10-20 07:00:00');
|
||||
}));
|
||||
|
||||
// ── ⑧ 时区：生产容器是 UTC，库里时间是北京时间 ──────────────────────────
|
||||
// 2026-10-21 实测：容器 /etc/timezone=Etc/UTC，mssql useUTC:false 把 GETDATE()
|
||||
// 构造成「墙钟当 UTC」的 Date → 比真实 now 快 8 小时。北京时间 00:00~08:00
|
||||
// 服务端取到的是「昨天」，13:00 轮因此把整个历史未发池算进来（3895 单 vs 本地 6 单）。
|
||||
test('beijingNow：任何机器时区下读出来的本地时间都等于北京时间', () => {
|
||||
// 真实时刻 2026-10-21T00:04:00Z = 北京时间 2026-10-21 08:04
|
||||
const base = new Date('2026-10-21T00:04:00Z');
|
||||
const bj = registry.beijingNow(base);
|
||||
const stamp = (d) => `${d.getFullYear()}-${String(d.getMonth() + 1).padStart(2, '0')}`
|
||||
+ `-${String(d.getDate()).padStart(2, '0')} `
|
||||
+ `${String(d.getHours()).padStart(2, '0')}:${String(d.getMinutes()).padStart(2, '0')}`;
|
||||
assert.equal(stamp(bj), '2026-10-21 08:04', '平移后本地 getter 必须读出北京时间');
|
||||
|
||||
// 跨日场景：真实时刻 2026-10-20T23:48:00Z = 北京时间 2026-10-21 07:48（UTC 上还是「昨天」）
|
||||
const midnight = registry.beijingNow(new Date('2026-10-20T23:48:00Z'));
|
||||
assert.equal(stamp(midnight).slice(0, 10), '2026-10-21',
|
||||
'北京时间 00:00~08:00 不能取成前一天');
|
||||
});
|
||||
|
||||
test('resolveActiveRound 默认按北京时间取「今天」，不依赖容器时区', () => {
|
||||
// 北京时间 2026-10-21 07:48（UTC 上是 10-20 23:48）→ 还没到 13:00，应当 notStarted
|
||||
const round = registry.resolveActiveRound(registry.beijingNow(new Date('2026-10-20T23:48:00Z')));
|
||||
assert.equal(round, null, '北京时间 07:48 未到 13:00 首轮核验');
|
||||
// 北京时间 2026-10-21 13:30 → 13:00 轮生效，窗口上界 07:00、核验 13:00
|
||||
const noon = registry.resolveActiveRound(registry.beijingNow(new Date('2026-10-21T05:30:00Z')));
|
||||
assert.equal(noon.key, 'NOON');
|
||||
assert.equal(noon.date, '2026-10-21');
|
||||
assert.equal(noon.deadline, '2026-10-21 13:00:00');
|
||||
assert.equal(noon.windowEnd, '2026-10-21 07:00:00');
|
||||
});
|
||||
@ -1,101 +0,0 @@
|
||||
# 业务库补表需求：每日进销存流水
|
||||
|
||||
> 提给：DBA / 聚水潭数据同步负责人
|
||||
> 提出方：仓库系统（cangku）· 大货库存监控 → 每日进销存
|
||||
> 日期：2026-09-24
|
||||
|
||||
## 背景
|
||||
|
||||
「每日进销存」页面需要按仓库展示 26 个仓的日内进销存流水，表头 21 列：
|
||||
|
||||
| # | 列 | # | 列 |
|
||||
|---|---|---|---|
|
||||
| 1 | 仓库 | 12 | 销售退货 |
|
||||
| 2 | 期初数量 | 13 | 调拨入 |
|
||||
| 3 | 加工进仓 | 14 | 期初(2) |
|
||||
| 4 | 采购退货 | 15 | 其它出库 |
|
||||
| 5 | 采购进仓 | 16 | 期末数量 |
|
||||
| 6 | 其它进仓 | 17 | 库存周转天数 |
|
||||
| 7 | 其它退货 | 18 | 滞销预警级库存量 |
|
||||
| 8 | 销售出仓 | 19 | 商品慢流级库存量 |
|
||||
| 9 | 盘点 | 20 | 商品呆滞级库存量 |
|
||||
| 10 | 加工出仓 | 21 | 商品僵尸级库存量 |
|
||||
| 11 | 调拨出 | | |
|
||||
|
||||
其中 1、16~21 列已能从业务库算出（见下表「已具备」），**2~15 列目前无法从业务库还原**。
|
||||
|
||||
## 已具备（无需补表）
|
||||
|
||||
| 列 | 来源 | 说明 |
|
||||
|---|---|---|
|
||||
| 仓库 | `rpt.jst_warehouseInfo` | `wms_co_id` 与仓库名映射 |
|
||||
| 期末数量 | `rpt.jst_inventoryInfo` | 按 `wms_co_id` 单仓 `SUM(qty)`，实时 |
|
||||
| 库存周转天数 | 近 30 天发货 ÷ 实时库存 | `jst_OrderItem` × `jst_Orders`（`send_date`） |
|
||||
| 四级库存量 | 实时库存 × 发货 × `pm_stockMonitor.created` | 库龄 = 基准时刻 − SKU 建档时间 |
|
||||
|
||||
## 缺口一：没有按天的历史库存结存表（阻塞「期初数量」）
|
||||
|
||||
`rpt.jst_inventoryInfo` 只有**当前**库存，没有历史版本；`rpt.pm_stockMonitor` 是「归属仓」口径的每日快照（`jsStock`），与实物库存口径不一致（崔桥 115135 vs 实物 92439），不能当结存用。
|
||||
|
||||
**现状的临时方案**：项目本地 MySQL 建了 `daily_inventory_snapshot` 表，每天 01:30 把 26 仓实时库存落一份快照，`今日期初 = 昨日快照`。这是自采数据，一旦任务漏跑就会断链。
|
||||
|
||||
**请求**：请提供按天、按仓、按 SKU 的库存结存表，形如：
|
||||
|
||||
```
|
||||
jst_inventoryDaily(
|
||||
biz_date DATE, -- 业务日
|
||||
wms_co_id BIGINT, -- 仓库
|
||||
sku_id VARCHAR, -- SKU
|
||||
qty DECIMAL, -- 当日结存
|
||||
...
|
||||
)
|
||||
```
|
||||
|
||||
有了它，「期初数量」即可直接取上一业务日结存，本地快照表可退役。
|
||||
|
||||
## 缺口二：缺少 4 类单据表（阻塞 12 个流水列）
|
||||
|
||||
业务库 `rpt` 下已排查过全部 220 张表，**不存在**以下单据：
|
||||
|
||||
| 缺失单据 | 影响的列 |
|
||||
|---|---|
|
||||
| 调拨单（调拨出 / 调拨入） | 调拨出、调拨入 |
|
||||
| 盘点单 | 盘点 |
|
||||
| 加工单（加工进仓 / 加工出仓） | 加工进仓、加工出仓 |
|
||||
| 其它出入库单 | 其它进仓、其它退货、其它出库、期初(2) |
|
||||
|
||||
请补充按单据行（SKU 级）的明细表，至少包含：
|
||||
|
||||
```
|
||||
业务日期 / 单据号 / 仓库 wms_co_id / sku_id / 数量 / 单据类型(出|入) / 状态
|
||||
```
|
||||
|
||||
## 缺口三：已有单据的数值与进销存口径不一致（阻塞 销售出仓 / 采购进仓 / 采购退货 / 销售退货）
|
||||
|
||||
这 4 类单据表**存在**，但按天汇总后与聚水潭进销存导出的数值对不上，不能直接用：
|
||||
|
||||
| 列 | 现有来源 | 9-23 崔桥工厂仓实测 | 基准值 | 偏差 |
|
||||
|---|---|---:|---:|---|
|
||||
| 销售出仓 | `jst_OrderItem` × `jst_Orders` 按 `send_date` | 1,769 | 4,273 | **−59%** |
|
||||
| 销售出仓 | 同上，按 `order_date` | 1,723 | 4,273 | −60% |
|
||||
| 销售出仓 | 同上，按 `modified` | 5,471 | 4,273 | +28% |
|
||||
| 采购进仓 | `jst_purchaseItem.inQty` × `jst_purchase` 按 `confirm_date` | 数百 | 1,295 | 严重偏低 |
|
||||
|
||||
其它已排除的候选：
|
||||
|
||||
- `rpt.jst_salesOutboundInfo`：`qty` 全为 0，且 `order_type` 只含销售类订单，不含调拨 / 其它出库。
|
||||
- `rpt.jst_originalBillInfo`（1,500 万行）：是支付宝 / 财务账单表（`channel=alipayCSV`、`fee_name=交易收款`、`sku_id` 为 null），与库存流水无关。
|
||||
- `rpt.jst_qmcust_salesoutbound`（奇门出库单）：非本业务口径。
|
||||
|
||||
**请求**：确认这 4 类表在报表库（JSReportReplica）的同步是否完整、以及「进销存导出」所用的日期字段是哪一个（发 / 审 / 确 / 记账）。给出字段口径后这 4 列即可接入。
|
||||
|
||||
## 验收标准
|
||||
|
||||
补表后，任一业务日应满足行内恒等式：
|
||||
|
||||
```
|
||||
期末数量 = 期初数量 + 加工进仓 + 采购进仓 + 其它进仓 + 其它退货 + 销售退货 + 调拨入
|
||||
− 采购退货 − 销售出仓 − 盘点 − 加工出仓 − 调拨出 − 其它出库
|
||||
```
|
||||
|
||||
页面会以该恒等式做逐仓自校验，全部通过后才会撤下「暂缺单据来源」的提示。
|
||||
@ -1,29 +1,9 @@
|
||||
import request from './request';
|
||||
|
||||
const LIST_TIMEOUT_MS = 5 * 60 * 1000;
|
||||
const IMPORT_TIMEOUT_MS = 2 * 60 * 1000;
|
||||
|
||||
// 每日进销存：进销存流水 + 实时期末 + 分级库存量
|
||||
// refresh=1 跳过后端 5 分钟缓存，强制重算（一次要扫订单明细，约 15~20s）
|
||||
// date=YYYY-MM-DD 查看指定业务日（默认取业务库最新业务日）
|
||||
export const getDailyInventory = (params = {}) => request.get(
|
||||
// 每日进销存：25 仓 × 进销存流水 + 实时期末 + 分级库存量
|
||||
export const getDailyInventory = () => request.get(
|
||||
'/api/daily-inventory',
|
||||
{ params, timeout: LIST_TIMEOUT_MS }
|
||||
);
|
||||
|
||||
// 导入聚水潭「进销存按仓导出」xlsx：file 为 File 对象，date 为业务日 YYYY-MM-DD
|
||||
export const importDailyInventoryOfficial = ({ file, date }) => {
|
||||
const formData = new FormData();
|
||||
formData.append('file', file);
|
||||
formData.append('date', date);
|
||||
return request.post('/api/daily-inventory/official-import', formData, {
|
||||
timeout: IMPORT_TIMEOUT_MS,
|
||||
headers: { 'Content-Type': 'multipart/form-data' },
|
||||
});
|
||||
};
|
||||
|
||||
// 查询某业务日已导入的官方进销存数据
|
||||
export const getDailyInventoryOfficial = (date) => request.get(
|
||||
'/api/daily-inventory/official',
|
||||
{ params: { date } }
|
||||
{ timeout: LIST_TIMEOUT_MS }
|
||||
);
|
||||
|
||||
@ -1,17 +0,0 @@
|
||||
import request from './request';
|
||||
|
||||
// 每日进销存 · 定时截图通知（管理员专用）
|
||||
// 后端只返回「是否已配置」与脱敏预览，不返回任何密钥
|
||||
|
||||
export const getDailyInventoryNotificationConfig = () =>
|
||||
request.get('/api/daily-inventory-notification/config');
|
||||
|
||||
export const saveDailyInventoryNotificationConfig = (payload) =>
|
||||
request.put('/api/daily-inventory-notification/config', payload);
|
||||
|
||||
/** 立即测试：真实截图 + 上传 + 通知一次，不影响正式定时任务的幂等记录 */
|
||||
export const runDailyInventoryNotificationTest = () =>
|
||||
request.post('/api/daily-inventory-notification/test', {}, { timeout: 300000 });
|
||||
|
||||
export const getDailyInventoryNotificationRuns = (limit = 10) =>
|
||||
request.get('/api/daily-inventory-notification/runs', { params: { limit } });
|
||||
@ -1,16 +0,0 @@
|
||||
import request from './request';
|
||||
|
||||
const LIST_TIMEOUT_MS = 5 * 60 * 1000;
|
||||
|
||||
// 拣选库位动销分析：仓库 × 仓位 → 类型 / 库存数量 / SKU数 / 近N天销量 / 日销 / 动销等级
|
||||
// refresh=1 跳过后端 5 分钟缓存，强制重算
|
||||
export const getPickingBinSalesAnalysis = (params = {}) => request.get(
|
||||
'/api/picking-bin-sales-analysis',
|
||||
{ params, timeout: LIST_TIMEOUT_MS }
|
||||
);
|
||||
|
||||
// 导出库位明细（xlsx/csv，服务端直接返回文件流）
|
||||
export const exportPickingBinSalesAnalysis = (params = {}) => request.get(
|
||||
'/api/picking-bin-sales-analysis/export',
|
||||
{ params, responseType: 'blob', timeout: LIST_TIMEOUT_MS }
|
||||
);
|
||||
@ -1,16 +0,0 @@
|
||||
import request from './request';
|
||||
|
||||
const LIST_TIMEOUT_MS = 5 * 60 * 1000;
|
||||
|
||||
// 仓库库存动销分析：仓库 × 动销等级 → SKU数量 / SKU占比 / 库存数量 / 库存占比 / 销量
|
||||
// refresh=1 跳过后端 5 分钟缓存，强制重算
|
||||
export const getStockSalesAnalysis = (params = {}) => request.get(
|
||||
'/api/stock-sales-analysis',
|
||||
{ params, timeout: LIST_TIMEOUT_MS }
|
||||
);
|
||||
|
||||
// 导出「销售=0」档的 SKU 级明细（xlsx/csv，服务端直接返回文件流）
|
||||
export const exportStockSalesZeroDetail = (params = {}) => request.get(
|
||||
'/api/stock-sales-analysis/zero-sales-export',
|
||||
{ params, responseType: 'blob', timeout: LIST_TIMEOUT_MS }
|
||||
);
|
||||
@ -1,23 +0,0 @@
|
||||
import request from './request';
|
||||
|
||||
// 发货时效要扫两张订单表 + 出库表（rpt 下全是视图），冷启动实测 40~50 秒，
|
||||
// 超时必须放大到 3 分钟，否则前端会先断开、后端还在跑。
|
||||
const TIMELINESS_TIMEOUT_MS = 3 * 60 * 1000;
|
||||
|
||||
// 仓储中心 24 小时发货时效：每个主仓「超时未发」数量 + 超时订单明细
|
||||
// params.round 'NOON' | 'AFTERNOON'（不传按当前时刻自动判定）
|
||||
// params.limit 明细条数上限
|
||||
export const getWarehouseShipTimeliness = (params = {}) => request.get(
|
||||
'/api/warehouse-ship-timeliness/list',
|
||||
{
|
||||
params,
|
||||
timeout: TIMELINESS_TIMEOUT_MS,
|
||||
headers: { 'Cache-Control': 'no-cache' },
|
||||
}
|
||||
);
|
||||
|
||||
// 仅取今日两轮核验的描述（不打订单表，秒回），用于顶部提示
|
||||
export const getWarehouseShipTimelinessRounds = () => request.get(
|
||||
'/api/warehouse-ship-timeliness/rounds',
|
||||
{ timeout: 30000 }
|
||||
);
|
||||
@ -36,13 +36,10 @@ export const DEFAULT_SIDEBAR_CONFIG = {
|
||||
{ key: 'mkh-bom-data', label: 'MKH-BOM资料', icon: 'table', routeKey: 'mkh-bom-data', visible: true, order: 20 },
|
||||
],
|
||||
},
|
||||
{ key: 'warehouse-ship-timeliness', type: 'item', label: '仓储中心24小时发货时效', icon: 'inbox', routeKey: 'warehouse-ship-timeliness', visible: true, order: 110 },
|
||||
{
|
||||
key: 'large-stock-monitor', type: 'group', label: '大货库存监控', icon: 'appstore', visible: true, order: 200, defaultExpanded: true,
|
||||
children: [
|
||||
{ key: 'daily-inventory', label: '每日进销存', icon: 'table', routeKey: 'daily-inventory', visible: true, order: 10 },
|
||||
{ key: 'stock-sales-analysis', label: '库存动销分析', icon: 'line-chart', routeKey: 'stock-sales-analysis', visible: true, order: 20 },
|
||||
{ key: 'picking-bin-sales-analysis', label: '拣选库位动销分析', icon: 'inbox', routeKey: 'picking-bin-sales-analysis', visible: true, order: 30 },
|
||||
],
|
||||
},
|
||||
{
|
||||
|
||||
@ -3,81 +3,59 @@
|
||||
*
|
||||
* 表头取自桌面《库存监控.xlsx》，顺序与表格一致。
|
||||
* source 标记该列数据来源，便于在页面上如实标注口径：
|
||||
* - snapshot：来自项目本地快照表 daily_inventory_snapshot（每日定时落库，自动滚动）
|
||||
* - baseline：22 号基准值（业务库无对应单据表，无法还原）
|
||||
* - runtime：运行时从业务库实时取数
|
||||
* - unavailable：业务库缺少对应单据表，暂无法计算（渲染为「—」）
|
||||
*/
|
||||
|
||||
export const COLUMN_SOURCE = {
|
||||
snapshot: 'snapshot',
|
||||
baseline: 'baseline',
|
||||
runtime: 'runtime',
|
||||
unavailable: 'unavailable',
|
||||
};
|
||||
|
||||
const NO_SOURCE_TIP = '业务库 JSReportReplica 缺少该单据表（调拨 / 盘点 / 加工 / 其它出入库），以聚水潭「进销存按仓导出」为准，导入后本列自动出数';
|
||||
const FLOW_CALIBER_NOTE = '口径说明：业务库只能还原该列的近似值（采购按单据日期、销售按订单发货日期），与聚水潭进销存口径存在差异，已导入官方数据时以官方为准';
|
||||
const OFFICIAL_TIP = '同一业务日导入过聚水潭进销存导出时，本列直接采用官方值（单元格为常规色）；未导入时回退业务库推算（单元格标灰）';
|
||||
|
||||
/** 表格存在两个名为「期初」的列，第二个加后缀区分 */
|
||||
export const DAILY_INVENTORY_COLUMNS = [
|
||||
{ key: 'warehouse', label: '仓库', source: 'snapshot', tip: '取自主数据表 rpt.jst_warehouseInfo 的仓库名，表格显示为「XX主仓」' },
|
||||
{ key: 'openingQty', label: '期初数量', source: 'snapshot', tip: `优先取聚水潭「进销存按仓导出」的官方期初；未导入时取本地快照表 daily_inventory_snapshot 中上一业务日的期末结存（每日 01:30 自动落库），快照缺失则自动用「实时库存扣流水」回推补写（回推值受业务库缺失的 8 类单据影响，与官方存在偏差）` },
|
||||
{ key: 'processIn', label: '加工进仓', source: 'unavailable', tip: `加工进仓。${NO_SOURCE_TIP} ${OFFICIAL_TIP}` },
|
||||
{ key: 'purchaseReturn', label: '采购退货', source: 'runtime', tip: `采购退货（流出，负数）。rpt.jst_purchaseout × jst_purchaseoutItem，按 io_date 统计。${FLOW_CALIBER_NOTE} ${OFFICIAL_TIP}` },
|
||||
{ key: 'purchaseIn', label: '采购进仓', source: 'runtime', tip: `采购进仓（流入）。rpt.jst_purchase × jst_purchaseItem，按 po_date 统计，仅计 Confirmed/Finished 状态。${FLOW_CALIBER_NOTE} ${OFFICIAL_TIP}` },
|
||||
{ key: 'otherIn', label: '其它进仓', source: 'unavailable', tip: `其它进仓。${NO_SOURCE_TIP} ${OFFICIAL_TIP}` },
|
||||
{ key: 'otherReturn', label: '其它退货', source: 'unavailable', tip: `其它退货。${NO_SOURCE_TIP} ${OFFICIAL_TIP}` },
|
||||
{ key: 'salesOut', label: '销售出仓', source: 'runtime', tip: `销售出仓（流出，负数）。rpt.jst_Orders × jst_OrderItem，按 send_date 统计，排除 Delete/Cancelled，与「库存周转天数」的发货口径一致。${FLOW_CALIBER_NOTE} ${OFFICIAL_TIP}` },
|
||||
{ key: 'stocktaking', label: '盘点', source: 'unavailable', tip: `盘点。${NO_SOURCE_TIP} ${OFFICIAL_TIP}` },
|
||||
{ key: 'processOut', label: '加工出仓', source: 'unavailable', tip: `加工出仓。${NO_SOURCE_TIP} ${OFFICIAL_TIP}` },
|
||||
{ key: 'transferOut', label: '调拨出', source: 'unavailable', tip: `调拨出。${NO_SOURCE_TIP} ${OFFICIAL_TIP}` },
|
||||
{ key: 'salesReturn', label: '销售退货', source: 'runtime', tip: `销售退货（流入）。rpt.jst_returnAndRefundInfo × jst_returnAndRefundItem，按 as_date 统计，类型限定普通退货/拒收退货/换货/维修，取明细实收数量 r_qty。${FLOW_CALIBER_NOTE} ${OFFICIAL_TIP}` },
|
||||
{ key: 'transferIn', label: '调拨入', source: 'unavailable', tip: `调拨入。${NO_SOURCE_TIP} ${OFFICIAL_TIP}` },
|
||||
{ key: 'openingQtyExtra', label: '期初(2)', source: 'unavailable', tip: '聚水潭导出表中的第二个「期初」列，业务库无对应来源' },
|
||||
{ key: 'otherOut', label: '其它出库', source: 'unavailable', tip: `其它出库。${NO_SOURCE_TIP} ${OFFICIAL_TIP}` },
|
||||
{ key: 'closingQty', label: '期末数量', source: 'runtime', tip: `优先取聚水潭「进销存按仓导出」的官方期末；未导入时取实时库存 rpt.jst_inventoryInfo，按仓库 wms_co_id 单仓统计（存货数量不为 0 的 SKU 汇总）` },
|
||||
{ key: 'turnoverDays', label: '库存周转天数', source: 'runtime', tip: '月度发货总件数 / 月度日均库存件数 × 100%。月度发货总件数＝近 30 天已发货订单件数（jst_OrderItem×jst_Orders，按 send_date，排除 Delete/Cancelled）；月度日均库存件数＝该仓实时库存（无历史结存表，以当日库存近似）' },
|
||||
{ key: 'warnLevel', label: '滞销预警级库存量', source: 'runtime', tip: 'SKU 级：库龄 < 3 个月 且 周转率 30%~199% 的库存合计' },
|
||||
{ key: 'slowLevel', label: '商品慢流级库存量', source: 'runtime', tip: 'SKU 级：库龄 < 3 个月且周转率 ≥ 200%，或库龄 > 3 个月且周转率 30%~99% 的库存合计' },
|
||||
{ key: 'staleLevel', label: '商品呆滞级库存量', source: 'runtime', tip: 'SKU 级：库龄 3~12 个月且周转率 ≥ 100%，或库龄 > 12 个月且周转率 100%~199% 的库存合计' },
|
||||
{ key: 'zombieLevel', label: '商品僵尸级库存量', source: 'runtime', tip: 'SKU 级：库龄 > 12 个月 且 周转率 ≥ 200% 的库存合计' },
|
||||
{ key: 'warehouse', label: '仓库', source: 'baseline', tip: '取自主数据表 rpt.jst_warehouseInfo 的仓库名，表格显示为「XX主仓」' },
|
||||
{ key: 'openingQty', label: '期初数量', source: 'baseline', tip: '22 号进销存基准值。业务库无按天的历史库存结存表，无法还原，取自 9-22 导出数据' },
|
||||
{ key: 'processIn', label: '加工进仓', source: 'baseline', tip: '22 号基准值。业务库无加工单据表' },
|
||||
{ key: 'purchaseReturn', label: '采购退货', source: 'baseline', tip: '22 号基准值（业务库 jst_purchaseout 虽有单据，但数值与该进销存口径不一致）' },
|
||||
{ key: 'purchaseIn', label: '采购进仓', source: 'baseline', tip: '22 号基准值（同上，业务库数值与进销存口径不一致）' },
|
||||
{ key: 'otherIn', label: '其它进仓', source: 'baseline', tip: '22 号基准值。业务库无对应单据表' },
|
||||
{ key: 'otherReturn', label: '其它退货', source: 'baseline', tip: '22 号基准值。业务库无对应单据表' },
|
||||
{ key: 'salesOut', label: '销售出仓', source: 'baseline', tip: '22 号基准值（负数为出库）。业务库 jst_salesOutboundInfo 数值与该进销存口径不一致' },
|
||||
{ key: 'stocktaking', label: '盘点', source: 'baseline', tip: '22 号基准值。业务库无盘点单据表' },
|
||||
{ key: 'processOut', label: '加工出仓', source: 'baseline', tip: '22 号基准值。业务库无加工单据表' },
|
||||
{ key: 'transferOut', label: '调拨出', source: 'baseline', tip: '22 号基准值（负数为调出）。业务库无调拨单据表' },
|
||||
{ key: 'salesReturn', label: '销售退货', source: 'baseline', tip: '22 号基准值（业务库 jst_returnAndRefundInfo 数值与该进销存口径不一致）' },
|
||||
{ key: 'transferIn', label: '调拨入', source: 'baseline', tip: '22 号基准值。业务库无调拨单据表' },
|
||||
{ key: 'openingQtyExtra', label: '期初(2)', source: 'baseline', tip: '表格中的第二个「期初」列（9-22 导出值）' },
|
||||
{ key: 'otherOut', label: '其它出库', source: 'baseline', tip: '22 号基准值（负数为出库）。业务库无对应单据表' },
|
||||
{ key: 'closingQty', label: '期末数量', source: 'runtime', tip: '聚水潭实时库存 rpt.jst_inventoryInfo，按仓库 wms_co_id 单仓统计（与表格 22 号期末一致，24/25 仓精确匹配）' },
|
||||
{ key: 'turnoverDays', label: '库存周转天数', source: 'runtime', tip: '月度发货总件数 / 月度日均库存件数 × 100%（全员均值），数据来自 pm_stockMonitor' },
|
||||
{ key: 'warnLevel', label: '滞销预警级库存量', source: 'runtime', tip: '库龄 < 3 个月 且 30% ≤ 周转率 ≤ 199% 的 SKU 库存合计' },
|
||||
{ key: 'slowLevel', label: '商品慢流级库存量', source: 'runtime', tip: '库龄 < 3 个月且周转率 ≥ 200%，或库龄 ≥ 3 个月且周转率 30%~99% 的 SKU 库存合计' },
|
||||
{ key: 'staleLevel', label: '商品呆滞级库存量', source: 'runtime', tip: '库龄 3~12 个月且周转率 ≥ 100%，或库龄 > 12 个月且周转率 100%~199% 的 SKU 库存合计' },
|
||||
{ key: 'zombieLevel', label: '商品僵尸级库存量', source: 'runtime', tip: '库龄 > 12 个月 且 周转率 ≥ 200% 的 SKU 库存合计' },
|
||||
];
|
||||
|
||||
/** 口径说明弹框文案 */
|
||||
export const FORMULA_DESCRIPTION = [
|
||||
'数据来源说明（全部来自数据库或聚水潭官方导出，无人工填数）：',
|
||||
'· 聚水潭官方进销存（优先）：把聚水潭「进销存按仓导出」的 xlsx 在页面右上角导入后，',
|
||||
' 该业务日的期初、12 个流水列、期末直接采用官方值，恒等式「期初 + 流水 = 期末」逐仓闭合。',
|
||||
' 业务库 JSReportReplica 只能还原 4/12 个流水列，且口径与聚水潭不一致（采购按单据日期 vs 实际入库、',
|
||||
' 销售按订单发货日期 vs 出库单、jst_salesOutboundInfo.qty 全为 0），调拨 / 盘点 / 加工 / 其它出入库更没有对应单据表，',
|
||||
' 因此未导入官方数据时这些列显示「—」或为业务库近似值（单元格标灰）。',
|
||||
'· 期初数量：官方期初优先；未导入时取本地快照表 daily_inventory_snapshot 中「上一业务日」的期末结存。',
|
||||
' 业务库 JSReportReplica 没有按天的历史库存结存表，因此由本系统每天 01:30 把各仓实时库存落一份快照，',
|
||||
' 今日期初 = 昨日快照，逐日自动滚动；导入官方数据时会同步回写快照，让后续推算也对齐聚水潭口径。',
|
||||
'· 流水列（12 列）：官方数据优先（导入后 12 列全部出数）；未导入时业务库可还原 4 列 ——',
|
||||
' 采购进仓（jst_purchase×Item，po_date，Confirmed/Finished）、采购退货（jst_purchaseout×Item，io_date）、',
|
||||
' 销售出仓（jst_Orders×OrderItem，send_date，与周转率发货口径一致）、销售退货（jst_returnAndRefund×Item，as_date，实收 r_qty）。',
|
||||
' 其余 8 列（加工进仓 / 其它进仓 / 其它退货 / 盘点 / 加工出仓 / 调拨出 / 调拨入 / 其它出库）业务库无单据表，显示「—」。',
|
||||
'数据来源说明：',
|
||||
'· 期初数量 / 加工进仓 / 采购退货 / 采购进仓 / 其它进仓 / 其它退货 / 销售出仓 / 盘点 / 加工出仓 / 调拨出 / 销售退货 / 调拨入 / 其它出库：',
|
||||
' 取自 2026-09-22 聚水潭进销存导出值。业务库 JSReportReplica 无历史库存结存表，',
|
||||
' 也缺少调拨 / 盘点 / 加工 / 其它出入库单据表；已有的采购与销售单据数值与该进销存口径不一致，故采用导出值。',
|
||||
'· 期末数量：运行时取聚水潭实时库存 rpt.jst_inventoryInfo（按 wms_co_id 单仓），随刷新滚动。',
|
||||
'· 库存周转天数 / 四级库存量：运行时计算，库龄基准时刻为快照日次日 01:00。',
|
||||
'· 库存周转天数 / 四级库存量：运行时由库存快照 rpt.pm_stockMonitor 计算，基准时刻为快照日次日 01:00。',
|
||||
'',
|
||||
'算式：',
|
||||
'· 期末数量 = 期初数量 + 加工进仓 + 采购进仓 + 其它进仓 + 其它退货 + 销售退货 + 调拨入',
|
||||
' − 采购退货 − 销售出仓 − 盘点 − 加工出仓 − 调拨出 − 其它出库',
|
||||
'· 库存周转天数 = 月度发货总件数 / 月度日均库存件数 × 100%',
|
||||
' 月度发货总件数 = 该仓近 30 天已发货订单件数',
|
||||
' （jst_OrderItem 关联 jst_Orders，按订单发货仓 wms_co_id 归属，send_date 落在窗口内，排除 Delete / Cancelled）',
|
||||
' 月度日均库存件数 = 该仓聚水潭实时库存 jst_inventoryInfo 汇总',
|
||||
' （业务库无按天的历史库存结存表，无法算真正的日均库存，以当日库存近似月度日均）',
|
||||
' 库龄(天) = 基准时刻 − SKU 建档时间 created；3 个月按 90 天、12 个月按 365 天折算',
|
||||
'· 库存分级（SKU 级，库龄 + 周转率双维度，低于 30% 的不计入任何级别）：',
|
||||
' 其中 月度发货总件数 = threeAvgSale × 30，月度日均库存件数 = jsStock',
|
||||
'· 库存分级（库龄 + 周转率双维度）：',
|
||||
' 库龄 < 3 个月 且 周转率 30%~199% → 滞销预警',
|
||||
' 库龄 < 3 个月 且 周转率 ≥ 200% → 商品慢流',
|
||||
' 库龄 > 3 个月 且 周转率 30%~99% → 商品慢流',
|
||||
' 库龄 ≥ 3 个月 且 周转率 30%~99% → 商品慢流',
|
||||
' 库龄 3~12 个月 且 周转率 ≥ 100% → 商品呆滞',
|
||||
' 库龄 > 12 个月 且 周转率 100%~199% → 商品呆滞',
|
||||
' 库龄 > 12 个月 且 周转率 ≥ 200% → 商品僵尸',
|
||||
'',
|
||||
'注意：仓库整体周转率按「该仓发货总量 ÷ 该仓库存总量」计算，与四级分级的 SKU 级取舍不是同一个口径，',
|
||||
' 两者不必相等（例如整体周转率 6% 的仓里，仍可以有部分 SKU 周转率超 30% 而被判为预警级）。',
|
||||
];
|
||||
|
||||
@ -1,91 +0,0 @@
|
||||
/** 拣选库位动销分析 —— 表头与口径说明（粒度：仓位 × 商品编码） */
|
||||
|
||||
export const PICKING_BIN_COLUMNS = [
|
||||
{
|
||||
key: 'warehouse',
|
||||
label: '仓库',
|
||||
tip: '聚水潭主仓（按 wms_co_id 单仓独立统计，不合并分仓）',
|
||||
},
|
||||
{
|
||||
key: 'binName',
|
||||
label: '仓位',
|
||||
tip: '系统仓位编码（jst_packInventoryInfo.bin）；同一仓位有多个商品时会出现多行',
|
||||
},
|
||||
{
|
||||
key: 'binType',
|
||||
label: '类型',
|
||||
tip: '统计范围固定为真实拣选仓位（pack_type=Bin 且 bin_group 为空）；箱记录和存货位不纳入动销分析',
|
||||
},
|
||||
{
|
||||
key: 'skuId',
|
||||
label: '商品编码',
|
||||
tip: '商品编码（jst_packInventoryInfo.sku_id），一行就是一个「仓位 × 商品」组合',
|
||||
},
|
||||
{
|
||||
key: 'stockQty',
|
||||
label: '库存数量',
|
||||
tip: '该商品在这个仓位上的当前库存件数（同一仓位多行的库存相加 = 仓位库存）',
|
||||
},
|
||||
{
|
||||
key: 'salesQty',
|
||||
label: '商品销量',
|
||||
tip: '近 N 天该商品的销量（整档，不按仓位分摊）：含线上订单、组合装子件拆分、全民客户(B2B分销)渠道；同一商品占几个仓位，这几行显示的销量都一样，所以这一列不能直接按行求和',
|
||||
},
|
||||
{
|
||||
key: 'dailySales',
|
||||
label: '商品日销',
|
||||
tip: '商品销量 ÷ 统计天数，动销等级严格按此值划分',
|
||||
},
|
||||
{
|
||||
key: 'gradeKey',
|
||||
label: '动销等级',
|
||||
tip: '按商品日销划分：爆款≥20 / 热卖款 10~20 / 平销款 3~10 / 滞销款-1 1~3 / 滞销款-2 0~1 / 销售=0',
|
||||
},
|
||||
];
|
||||
|
||||
export const PICKING_BIN_WINDOW_OPTIONS = [
|
||||
{ label: '近 7 天', value: 7 },
|
||||
{ label: '近 15 天', value: 15 },
|
||||
{ label: '近 30 天', value: 30 },
|
||||
{ label: '近 60 天', value: 60 },
|
||||
];
|
||||
|
||||
export const PICKING_BIN_DEFAULT_DAYS = 30;
|
||||
|
||||
/** 动销等级展示色（与后端 key 对应） */
|
||||
export const PICKING_BIN_GRADE_COLORS = {
|
||||
hot: 'red',
|
||||
best: 'volcano',
|
||||
normal: 'blue',
|
||||
slow1: 'gold',
|
||||
slow2: 'default',
|
||||
zero: 'default',
|
||||
};
|
||||
|
||||
export const PICKING_BIN_DESCRIPTION = [
|
||||
'【统计范围】只统计真实拣选仓位（pack_type=Bin 且 bin_group 为空）；箱记录（pack_type=Pack）和存货位不纳入动销分析。',
|
||||
'',
|
||||
'【粒度】一行 = 一个「仓位 × 商品编码」组合。一个仓位放了 N 个商品就显示 N 行，列表与导出一致。',
|
||||
' 库存数量 = 该商品在这个仓位上的实际库存（同一仓位多行相加 = 仓位总库存）。',
|
||||
'',
|
||||
'【动销等级口径】按「商品日销」分档：商品日销 = 该商品近 N 天销量 ÷ N。',
|
||||
' 爆款：日销 ≥ 20；热卖款：10 ≤ 日销 ＜ 20；平销款：3 ≤ 日销 ＜ 10；',
|
||||
' 滞销款-1：1 ≤ 日销 ＜ 3；滞销款-2：0 ＜ 日销 ＜ 1；销售=0：窗口内该商品无销量。',
|
||||
' 等级判断的是商品本身的销售速度，与其摆放位置无关 —— 同一件商品占几个仓位，等级都相同。',
|
||||
'默认统计窗口为近 30 天，可切换 7 / 15 / 30 / 60 天。',
|
||||
'',
|
||||
'【为什么不用分摊销量来定等级】',
|
||||
' 同一 SKU 常同时占用多个同类型仓位（崔桥工厂仓实测 3290 个拣选 SKU 中 1431 个跨多个拣选位，最多 24 个）。',
|
||||
' 若把销量先摊到每个仓位再定等级，一件日销 100 的爆款放在 10 个仓位就会被算成日销 10 —— 判断的是「摆法」而不是商品。',
|
||||
'',
|
||||
'【商品销量为什么不能直接按行求和】',
|
||||
' 商品销量取的是整档销量（不除以占用仓位数），同一件商品跨仓位会重复出现，所以该列相加无意义。',
|
||||
' 需要按行求和请用导出文件里的「分摊销量」列：商品销量 ÷ 其占用的同类型仓位数。',
|
||||
' 恒等式已实测校验（差异 0）：全部行分摊销量之和 = 有库位记录的那些 SKU 的销量之和。',
|
||||
' 注意它小于全仓销量：jst_packInventoryInfo 只覆盖部分 SKU 的仓位数据，无仓位记录的 SKU 销量不计入任何库位。',
|
||||
'',
|
||||
'数据来源：库存取 rpt.jst_packInventoryInfo（按仓库 + 仓位 + 商品汇总）；',
|
||||
'销量按 send_date 窗口统计 4 个来源：① jst_Orders 普通商品行；② jst_Orders 组合装行（ZH-拼接编码）按组合装映射展开为子件；',
|
||||
'③ jst_qmcust_orderlist 全民客户(B2B分销)普通行（排除拆单父单 Split）；④ qmcust 组合装行同样展开。',
|
||||
'统计范围：只取 pack_type=Bin 且 bin_group 为空的真实拣选仓位，箱记录（pack_type=Pack）和存货位（bin_group=存货）不参与统计。',
|
||||
];
|
||||
@ -5,8 +5,6 @@ export const SIDEBAR_PAGES = [
|
||||
{ pageKey: 'dashboard_preview', path: '/planning/dev-style-preview', name: '仪表盘', category: 'planning', defaultRoles: DEFAULT_PLANNING_ROLES },
|
||||
{ pageKey: 'settings', path: '/settings', name: '系统设置', category: 'system', defaultRoles: DEFAULT_SYSTEM_ROLES },
|
||||
{ pageKey: 'daily_inventory', path: '/planning/operation/daily-inventory', name: '每日进销存', category: 'planning', defaultRoles: DEFAULT_PLANNING_ROLES },
|
||||
{ pageKey: 'stock_sales_analysis', path: '/planning/operation/stock-sales-analysis', name: '库存动销分析', category: 'planning', defaultRoles: DEFAULT_PLANNING_ROLES },
|
||||
{ pageKey: 'picking_bin_sales_analysis', path: '/planning/operation/picking-bin-sales-analysis', name: '拣选库位动销分析', category: 'planning', defaultRoles: DEFAULT_PLANNING_ROLES },
|
||||
{ pageKey: 'returns_inventory_cuiqiao', path: '/planning/operation/returns-inventory/cuiqiao', name: '崔桥工厂仓客退数据监控', category: 'planning', defaultRoles: DEFAULT_PLANNING_ROLES },
|
||||
{ pageKey: 'returns_inventory_subei', path: '/planning/operation/returns-inventory/subei', name: '苏北客退数据监控', category: 'planning', defaultRoles: DEFAULT_PLANNING_ROLES },
|
||||
{ pageKey: 'returns_inventory_suining', path: '/planning/operation/returns-inventory/suining', name: '睢宁客退数据监控', category: 'planning', defaultRoles: DEFAULT_PLANNING_ROLES },
|
||||
|
||||
@ -1,57 +0,0 @@
|
||||
/** 仓库库存动销分析 —— 表头与口径说明（与需求表一致） */
|
||||
|
||||
export const STOCK_SALES_COLUMNS = [
|
||||
{
|
||||
key: 'warehouse',
|
||||
label: '仓库',
|
||||
tip: '聚水潭主仓（按 wms_co_id 单仓独立统计，不合并分仓）',
|
||||
},
|
||||
{
|
||||
key: 'grade',
|
||||
label: '动销等级',
|
||||
tip: '按单个 SKU 的日均销量分档：日销 = 统计窗口内已发货件数 / 窗口天数',
|
||||
},
|
||||
{
|
||||
key: 'skuCount',
|
||||
label: 'SKU数量',
|
||||
tip: '该动销等级下「有库存或有销量」的 SKU 个数',
|
||||
},
|
||||
{
|
||||
key: 'skuRatio',
|
||||
label: 'SKU占比',
|
||||
tip: '该等级 SKU 数量 ÷ 该仓库 SKU 总数',
|
||||
},
|
||||
{
|
||||
key: 'stockQty',
|
||||
label: '库存数量',
|
||||
tip: '该等级 SKU 的实时库存件数（jst_inventoryInfo，按 wms_co_id + sku_id 汇总）',
|
||||
},
|
||||
{
|
||||
key: 'stockRatio',
|
||||
label: '库存占比',
|
||||
tip: '该等级库存数量 ÷ 该仓库库存总件数',
|
||||
},
|
||||
{
|
||||
key: 'salesQty',
|
||||
label: '销量',
|
||||
tip: '统计窗口内该等级 SKU 的已发货件数（jst_Orders × jst_OrderItem，按 send_date，排除 Delete/Cancelled）',
|
||||
},
|
||||
];
|
||||
|
||||
export const STOCK_SALES_WINDOW_OPTIONS = [
|
||||
{ label: '近 7 天', value: 7 },
|
||||
{ label: '近 14 天', value: 14 },
|
||||
{ label: '近 30 天', value: 30 },
|
||||
];
|
||||
|
||||
export const STOCK_SALES_DEFAULT_DAYS = 30;
|
||||
|
||||
export const STOCK_SALES_DESCRIPTION = [
|
||||
'动销等级口径：按「单个 SKU 的日均销量（日销）」分档，日销 = 统计窗口内已发货件数 ÷ 窗口天数。',
|
||||
' 爆款：日销 ≥ 20；热卖款：10 ≤ 日销 ＜ 20；平销款：3 ≤ 日销 ＜ 10；',
|
||||
' 滞销款-1：1 ≤ 日销 ＜ 3；滞销款-2：0 ＜ 日销 ＜ 1；销售=0：窗口内无销量的 SKU。',
|
||||
'SKU数量 / 库存数量 / 销量：仓库内按等级汇总；「汇总」行为该仓库六个等级的合计。',
|
||||
'SKU占比 = 该等级 SKU 数量 ÷ 该仓库 SKU 总数；库存占比 = 该等级库存数量 ÷ 该仓库库存总件数。',
|
||||
'统计范围：只统计「有库存或有销量」的 SKU；库存为 0 且窗口内无销量的 SKU 已下架，不计入分母。',
|
||||
'库存取业务库实时库存表；销量取销售出库单（jst_Orders × jst_OrderItem，按 send_date，排除 Delete/Cancelled），与「每日进销存」发货口径一致。',
|
||||
];
|
||||
@ -119,14 +119,7 @@ const SIDEBAR_ROUTE_MAP = {
|
||||
activePath: '/planning/operation/mkh-bom-data',
|
||||
matchMode: 'prefix',
|
||||
},
|
||||
'warehouse-ship-timeliness': {
|
||||
path: '/planning/operation/warehouse-ship-timeliness',
|
||||
activePath: '/planning/operation/warehouse-ship-timeliness',
|
||||
matchMode: 'prefix',
|
||||
},
|
||||
'daily-inventory': { path: '/planning/operation/daily-inventory' },
|
||||
'stock-sales-analysis': { path: '/planning/operation/stock-sales-analysis' },
|
||||
'picking-bin-sales-analysis': { path: '/planning/operation/picking-bin-sales-analysis' },
|
||||
settings: { path: '/settings' },
|
||||
'online-desktop-users': { path: '/settings/online-desktop-users' },
|
||||
'desktop-execution-tasks': { path: '/settings/desktop-execution-tasks' },
|
||||
|
||||
@ -1,19 +1,8 @@
|
||||
import React, { useCallback, useEffect, useMemo, useState } from 'react';
|
||||
import {
|
||||
Alert, Button, DatePicker, Input, Modal, Select, Space, Spin, Switch, Table, Tag, TimePicker,
|
||||
Tooltip, Typography, Upload,
|
||||
} from 'antd';
|
||||
import {
|
||||
BellOutlined, InfoCircleOutlined, PlusOutlined, ReloadOutlined, UploadOutlined,
|
||||
} from '@ant-design/icons';
|
||||
import dayjs from 'dayjs';
|
||||
import { Alert, Button, Modal, Space, Spin, Table, Tooltip, Typography } from 'antd';
|
||||
import { InfoCircleOutlined, ReloadOutlined } from '@ant-design/icons';
|
||||
import { SycmPage } from '../../components/Common';
|
||||
import { getDailyInventory, importDailyInventoryOfficial } from '../../api/dailyInventory';
|
||||
import {
|
||||
getDailyInventoryNotificationConfig,
|
||||
runDailyInventoryNotificationTest,
|
||||
saveDailyInventoryNotificationConfig,
|
||||
} from '../../api/dailyInventoryNotification.js';
|
||||
import { getDailyInventory } from '../../api/dailyInventory';
|
||||
import {
|
||||
DAILY_INVENTORY_COLUMNS,
|
||||
COLUMN_SOURCE,
|
||||
@ -23,34 +12,6 @@ import './style.css';
|
||||
|
||||
const { Title, Text } = Typography;
|
||||
|
||||
const TIME_FORMAT = 'HH:mm';
|
||||
|
||||
/** 当前登录用户是否为管理员（决定「通知设置」入口是否可见） */
|
||||
function readIsAdmin() {
|
||||
try {
|
||||
const stored = JSON.parse(localStorage.getItem('auth_user') || 'null');
|
||||
if (stored?.role) return stored.role === 'admin';
|
||||
const token = localStorage.getItem('token') || '';
|
||||
const payload = JSON.parse(window.atob(token.split('.')[1].replace(/-/g, '+').replace(/_/g, '/')));
|
||||
return payload?.role === 'admin';
|
||||
} catch {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
/** 收件人名单规范化：去空、去重、限长（后端会再校验一次） */
|
||||
function normalizeRecipientList(list = []) {
|
||||
const seen = new Set();
|
||||
const result = [];
|
||||
for (const raw of list) {
|
||||
const name = String(raw ?? '').trim().slice(0, 50);
|
||||
if (!name || seen.has(name)) continue;
|
||||
seen.add(name);
|
||||
result.push(name);
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
const TipTitle = ({ tip, children }) => (
|
||||
<Tooltip title={tip}>
|
||||
<span className="daily-inventory-th-tip">{children}</span>
|
||||
@ -62,12 +23,12 @@ const int = (value) => {
|
||||
return Number(value).toLocaleString('zh-CN', { maximumFractionDigits: 0 });
|
||||
};
|
||||
|
||||
const percent = (value) => {
|
||||
const decimal = (value, digits = 1) => {
|
||||
if (value === null || value === undefined || value === '') return '—';
|
||||
return `${Number(value).toLocaleString('zh-CN', {
|
||||
minimumFractionDigits: 2,
|
||||
maximumFractionDigits: 2,
|
||||
})}%`;
|
||||
return Number(value).toLocaleString('zh-CN', {
|
||||
minimumFractionDigits: digits,
|
||||
maximumFractionDigits: digits,
|
||||
});
|
||||
};
|
||||
|
||||
/** 负数标红、正数标黑：出入库列以负数表示流出，便于一眼分辨方向 */
|
||||
@ -84,33 +45,11 @@ const DailyInventory = () => {
|
||||
const [data, setData] = useState(null);
|
||||
const [helpOpen, setHelpOpen] = useState(false);
|
||||
|
||||
// ── 定时截图通知设置 ──
|
||||
const isAdmin = useMemo(readIsAdmin, []);
|
||||
const [notifyOpen, setNotifyOpen] = useState(false);
|
||||
const [notifyLoading, setNotifyLoading] = useState(false);
|
||||
const [notifySaving, setNotifySaving] = useState(false);
|
||||
const [notifyTesting, setNotifyTesting] = useState(false);
|
||||
const [notifyConfig, setNotifyConfig] = useState(null);
|
||||
const [notifyResult, setNotifyResult] = useState(null);
|
||||
const [recipientDraft, setRecipientDraft] = useState('');
|
||||
const [notifyForm, setNotifyForm] = useState({ enabled: false, notifyTime: '01:00', recipients: [] });
|
||||
|
||||
// ── 业务日切换 + 聚水潭官方进销存导入 ──
|
||||
const [selectedDate, setSelectedDate] = useState(''); // 空 = 业务库最新业务日
|
||||
const [importOpen, setImportOpen] = useState(false);
|
||||
const [importDate, setImportDate] = useState(null);
|
||||
const [importFile, setImportFile] = useState(null);
|
||||
const [importing, setImporting] = useState(false);
|
||||
const [importResult, setImportResult] = useState(null);
|
||||
|
||||
const load = useCallback(async (force = false) => {
|
||||
const load = useCallback(async () => {
|
||||
setLoading(true);
|
||||
setError('');
|
||||
try {
|
||||
const params = {};
|
||||
if (selectedDate) params.date = selectedDate;
|
||||
if (force) params.refresh = '1';
|
||||
const res = await getDailyInventory(params);
|
||||
const res = await getDailyInventory();
|
||||
setData(res?.data ?? null);
|
||||
} catch (err) {
|
||||
setError(err?.response?.data?.error || err?.message || '每日进销存数据加载失败');
|
||||
@ -118,77 +57,35 @@ const DailyInventory = () => {
|
||||
} finally {
|
||||
setLoading(false);
|
||||
}
|
||||
}, [selectedDate]);
|
||||
}, []);
|
||||
|
||||
useEffect(() => { load(); }, [load]);
|
||||
|
||||
const items = useMemo(() => data?.items ?? [], [data]);
|
||||
|
||||
const officialFlowKeys = useMemo(() => new Set(data?.flowColumnsOfficial || []), [data]);
|
||||
|
||||
const columns = useMemo(() => DAILY_INVENTORY_COLUMNS.map((col) => {
|
||||
const isRuntime = col.source === COLUMN_SOURCE.runtime;
|
||||
const isUnavailable = col.source === COLUMN_SOURCE.unavailable;
|
||||
// 该列已导入聚水潭官方数据时，不再按「无数据来源」置灰
|
||||
const noSource = isUnavailable && !officialFlowKeys.has(col.key);
|
||||
return {
|
||||
title: <TipTitle tip={col.tip}>{col.label}</TipTitle>,
|
||||
dataIndex: col.key,
|
||||
key: col.key,
|
||||
align: col.key === 'warehouse' ? 'left' : 'right',
|
||||
width: col.key === 'warehouse' ? 260 : 130,
|
||||
width: col.key === 'warehouse' ? 240 : 130,
|
||||
fixed: col.key === 'warehouse' ? 'left' : undefined,
|
||||
className: isRuntime
|
||||
? 'daily-inventory-col--runtime'
|
||||
: (noSource ? 'daily-inventory-col--unavailable' : undefined),
|
||||
className: isRuntime ? 'daily-inventory-col--runtime' : undefined,
|
||||
render: (value, record) => {
|
||||
if (record?.isTotal) {
|
||||
// 合计行：四级库存量累加，周转率按「总发货 / 总库存」重算（后端已给出）
|
||||
if (col.key === 'warehouse') return <span className="daily-inventory-warehouse">{value}</span>;
|
||||
// 该列整体无数据来源时，合计行同样显示「—」，避免误读为 0
|
||||
if (value === null || value === undefined || value === '') {
|
||||
return <span className="daily-inventory-cell--na">—</span>;
|
||||
}
|
||||
if (col.key === 'turnoverDays') return percent(value);
|
||||
// 合计行：周转天数不累加，显示「—」
|
||||
if (col.key === 'turnoverDays') return '—';
|
||||
return int(value);
|
||||
}
|
||||
if (col.key === 'warehouse') {
|
||||
return (
|
||||
<span className="daily-inventory-warehouse">
|
||||
{value}
|
||||
{record?.source?.hasOfficial ? (
|
||||
<Tooltip title="该仓已导入聚水潭官方进销存，期初/流水/期末均为官方值">
|
||||
<Tag color="blue" className="daily-inventory-tag">官方</Tag>
|
||||
</Tooltip>
|
||||
) : (
|
||||
<Tooltip title="该仓未导入聚水潭官方进销存，数值为业务库推算（流水列可能缺 8 类单据）">
|
||||
<Tag className="daily-inventory-tag">推算</Tag>
|
||||
</Tooltip>
|
||||
)}
|
||||
</span>
|
||||
);
|
||||
}
|
||||
if (value === null || value === undefined || value === '') {
|
||||
return <span className="daily-inventory-cell--na">—</span>;
|
||||
}
|
||||
// 数据来源标记：官方值正常显示，业务库推算值标灰提示口径差异
|
||||
const cellSource = col.key === 'openingQty' ? record?.source?.opening
|
||||
: col.key === 'closingQty' ? record?.source?.closing
|
||||
: record?.source?.flows?.[col.key];
|
||||
const wrap = (node) => (cellSource === 'derived' ? (
|
||||
<Tooltip title="业务库推算值，口径与聚水潭进销存存在差异；导入该业务日的聚水潭导出后自动切换为官方值">
|
||||
<span className="daily-inventory-cell--derived">{node}</span>
|
||||
</Tooltip>
|
||||
) : node);
|
||||
|
||||
if (col.key === 'openingQty' || col.key === 'openingQtyExtra' || col.key === 'closingQty') {
|
||||
return wrap(int(value));
|
||||
}
|
||||
if (col.key === 'turnoverDays') return percent(value);
|
||||
return wrap(renderSigned(value));
|
||||
if (col.key === 'warehouse') return <span className="daily-inventory-warehouse">{value}</span>;
|
||||
if (col.key === 'closingQty') return int(value);
|
||||
if (col.key === 'turnoverDays') return decimal(value, 1);
|
||||
return renderSigned(value);
|
||||
},
|
||||
};
|
||||
}), [officialFlowKeys]);
|
||||
}), []);
|
||||
|
||||
const tableRows = useMemo(() => {
|
||||
if (!data?.totals) return items;
|
||||
@ -197,159 +94,6 @@ const DailyInventory = () => {
|
||||
|
||||
const noGradeCount = useMemo(() => items.filter((it) => !it.hasGrade).length, [items]);
|
||||
|
||||
/** 业务日下拉：最新业务日 + 已导入聚水潭官方数据的日期 */
|
||||
const dateOptions = useMemo(() => {
|
||||
const opts = [{
|
||||
value: '__latest__',
|
||||
label: `最新业务日${data?.systemBizDate ? `（${data.systemBizDate}）` : ''}`,
|
||||
}];
|
||||
(data?.official?.availableDates || [])
|
||||
.filter((d) => d !== data?.systemBizDate)
|
||||
.forEach((d) => opts.push({ value: d, label: `${d}（聚水潭官方）` }));
|
||||
return opts;
|
||||
}, [data]);
|
||||
|
||||
const openImport = useCallback(() => {
|
||||
setImportResult(null);
|
||||
setImportFile(null);
|
||||
setImportDate(data?.latestBizDate ? dayjs(data.latestBizDate) : dayjs());
|
||||
setImportOpen(true);
|
||||
}, [data]);
|
||||
|
||||
const submitImport = useCallback(async () => {
|
||||
if (!importFile) {
|
||||
setImportResult({ type: 'error', text: '请先选择聚水潭导出的 xlsx 文件' });
|
||||
return;
|
||||
}
|
||||
if (!importDate) {
|
||||
setImportResult({ type: 'error', text: '请选择业务日期' });
|
||||
return;
|
||||
}
|
||||
setImporting(true);
|
||||
setImportResult(null);
|
||||
try {
|
||||
const res = await importDailyInventoryOfficial({
|
||||
file: importFile,
|
||||
date: importDate.format('YYYY-MM-DD'),
|
||||
});
|
||||
const result = res?.data ?? {};
|
||||
const bizDate = result.bizDate || importDate.format('YYYY-MM-DD');
|
||||
const notes = [
|
||||
...(result.warnings || []),
|
||||
...(result.unknownWarehouses || []).map((w) => `未匹配到仓库 ID，已按仓库名存档：${w}`),
|
||||
...(result.mismatches || []).map((m) => `${m.warehouse}：期初 + 流水 − 期末 = ${m.diff}`),
|
||||
];
|
||||
setImportResult({
|
||||
type: 'success',
|
||||
text: `${bizDate} 已导入 ${result.imported || 0} 个仓库${result.mismatches?.length ? '，存在恒等式不闭合的仓库' : '，恒等式逐仓闭合'}`,
|
||||
notes,
|
||||
});
|
||||
if (selectedDate === bizDate) await load(true);
|
||||
else setSelectedDate(bizDate);
|
||||
} catch (err) {
|
||||
setImportResult({
|
||||
type: 'error',
|
||||
text: err?.response?.data?.error || err?.message || '导入失败',
|
||||
notes: err?.response?.data?.detail ? [err.response.data.detail] : [],
|
||||
});
|
||||
} finally {
|
||||
setImporting(false);
|
||||
}
|
||||
}, [importFile, importDate, selectedDate, load]);
|
||||
|
||||
// ── 通知设置：读取 / 保存 / 立即测试 ──
|
||||
const applyNotifyConfig = useCallback((config = {}) => {
|
||||
setNotifyConfig(config);
|
||||
setNotifyForm({
|
||||
enabled: config.enabled === true,
|
||||
notifyTime: config.notifyTime || '01:00',
|
||||
recipients: normalizeRecipientList(config.recipients || []),
|
||||
});
|
||||
}, []);
|
||||
|
||||
const loadNotifyConfig = useCallback(async () => {
|
||||
setNotifyLoading(true);
|
||||
try {
|
||||
const res = await getDailyInventoryNotificationConfig();
|
||||
applyNotifyConfig(res?.data ?? {});
|
||||
} catch (err) {
|
||||
setNotifyConfig({ loadError: err?.response?.data?.error || err?.message || '加载通知设置失败' });
|
||||
} finally {
|
||||
setNotifyLoading(false);
|
||||
}
|
||||
}, [applyNotifyConfig]);
|
||||
|
||||
useEffect(() => {
|
||||
if (notifyOpen) {
|
||||
setNotifyResult(null);
|
||||
loadNotifyConfig();
|
||||
}
|
||||
}, [notifyOpen, loadNotifyConfig]);
|
||||
|
||||
const saveNotifySettings = useCallback(async () => {
|
||||
setNotifySaving(true);
|
||||
setNotifyResult(null);
|
||||
try {
|
||||
const res = await saveDailyInventoryNotificationConfig({
|
||||
enabled: notifyForm.enabled,
|
||||
notifyTime: notifyForm.notifyTime,
|
||||
recipients: normalizeRecipientList(notifyForm.recipients),
|
||||
});
|
||||
applyNotifyConfig(res?.data?.admin ?? res?.data ?? {});
|
||||
setNotifyResult({ type: 'success', text: '通知设置已保存' });
|
||||
} catch (err) {
|
||||
setNotifyResult({
|
||||
type: 'error',
|
||||
text: err?.response?.data?.error || err?.message || '保存通知设置失败',
|
||||
});
|
||||
} finally {
|
||||
setNotifySaving(false);
|
||||
}
|
||||
}, [notifyForm, applyNotifyConfig]);
|
||||
|
||||
const runNotifyTest = useCallback(async () => {
|
||||
setNotifyTesting(true);
|
||||
setNotifyResult(null);
|
||||
try {
|
||||
const res = await runDailyInventoryNotificationTest();
|
||||
const result = res?.data ?? {};
|
||||
if (result.success) {
|
||||
setNotifyResult({
|
||||
type: 'success',
|
||||
text: `测试完成：截图已上传，成功通知 ${(result.recipients || []).filter((r) => r.status === 'sent').length} 人`,
|
||||
url: result.screenshotUrl,
|
||||
});
|
||||
} else {
|
||||
setNotifyResult({ type: 'error', text: `测试未成功：${result.error || result.reason || '未知原因'}` });
|
||||
}
|
||||
loadNotifyConfig();
|
||||
} catch (err) {
|
||||
setNotifyResult({
|
||||
type: 'error',
|
||||
text: err?.response?.data?.error || err?.message || '执行测试失败',
|
||||
});
|
||||
} finally {
|
||||
setNotifyTesting(false);
|
||||
}
|
||||
}, [loadNotifyConfig]);
|
||||
|
||||
const addRecipients = useCallback(() => {
|
||||
const incoming = normalizeRecipientList(String(recipientDraft || '').split(/[,，;；\n]+/));
|
||||
if (!incoming.length) return;
|
||||
setNotifyForm((old) => ({
|
||||
...old,
|
||||
recipients: normalizeRecipientList([...(old.recipients || []), ...incoming]),
|
||||
}));
|
||||
setRecipientDraft('');
|
||||
}, [recipientDraft]);
|
||||
|
||||
const removeRecipient = useCallback((name) => {
|
||||
setNotifyForm((old) => ({
|
||||
...old,
|
||||
recipients: (old.recipients || []).filter((item) => item !== name),
|
||||
}));
|
||||
}, []);
|
||||
|
||||
return (
|
||||
<SycmPage className="daily-inventory-page">
|
||||
<div className="daily-inventory-header">
|
||||
@ -365,71 +109,29 @@ const DailyInventory = () => {
|
||||
</Button>
|
||||
</div>
|
||||
<div className="daily-inventory-header__meta">
|
||||
<span>期初日期：{data?.openingDate || '—'}</span>
|
||||
<span>基准日期：{data?.baselineDate || '—'}</span>
|
||||
<span>库存快照日：{data?.latestBizDate || '—'}</span>
|
||||
<span>分级基准时刻：{data?.asOf || '—'}</span>
|
||||
{data?.shipWindow ? (
|
||||
<span>
|
||||
发货统计窗口：{data.shipWindow.shipFrom} ~ {data.shipWindow.shipTo}（近 {data.shipWindow.days} 天）
|
||||
</span>
|
||||
) : null}
|
||||
{data?.items?.[0]?.closingTakenAt ? (
|
||||
<span>
|
||||
库存取数时间：{new Date(data.items[0].closingTakenAt).toLocaleString('zh-CN', { hour12: false })}
|
||||
</span>
|
||||
) : null}
|
||||
</div>
|
||||
<Space wrap>
|
||||
<Tooltip title="切换业务日：导入过聚水潭进销存导出的日期会以官方值显示">
|
||||
<Select
|
||||
style={{ width: 210 }}
|
||||
value={selectedDate || '__latest__'}
|
||||
onChange={(v) => setSelectedDate(v === '__latest__' ? '' : v)}
|
||||
options={dateOptions}
|
||||
/>
|
||||
</Tooltip>
|
||||
{isAdmin ? (
|
||||
<Tooltip title="上传聚水潭「进销存按仓导出」xlsx，按业务日校正期初 / 12 个流水列 / 期末">
|
||||
<Button icon={<UploadOutlined />} onClick={openImport}>导入聚水潭进销存</Button>
|
||||
</Tooltip>
|
||||
) : null}
|
||||
{isAdmin ? (
|
||||
<Button icon={<BellOutlined />} onClick={() => setNotifyOpen(true)}>通知设置</Button>
|
||||
) : null}
|
||||
<Button icon={<ReloadOutlined />} onClick={() => load(false)} loading={loading}>刷新</Button>
|
||||
<Tooltip title="跳过 5 分钟缓存，重新扫描订单明细重算周转率与分级（约 15~20 秒）">
|
||||
<Button onClick={() => load(true)} loading={loading}>强制重算</Button>
|
||||
</Tooltip>
|
||||
<Space>
|
||||
<Button icon={<ReloadOutlined />} onClick={load} loading={loading}>刷新</Button>
|
||||
</Space>
|
||||
</div>
|
||||
|
||||
<Alert
|
||||
type={data?.official?.hasData ? 'success' : 'info'}
|
||||
type="info"
|
||||
showIcon
|
||||
message={data?.official?.hasData
|
||||
? `已按聚水潭官方进销存校正（${data.latestBizDate}）：12 个流水列全部为官方值`
|
||||
: '尚未导入聚水潭官方进销存：流水列为业务库推算值'}
|
||||
message="数据来源混合，请注意口径"
|
||||
description={
|
||||
<span>
|
||||
{data?.official?.hasData ? (
|
||||
<>
|
||||
本页 <b>{data.latestBizDate}</b> 的期初、12 个流水列、期末取自聚水潭「进销存按仓导出」，
|
||||
共 <b>{data.official.warehouseCount}</b> 个仓；
|
||||
{data.official.balanceMismatch?.length
|
||||
? `其中 ${data.official.balanceMismatch.length} 个仓「期初 + 流水 ≠ 期末」，请核对导出文件。`
|
||||
: '「期初 + 流水 = 期末」逐仓闭合。'}
|
||||
{' '}未纳入该导出的仓库仍用业务库推算（仓库列标记为「推算」）。
|
||||
可在右上角切换业务日或重新导入。
|
||||
</>
|
||||
) : (
|
||||
<>
|
||||
业务库只能还原 4／12 个流水列，且口径与聚水潭进销存不一致（采购按单据日期、销售按订单发货日期），
|
||||
调拨／盘点／加工／其它出入库没有对应单据表。
|
||||
请在右上角「导入聚水潭进销存」上传导出文件，导入后该业务日的期初与 12 个流水列即为官方值。
|
||||
</>
|
||||
)}
|
||||
{data?.staleMetrics ? ` 当前查看的是历史业务日 ${data.latestBizDate}，右侧周转率与四级库存量为当前实时口径。` : ''}
|
||||
{noGradeCount > 0 ? ` 其中 ${noGradeCount} 个仓在聚水潭库存表中无有效库存，周转率与四级库存量显示「—」。` : ''}
|
||||
期初数量与 12 个流水列取自 <b>{data?.baselineDate || '2026-09-22'}</b> 聚水潭进销存导出值（业务库缺少调拨／盘点／加工／其它出入库单据表，无法还原）；
|
||||
期末数量与右侧 5 列为运行时实时取数。悬浮表头可看每列口径。
|
||||
{noGradeCount > 0 ? ` 其中 ${noGradeCount} 个仓在库存快照中无数据，周转天数与四级库存量显示「—」。` : ''}
|
||||
</span>
|
||||
}
|
||||
style={{ marginBottom: 12 }}
|
||||
@ -452,216 +154,9 @@ const DailyInventory = () => {
|
||||
</Spin>
|
||||
|
||||
<Text type="secondary" className="daily-inventory-footer">
|
||||
共 {items.length} 个仓库；蓝色底纹列为运行时实时取数，灰色列为暂无单据来源，其余为本地快照表取值。
|
||||
共 {items.length} 个仓库；蓝色底纹列为运行时取数，其余为基准值。
|
||||
</Text>
|
||||
|
||||
<Modal
|
||||
title="定时截图通知"
|
||||
open={notifyOpen}
|
||||
onCancel={() => setNotifyOpen(false)}
|
||||
width={720}
|
||||
destroyOnHidden
|
||||
styles={{ body: { maxHeight: '62vh', overflowY: 'auto', paddingRight: 12 } }}
|
||||
footer={(
|
||||
<Space wrap>
|
||||
<Button type="primary" loading={notifySaving} disabled={notifyLoading} onClick={saveNotifySettings}>
|
||||
保存设置
|
||||
</Button>
|
||||
<Tooltip title="真实执行一次截图、上传与通知；测试不会占用正式推送的幂等记录">
|
||||
<Button loading={notifyTesting} disabled={notifyLoading} onClick={runNotifyTest}>
|
||||
立即测试
|
||||
</Button>
|
||||
</Tooltip>
|
||||
<Button onClick={() => setNotifyOpen(false)}>关闭</Button>
|
||||
</Space>
|
||||
)}
|
||||
>
|
||||
<Spin spinning={notifyLoading}>
|
||||
{notifyConfig?.loadError ? (
|
||||
<Alert type="error" showIcon message={notifyConfig.loadError} style={{ marginBottom: 12 }} />
|
||||
) : null}
|
||||
|
||||
{notifyConfig?.blockingReasons?.length ? (
|
||||
<Alert
|
||||
type="warning"
|
||||
showIcon
|
||||
style={{ marginBottom: 12 }}
|
||||
message="当前不会自动推送，原因如下"
|
||||
description={<span>{notifyConfig.blockingReasons.join('；')}</span>}
|
||||
/>
|
||||
) : null}
|
||||
|
||||
<div className="daily-inventory-notify-form">
|
||||
<div className="daily-inventory-notify-row">
|
||||
<span className="daily-inventory-notify-label">启用每日截图通知</span>
|
||||
<Switch
|
||||
checked={notifyForm.enabled}
|
||||
onChange={(checked) => setNotifyForm((old) => ({ ...old, enabled: checked }))}
|
||||
/>
|
||||
</div>
|
||||
|
||||
<div className="daily-inventory-notify-row">
|
||||
<span className="daily-inventory-notify-label">通知时间</span>
|
||||
<TimePicker
|
||||
format={TIME_FORMAT}
|
||||
minuteStep={5}
|
||||
allowClear={false}
|
||||
value={dayjs(`2026-01-01T${notifyForm.notifyTime}:00`)}
|
||||
onChange={(value) => setNotifyForm((old) => ({
|
||||
...old,
|
||||
notifyTime: value ? value.format(TIME_FORMAT) : '01:00',
|
||||
}))}
|
||||
style={{ width: 140 }}
|
||||
/>
|
||||
<Text type="secondary">（{notifyConfig?.timezone || 'Asia/Shanghai'}，默认 01:00）</Text>
|
||||
</div>
|
||||
|
||||
<div className="daily-inventory-notify-row">
|
||||
<span className="daily-inventory-notify-label">通知用户</span>
|
||||
<Input
|
||||
allowClear
|
||||
placeholder="输入通知中心中的姓名或别名，回车添加；多个可用逗号分隔"
|
||||
value={recipientDraft}
|
||||
onChange={(e) => setRecipientDraft(e.target.value)}
|
||||
onPressEnter={addRecipients}
|
||||
style={{ width: 320 }}
|
||||
/>
|
||||
<Button icon={<PlusOutlined />} onClick={addRecipients} disabled={!String(recipientDraft || '').trim()}>
|
||||
添加
|
||||
</Button>
|
||||
</div>
|
||||
|
||||
<div className="daily-inventory-notify-recipients">
|
||||
{notifyForm.recipients.length ? (
|
||||
notifyForm.recipients.map((name) => (
|
||||
<Tag key={name} closable onClose={() => removeRecipient(name)}>{name}</Tag>
|
||||
))
|
||||
) : (
|
||||
<Text type="secondary">尚未添加通知用户</Text>
|
||||
)}
|
||||
</div>
|
||||
<Text type="secondary">
|
||||
自动去除空值与重复姓名，最多 {notifyConfig?.maxRecipients || 20} 人。
|
||||
</Text>
|
||||
</div>
|
||||
|
||||
{notifyResult ? (
|
||||
<Alert
|
||||
type={notifyResult.type}
|
||||
showIcon
|
||||
style={{ marginTop: 12 }}
|
||||
message={notifyResult.text}
|
||||
description={notifyResult.url ? (
|
||||
<a href={notifyResult.url} target="_blank" rel="noreferrer">{notifyResult.url}</a>
|
||||
) : null}
|
||||
/>
|
||||
) : null}
|
||||
|
||||
{notifyConfig && !notifyConfig.loadError ? (
|
||||
<div className="daily-inventory-notify-meta">
|
||||
<div>
|
||||
统一通知中心：
|
||||
<Text type={notifyConfig.notificationCenter?.configured ? 'success' : 'warning'} strong>
|
||||
{notifyConfig.notificationCenter?.configured ? '已配置' : '未配置'}
|
||||
</Text>
|
||||
{notifyConfig.notificationCenter?.baseUrl ? (
|
||||
<Text type="secondary">{` ${notifyConfig.notificationCenter.baseUrl}`}</Text>
|
||||
) : null}
|
||||
</div>
|
||||
<div>
|
||||
对象存储：
|
||||
<Text type={notifyConfig.objectStorage?.configured ? 'success' : 'warning'} strong>
|
||||
{notifyConfig.objectStorage?.configured ? '已配置' : '未配置'}
|
||||
</Text>
|
||||
{notifyConfig.objectStorage?.bucket ? (
|
||||
<Text type="secondary">{` 桶 ${notifyConfig.objectStorage.bucket}`}</Text>
|
||||
) : null}
|
||||
</div>
|
||||
<div>
|
||||
上次执行：
|
||||
<b>{notifyConfig.lastRunAt ? new Date(notifyConfig.lastRunAt).toLocaleString('zh-CN') : '—'}</b>
|
||||
{notifyConfig.lastRunSuccess === null ? '' : (
|
||||
<Text type={notifyConfig.lastRunSuccess ? 'success' : 'danger'}>
|
||||
{` ${notifyConfig.lastRunSuccess ? '成功' : '失败'}`}
|
||||
</Text>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
) : null}
|
||||
|
||||
{notifyConfig?.runs?.length ? (
|
||||
<div className="daily-inventory-notify-runs">
|
||||
<Text strong>最近执行记录</Text>
|
||||
{notifyConfig.runs.slice(0, 5).map((run, index) => (
|
||||
<div key={`${run.runAt}-${index}`} className="daily-inventory-notify-run">
|
||||
<span>{new Date(run.runAt).toLocaleString('zh-CN')}</span>
|
||||
<Text type={run.success ? 'success' : 'danger'}>
|
||||
{run.success ? '成功' : `失败（${run.error || run.reason || '未知原因'}）`}
|
||||
</Text>
|
||||
{run.screenshotUrl ? (
|
||||
<a href={run.screenshotUrl} target="_blank" rel="noreferrer">截图</a>
|
||||
) : null}
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
) : null}
|
||||
</Spin>
|
||||
</Modal>
|
||||
|
||||
<Modal
|
||||
title="导入聚水潭进销存（按仓）"
|
||||
open={importOpen}
|
||||
onCancel={() => setImportOpen(false)}
|
||||
width={620}
|
||||
destroyOnHidden
|
||||
footer={(
|
||||
<Space wrap>
|
||||
<Button type="primary" loading={importing} onClick={submitImport}>开始导入</Button>
|
||||
<Button onClick={() => setImportOpen(false)}>关闭</Button>
|
||||
</Space>
|
||||
)}
|
||||
>
|
||||
<div className="daily-inventory-import">
|
||||
<div className="daily-inventory-import-row">
|
||||
<span className="daily-inventory-import-label">业务日期</span>
|
||||
<DatePicker
|
||||
value={importDate}
|
||||
onChange={(v) => setImportDate(v)}
|
||||
allowClear={false}
|
||||
style={{ width: 180 }}
|
||||
/>
|
||||
<Text type="secondary">导出文件对应的进销存日期</Text>
|
||||
</div>
|
||||
<div className="daily-inventory-import-row">
|
||||
<span className="daily-inventory-import-label">导出文件</span>
|
||||
<Upload
|
||||
accept=".xlsx,.xls"
|
||||
maxCount={1}
|
||||
fileList={importFile ? [{ uid: 'import', name: importFile.name, status: 'done' }] : []}
|
||||
beforeUpload={(file) => { setImportFile(file); return false; }}
|
||||
onRemove={() => { setImportFile(null); return true; }}
|
||||
>
|
||||
<Button icon={<UploadOutlined />}>选择文件</Button>
|
||||
</Upload>
|
||||
</div>
|
||||
<Text type="secondary">
|
||||
需包含「仓库 / 期初数量 / 12 个流水列 / 期末数量」表头；同一业务日重复导入会整体覆盖。
|
||||
导入后会自动回写本地库存快照，使「今日期初 = 昨日结存」的推算也对齐聚水潭口径。
|
||||
</Text>
|
||||
{importResult ? (
|
||||
<Alert
|
||||
type={importResult.type}
|
||||
showIcon
|
||||
style={{ marginTop: 12 }}
|
||||
message={importResult.text}
|
||||
description={importResult.notes?.length
|
||||
? <span>{importResult.notes.join('；')}</span>
|
||||
: null}
|
||||
/>
|
||||
) : null}
|
||||
</div>
|
||||
</Modal>
|
||||
|
||||
<Modal
|
||||
title="计算口径说明"
|
||||
open={helpOpen}
|
||||
|
||||
@ -53,15 +53,6 @@
|
||||
background: rgba(22, 119, 255, 0.04);
|
||||
}
|
||||
|
||||
/* 暂无单据来源的列：淡灰底纹，提示该列待 DBA 补表 */
|
||||
.daily-inventory-table .daily-inventory-col--unavailable {
|
||||
background: rgba(0, 0, 0, 0.03);
|
||||
}
|
||||
|
||||
.daily-inventory-cell--na {
|
||||
color: rgba(0, 0, 0, 0.25);
|
||||
}
|
||||
|
||||
.daily-inventory-warehouse {
|
||||
white-space: nowrap;
|
||||
}
|
||||
@ -78,95 +69,11 @@
|
||||
color: rgba(0, 0, 0, 0.3);
|
||||
}
|
||||
|
||||
/* 业务库推算值：标灰 + 斜体，提示与聚水潭官方口径存在差异 */
|
||||
.daily-inventory-cell--derived {
|
||||
color: rgba(0, 0, 0, 0.42);
|
||||
font-style: italic;
|
||||
}
|
||||
|
||||
/* 仓库名后的来源标签 */
|
||||
.daily-inventory-tag {
|
||||
margin-left: 6px;
|
||||
transform: scale(0.85);
|
||||
transform-origin: left center;
|
||||
}
|
||||
|
||||
/* 导入聚水潭进销存弹窗 */
|
||||
.daily-inventory-import {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 12px;
|
||||
}
|
||||
|
||||
.daily-inventory-import-row {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: 10px;
|
||||
}
|
||||
|
||||
.daily-inventory-import-label {
|
||||
width: 72px;
|
||||
color: rgba(0, 0, 0, 0.75);
|
||||
}
|
||||
|
||||
.daily-inventory-row--total > td {
|
||||
font-weight: 600;
|
||||
background: rgba(0, 0, 0, 0.03);
|
||||
}
|
||||
|
||||
/* 定时截图通知设置弹窗 */
|
||||
.daily-inventory-notify-form {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 10px;
|
||||
}
|
||||
|
||||
.daily-inventory-notify-row {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: 8px;
|
||||
flex-wrap: wrap;
|
||||
}
|
||||
|
||||
.daily-inventory-notify-label {
|
||||
width: 120px;
|
||||
flex: none;
|
||||
color: rgba(0, 0, 0, 0.75);
|
||||
}
|
||||
|
||||
.daily-inventory-notify-recipients {
|
||||
display: flex;
|
||||
flex-wrap: wrap;
|
||||
gap: 6px;
|
||||
margin-left: 128px;
|
||||
min-height: 24px;
|
||||
}
|
||||
|
||||
.daily-inventory-notify-meta {
|
||||
margin-top: 14px;
|
||||
padding-top: 12px;
|
||||
border-top: 1px solid rgba(0, 0, 0, 0.08);
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 4px;
|
||||
font-size: 13px;
|
||||
}
|
||||
|
||||
.daily-inventory-notify-runs {
|
||||
margin-top: 12px;
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 4px;
|
||||
font-size: 12px;
|
||||
}
|
||||
|
||||
.daily-inventory-notify-run {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: 10px;
|
||||
color: rgba(0, 0, 0, 0.6);
|
||||
}
|
||||
|
||||
.daily-inventory-footer {
|
||||
font-size: 12px;
|
||||
}
|
||||
|
||||
@ -953,7 +953,6 @@ const MkhBomData = () => {
|
||||
<Text type="secondary">进度为查询阶段估算，实际完成以服务端返回为准。</Text>
|
||||
</Space>
|
||||
</Modal>
|
||||
|
||||
<header className="mkh-header">
|
||||
<div className="mkh-header__heading">
|
||||
<Title level={3}>MKH-BOM 资料</Title>
|
||||
|
||||
@ -1,288 +0,0 @@
|
||||
import React, { useCallback, useEffect, useMemo, useState } from 'react';
|
||||
import {
|
||||
Alert, Button, Card, Col, Input, Modal, Row, Select, Space, Spin, Statistic, Table, Tag, Tooltip, Typography, message,
|
||||
} from 'antd';
|
||||
import { DownloadOutlined, InfoCircleOutlined, ReloadOutlined } from '@ant-design/icons';
|
||||
import { SycmPage } from '../../components/Common';
|
||||
import {
|
||||
exportPickingBinSalesAnalysis,
|
||||
getPickingBinSalesAnalysis,
|
||||
} from '../../api/pickingBinSalesAnalysis';
|
||||
import { downloadBlobAsFile, readBlobErrorMessage } from '../../utils/tableExport';
|
||||
import {
|
||||
PICKING_BIN_COLUMNS,
|
||||
PICKING_BIN_WINDOW_OPTIONS,
|
||||
PICKING_BIN_DEFAULT_DAYS,
|
||||
PICKING_BIN_GRADE_COLORS,
|
||||
PICKING_BIN_DESCRIPTION,
|
||||
} from '../../constants/pickingBinSalesAnalysis';
|
||||
import './style.css';
|
||||
|
||||
const { Title, Text } = Typography;
|
||||
|
||||
const int = (value) => {
|
||||
if (value === null || value === undefined || value === '') return '—';
|
||||
return Number(value).toLocaleString('zh-CN', { maximumFractionDigits: 0 });
|
||||
};
|
||||
|
||||
const num = (value, digits = 2) => {
|
||||
if (value === null || value === undefined || value === '') return '—';
|
||||
return Number(value).toLocaleString('zh-CN', {
|
||||
minimumFractionDigits: digits,
|
||||
maximumFractionDigits: digits,
|
||||
});
|
||||
};
|
||||
|
||||
const TipTitle = ({ tip, children }) => (
|
||||
<Tooltip title={tip}>
|
||||
<span className="picking-bin-th-tip">{children}</span>
|
||||
</Tooltip>
|
||||
);
|
||||
|
||||
const PickingBinSalesAnalysis = () => {
|
||||
const [loading, setLoading] = useState(false);
|
||||
const [error, setError] = useState('');
|
||||
const [data, setData] = useState(null);
|
||||
const [helpOpen, setHelpOpen] = useState(false);
|
||||
const [days, setDays] = useState(PICKING_BIN_DEFAULT_DAYS);
|
||||
const [warehouse, setWarehouse] = useState('');
|
||||
const [grades, setGrades] = useState([]);
|
||||
const [keyword, setKeyword] = useState('');
|
||||
const [exporting, setExporting] = useState(false);
|
||||
|
||||
const params = useMemo(() => ({
|
||||
days,
|
||||
...(warehouse ? { wmsCoId: warehouse } : {}),
|
||||
}), [days, warehouse]);
|
||||
|
||||
const load = useCallback(async (options = {}) => {
|
||||
setLoading(true);
|
||||
setError('');
|
||||
try {
|
||||
const res = await getPickingBinSalesAnalysis({
|
||||
...(options.params ?? params),
|
||||
...(options.force ? { refresh: '1' } : {}),
|
||||
});
|
||||
setData(res?.data ?? null);
|
||||
} catch (err) {
|
||||
setError(err?.response?.data?.error || err?.message || '拣选库位动销分析数据加载失败');
|
||||
setData(null);
|
||||
} finally {
|
||||
setLoading(false);
|
||||
}
|
||||
}, [params]);
|
||||
|
||||
useEffect(() => { load(); }, [load]);
|
||||
|
||||
const items = useMemo(() => data?.items ?? [], [data]);
|
||||
const gradeMap = useMemo(() => new Map((data?.grades ?? []).map((g) => [g.key, g])), [data]);
|
||||
|
||||
const filteredRows = useMemo(() => {
|
||||
const kw = keyword.trim().toLowerCase();
|
||||
return items.filter((it) => {
|
||||
if (grades.length > 0 && !grades.includes(it.gradeKey)) return false;
|
||||
if (kw
|
||||
&& !String(it.binName).toLowerCase().includes(kw)
|
||||
&& !String(it.skuId).toLowerCase().includes(kw)) return false;
|
||||
return true;
|
||||
});
|
||||
}, [items, grades, keyword]);
|
||||
|
||||
const columns = useMemo(() => PICKING_BIN_COLUMNS.map((col) => ({
|
||||
title: <TipTitle tip={col.tip}>{col.label}</TipTitle>,
|
||||
key: col.key,
|
||||
dataIndex: col.key,
|
||||
align: ['warehouse', 'binName', 'binType', 'skuId', 'gradeKey'].includes(col.key) ? 'left' : 'right',
|
||||
width: col.key === 'warehouse' ? 240
|
||||
: (col.key === 'gradeKey' ? 170 : (col.key === 'skuId' ? 150 : 110)),
|
||||
sorter: ['stockQty', 'salesQty', 'dailySales'].includes(col.key)
|
||||
? (a, b) => (a[col.key] ?? 0) - (b[col.key] ?? 0)
|
||||
: undefined,
|
||||
render: (value) => {
|
||||
if (col.key === 'gradeKey') {
|
||||
const g = gradeMap.get(value);
|
||||
return <Tag color={PICKING_BIN_GRADE_COLORS[value] || 'default'}>{g?.label || value}</Tag>;
|
||||
}
|
||||
if (col.key === 'binType' || col.key === 'skuId') return <Text>{value || '—'}</Text>;
|
||||
if (col.key === 'dailySales') return num(value, 2);
|
||||
if (col.key === 'salesQty') return num(value, 2);
|
||||
if (col.key === 'stockQty') return int(value);
|
||||
return value || '—';
|
||||
},
|
||||
})), [gradeMap]);
|
||||
|
||||
const handleExport = useCallback(async () => {
|
||||
setExporting(true);
|
||||
try {
|
||||
const blob = await exportPickingBinSalesAnalysis({
|
||||
...params,
|
||||
...(grades.length > 0 ? { grade: grades.join(',') } : {}),
|
||||
format: 'xlsx',
|
||||
});
|
||||
const dateKey = (data?.latestBizDate || '').replace(/-/g, '') || '未知日期';
|
||||
const fileName = `拣选库位动销分析-${dateKey}.xlsx`;
|
||||
await downloadBlobAsFile(blob, fileName);
|
||||
message.success(`已开始下载：${fileName}`);
|
||||
} catch (exportError) {
|
||||
message.error(await readBlobErrorMessage(exportError, '库位动销明细导出失败'));
|
||||
} finally {
|
||||
setExporting(false);
|
||||
}
|
||||
}, [params, grades, data?.latestBizDate]);
|
||||
|
||||
const toggleGrade = useCallback((key) => {
|
||||
setGrades((prev) => (prev.includes(key) ? prev.filter((k) => k !== key) : [...prev, key]));
|
||||
}, []);
|
||||
|
||||
const summary = data?.summary ?? [];
|
||||
const total = data?.total ?? null;
|
||||
|
||||
return (
|
||||
<SycmPage className="picking-bin-page">
|
||||
<div className="picking-bin-header">
|
||||
<div className="picking-bin-header__title">
|
||||
<Title level={4} style={{ margin: 0 }}>拣选库位动销分析</Title>
|
||||
<Button
|
||||
type="text"
|
||||
icon={<InfoCircleOutlined />}
|
||||
onClick={() => setHelpOpen(true)}
|
||||
className="picking-bin-header__help"
|
||||
>
|
||||
口径说明
|
||||
</Button>
|
||||
</div>
|
||||
<div className="picking-bin-header__meta">
|
||||
<span>统计基准日：{data?.latestBizDate || '—'}</span>
|
||||
{data?.shipWindow ? (
|
||||
<span>销量窗口：{data.shipWindow.shipFrom} ~ {data.shipWindow.shipTo}（近 {data.shipWindow.days} 天）</span>
|
||||
) : null}
|
||||
{data?.takenAt ? (
|
||||
<span>仓位数据时间：{new Date(data.takenAt).toLocaleString('zh-CN', { hour12: false })}</span>
|
||||
) : null}
|
||||
</div>
|
||||
<Space wrap>
|
||||
<Space size={4}>
|
||||
<Text type="secondary">统计天数</Text>
|
||||
<Select
|
||||
value={days}
|
||||
options={PICKING_BIN_WINDOW_OPTIONS}
|
||||
onChange={setDays}
|
||||
style={{ width: 110 }}
|
||||
/>
|
||||
</Space>
|
||||
<Select
|
||||
allowClear
|
||||
value={warehouse || undefined}
|
||||
options={(data?.warehouses ?? []).map((w) => ({ label: w.warehouse, value: w.wmsCoId }))}
|
||||
onChange={(v) => setWarehouse(v || '')}
|
||||
showSearch
|
||||
optionFilterProp="label"
|
||||
style={{ minWidth: 240 }}
|
||||
placeholder="全部仓库"
|
||||
/>
|
||||
<Input.Search
|
||||
allowClear
|
||||
value={keyword}
|
||||
onChange={(e) => setKeyword(e.target.value)}
|
||||
placeholder="搜索仓位 / 商品编码"
|
||||
style={{ width: 180 }}
|
||||
/>
|
||||
<Button icon={<ReloadOutlined />} onClick={() => load()} loading={loading}>刷新</Button>
|
||||
<Tooltip title="跳过 5 分钟缓存，重新扫描订单与仓位明细重算（约 5~20 秒）">
|
||||
<Button onClick={() => load({ force: true })} loading={loading}>强制重算</Button>
|
||||
</Tooltip>
|
||||
<Tooltip title="导出当前筛选下的明细（仓库 / 仓位 / 类型 / 商品编码 / 库存数量 / 仓位SKU数 / 商品销量 / 分摊销量 / 商品日销 / 动销等级），仅含拣选位。按「仓位 × 商品编码」拆行；商品销量为整档销量（同一商品跨仓位重复，不可直接求和），需要求和请用「分摊销量」列；动销等级按商品日销判定">
|
||||
<Button icon={<DownloadOutlined />} onClick={handleExport} loading={exporting}>导出明细</Button>
|
||||
</Tooltip>
|
||||
</Space>
|
||||
</div>
|
||||
|
||||
<Alert
|
||||
type="info"
|
||||
showIcon
|
||||
message={`按「商品日均销量（商品日销）」划分 ${summary.length} 个动销等级，一行 = 一个「仓位 × 商品编码」组合`}
|
||||
description="商品日销 = 该商品近 N 天销量 ÷ N，不做仓位分摊，因此同一件商品放在几个仓位都是同一等级。商品销量跨仓位重复显示，不能直接按行求和（需要求和请导出用「分摊销量」列）。点击下方等级卡片可筛选。"
|
||||
style={{ marginBottom: 12 }}
|
||||
/>
|
||||
|
||||
{error ? <Alert type="error" showIcon message={error} style={{ marginBottom: 12 }} /> : null}
|
||||
|
||||
<Spin spinning={loading}>
|
||||
<Row gutter={[8, 8]} className="picking-bin-summary">
|
||||
{summary.map((s) => (
|
||||
<Col key={s.key} flex="1 1 150px">
|
||||
<Card
|
||||
size="small"
|
||||
hoverable
|
||||
onClick={() => toggleGrade(s.key)}
|
||||
className={grades.includes(s.key) ? 'picking-bin-card is-active' : 'picking-bin-card'}
|
||||
>
|
||||
<Tooltip title={`${s.tip}；明细 ${int(s.rowCount)} 行，库存合计 ${int(s.stockQty)} 件，日销合计 ${num(s.dailySales, 1)}（销量按去重商品计）`}>
|
||||
<Statistic
|
||||
title={s.label}
|
||||
value={s.skuCount}
|
||||
suffix="品"
|
||||
valueStyle={{ fontSize: 18 }}
|
||||
/>
|
||||
</Tooltip>
|
||||
<div className="picking-bin-card__meta">
|
||||
明细 {int(s.rowCount)} 行 · 库存 {int(s.stockQty)} · 日销 {num(s.dailySales, 1)}
|
||||
</div>
|
||||
</Card>
|
||||
</Col>
|
||||
))}
|
||||
{total ? (
|
||||
<Col flex="1 1 150px">
|
||||
<Card size="small" className="picking-bin-card is-total">
|
||||
<Tooltip title={`去重商品 ${int(total.skuCount)} 个，涉及「仓位 × 商品」组合 ${int(total.rowCount)} 行`}>
|
||||
<Statistic title={total.label} value={total.skuCount} suffix="品" valueStyle={{ fontSize: 18 }} />
|
||||
</Tooltip>
|
||||
<div className="picking-bin-card__meta">
|
||||
明细 {int(total.rowCount)} 行 · 库存 {int(total.stockQty)} · 日销 {num(total.dailySales, 1)}
|
||||
</div>
|
||||
</Card>
|
||||
</Col>
|
||||
) : null}
|
||||
</Row>
|
||||
|
||||
<Table
|
||||
className="picking-bin-table"
|
||||
columns={columns}
|
||||
dataSource={filteredRows}
|
||||
rowKey={(r) => `${r.wmsCoId}::${r.binName}::${r.skuId}`}
|
||||
size="small"
|
||||
bordered
|
||||
pagination={{
|
||||
pageSize: 50,
|
||||
showSizeChanger: true,
|
||||
pageSizeOptions: [50, 100, 200],
|
||||
showTotal: (t) => `共 ${t} 条明细`,
|
||||
}}
|
||||
scroll={{ x: 'max-content', y: 'calc(100vh - 420px)' }}
|
||||
/>
|
||||
</Spin>
|
||||
|
||||
<Text type="secondary" className="picking-bin-footer">
|
||||
当前筛选出 {filteredRows.length} 条明细
|
||||
{items.length !== filteredRows.length ? `（共 ${items.length} 条）` : ''}；
|
||||
去重商品 {int(data?.total?.skuCount ?? 0)} 个；统计范围：仅拣选位。
|
||||
</Text>
|
||||
|
||||
<Modal
|
||||
title="计算口径说明"
|
||||
open={helpOpen}
|
||||
onCancel={() => setHelpOpen(false)}
|
||||
footer={null}
|
||||
width={760}
|
||||
>
|
||||
<div className="picking-bin-help">
|
||||
{PICKING_BIN_DESCRIPTION.map((line, i) => (
|
||||
<p key={i} className={line.startsWith(' ') ? 'is-indent' : ''}>{line}</p>
|
||||
))}
|
||||
</div>
|
||||
</Modal>
|
||||
</SycmPage>
|
||||
);
|
||||
};
|
||||
|
||||
export default PickingBinSalesAnalysis;
|
||||
@ -1,95 +0,0 @@
|
||||
.picking-bin-page {
|
||||
padding: 16px 20px 24px;
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 12px;
|
||||
}
|
||||
|
||||
.picking-bin-header {
|
||||
display: flex;
|
||||
flex-wrap: wrap;
|
||||
align-items: center;
|
||||
justify-content: space-between;
|
||||
gap: 12px;
|
||||
}
|
||||
|
||||
.picking-bin-header__title {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: 4px;
|
||||
}
|
||||
|
||||
.picking-bin-header__help {
|
||||
font-size: 13px;
|
||||
}
|
||||
|
||||
.picking-bin-header__meta {
|
||||
display: flex;
|
||||
flex-wrap: wrap;
|
||||
gap: 16px;
|
||||
font-size: 13px;
|
||||
color: rgba(0, 0, 0, 0.55);
|
||||
}
|
||||
|
||||
.picking-bin-th-tip {
|
||||
border-bottom: 1px dashed rgba(0, 0, 0, 0.35);
|
||||
cursor: help;
|
||||
white-space: nowrap;
|
||||
}
|
||||
|
||||
.picking-bin-summary {
|
||||
margin-bottom: 12px;
|
||||
}
|
||||
|
||||
.picking-bin-card .ant-statistic-title {
|
||||
font-size: 12px;
|
||||
white-space: nowrap;
|
||||
overflow: hidden;
|
||||
text-overflow: ellipsis;
|
||||
}
|
||||
|
||||
.picking-bin-card.is-active {
|
||||
border-color: #1677ff;
|
||||
box-shadow: 0 0 0 2px rgba(22, 119, 255, 0.12);
|
||||
}
|
||||
|
||||
.picking-bin-card.is-total {
|
||||
background: rgba(22, 119, 255, 0.06);
|
||||
}
|
||||
|
||||
.picking-bin-card__meta {
|
||||
margin-top: 4px;
|
||||
font-size: 12px;
|
||||
color: rgba(0, 0, 0, 0.55);
|
||||
white-space: nowrap;
|
||||
overflow: hidden;
|
||||
text-overflow: ellipsis;
|
||||
}
|
||||
|
||||
.picking-bin-table .ant-table-thead > tr > th {
|
||||
white-space: nowrap;
|
||||
font-size: 12px;
|
||||
padding: 6px 8px;
|
||||
}
|
||||
|
||||
.picking-bin-table .ant-table-tbody > tr > td {
|
||||
padding: 5px 8px;
|
||||
font-size: 13px;
|
||||
vertical-align: middle;
|
||||
}
|
||||
|
||||
.picking-bin-footer {
|
||||
font-size: 12px;
|
||||
}
|
||||
|
||||
.picking-bin-help p {
|
||||
margin: 0 0 6px;
|
||||
line-height: 1.7;
|
||||
font-size: 13px;
|
||||
white-space: pre-wrap;
|
||||
}
|
||||
|
||||
.picking-bin-help p.is-indent {
|
||||
padding-left: 16px;
|
||||
color: rgba(0, 0, 0, 0.65);
|
||||
}
|
||||
@ -71,25 +71,6 @@ const RETURN_DEADLINE_TAGS = {
|
||||
};
|
||||
const RETURN_DEADLINE_RANK = { overdue: 3, pending: 2, done: 1, none: 0 };
|
||||
|
||||
// 供应商是否合作（后端取自简尚供应商主数据 js_supplier.coopersgn：1=合作 / 2=不合作）
|
||||
const SUPPLIER_COOP_TAGS = {
|
||||
cooperative: { color: 'green', label: '合作' },
|
||||
ended: { color: 'red', label: '不合作' },
|
||||
unknown: { color: 'default', label: '未知' },
|
||||
};
|
||||
const SUPPLIER_COOP_RANK = { ended: 2, cooperative: 1, unknown: 0 };
|
||||
const SUPPLIER_COOP_TIPS = {
|
||||
cooperative: '该商品编码的供应商在简尚供应商主数据里标记为「合作中」（js_supplier.coopersgn = 1）',
|
||||
ended: '该商品编码的供应商在简尚供应商主数据里标记为「不合作」（js_supplier.coopersgn = 2），退货处理需另行商定对接人',
|
||||
unknown: '供应商名在简尚供应商主数据（js_supplier）里没有匹配记录，或该编码没有供应商，无法判断合作状态',
|
||||
};
|
||||
|
||||
// 最晚退厂时间（工作平台「供应商不合作」）—— 2026-09-28 先上线占位：
|
||||
// 数据属于工作平台库 WorkbenchDataShared，副本账号目前没有该库访问权限（后端
|
||||
// supplierExitDateProvider.js 有完整取证），IT 开通后自动出数，页面无需再改。
|
||||
const EXIT_DATE_PENDING_TIP = '数据来源：工作平台（WorkbenchDataShared）· 供应商不合作。该库当前未授权给副本账号，待 IT 开通只读权限（或把该表同步进报表副本）后自动显示最晚退厂日期。';
|
||||
const EXIT_DATE_VALUE_TIP = '工作平台「供应商不合作」给出的最晚退厂日期：该供应商放在仓里的货最后必须拉走的日期';
|
||||
|
||||
// 预警等级过滤：主视图改成一排状态页签（全部 / 红色预警 / 关注 / 正常 / 未知），
|
||||
// 因此不再需要下拉选项；导出时仍把 warningLevel 原样传给后端（服务端 filter 同口径）。
|
||||
|
||||
@ -367,42 +348,11 @@ const COLUMNS = [
|
||||
},
|
||||
},
|
||||
{
|
||||
title: '供应商是否合作',
|
||||
dataIndex: 'supplierCoop',
|
||||
width: 136,
|
||||
title: '是否出库',
|
||||
dataIndex: 'isOutbound',
|
||||
width: 90,
|
||||
align: 'center',
|
||||
sorter: (a, b) => (SUPPLIER_COOP_RANK[a.supplierCoop] || 0) - (SUPPLIER_COOP_RANK[b.supplierCoop] || 0),
|
||||
render: (value) => {
|
||||
const tag = SUPPLIER_COOP_TAGS[value] || SUPPLIER_COOP_TAGS.unknown;
|
||||
return (
|
||||
<Tooltip title={SUPPLIER_COOP_TIPS[value] || SUPPLIER_COOP_TIPS.unknown}>
|
||||
<Tag color={tag.color}>{tag.label}</Tag>
|
||||
</Tooltip>
|
||||
);
|
||||
},
|
||||
},
|
||||
{
|
||||
title: '最晚退厂时间',
|
||||
dataIndex: 'latestExitDateLabel',
|
||||
width: 132,
|
||||
align: 'center',
|
||||
sorter: (a, b) => String(a.latestExitDateLabel || '').localeCompare(String(b.latestExitDateLabel || '')),
|
||||
render: (value, record) => {
|
||||
if (value) {
|
||||
return (
|
||||
<Tooltip title={EXIT_DATE_VALUE_TIP}>
|
||||
<Tag color="orange">{value}</Tag>
|
||||
</Tooltip>
|
||||
);
|
||||
}
|
||||
// 已接入但该供应商没有退厂日期 → 显示破折号；整列未接入 → 显示「待接入」
|
||||
if (record?.latestExitDateAvailable) return <span className="rsw-exit-date-empty">—</span>;
|
||||
return (
|
||||
<Tooltip title={EXIT_DATE_PENDING_TIP}>
|
||||
<Tag color="default">待接入</Tag>
|
||||
</Tooltip>
|
||||
);
|
||||
},
|
||||
render: (value) => (value ? <Tag color="green">是</Tag> : <Tag>否</Tag>),
|
||||
},
|
||||
{
|
||||
title: '创建时间来源',
|
||||
@ -455,8 +405,6 @@ const StockWarning = ({ warehouse }) => {
|
||||
rows: [], total: 0, summary: {}, warehouse: '', warehouseName: '', returnSlot: '',
|
||||
warehouseHasReturnStock: true, statDate: '', stockSyncedAt: '', gaps: [], import: null,
|
||||
hasImport: false,
|
||||
// 最晚退厂时间数据源状态（工作平台库未接入时为 available:false + message）
|
||||
exitDateMeta: { available: false, sourceLabel: '', message: '' },
|
||||
});
|
||||
const [loading, setLoading] = useState(false);
|
||||
const [exporting, setExporting] = useState(false);
|
||||
@ -495,7 +443,6 @@ const StockWarning = ({ warehouse }) => {
|
||||
gaps: payload.gaps || [],
|
||||
import: payload.import || null,
|
||||
hasImport: Boolean(payload.hasImport),
|
||||
exitDateMeta: payload.exitDateMeta || { available: false, sourceLabel: '', message: '' },
|
||||
});
|
||||
} catch (requestError) {
|
||||
setError(requestError?.response?.data?.error || requestError?.message || '加载客退数据监控失败');
|
||||
|
||||
@ -648,11 +648,6 @@
|
||||
font-weight: 600;
|
||||
}
|
||||
|
||||
/* 表格「最晚退厂时间」列：数据源已接入但该供应商无日期时的占位符 */
|
||||
.rsw-exit-date-empty {
|
||||
color: var(--sycm-text-quaternary, #bfbfbf);
|
||||
}
|
||||
|
||||
/* ── 退货库存预警：图表区 ─────────────────────────────────── */
|
||||
.rsw-charts {
|
||||
display: grid;
|
||||
|
||||
@ -1,267 +0,0 @@
|
||||
import React, { useCallback, useEffect, useMemo, useState } from 'react';
|
||||
import {
|
||||
Alert, Button, Modal, Select, Space, Spin, Table, Tooltip, Typography, message,
|
||||
} from 'antd';
|
||||
import { DownloadOutlined, InfoCircleOutlined, ReloadOutlined } from '@ant-design/icons';
|
||||
import { SycmPage } from '../../components/Common';
|
||||
import { exportStockSalesZeroDetail, getStockSalesAnalysis } from '../../api/stockSalesAnalysis';
|
||||
import { downloadBlobAsFile, readBlobErrorMessage } from '../../utils/tableExport';
|
||||
import {
|
||||
STOCK_SALES_COLUMNS,
|
||||
STOCK_SALES_WINDOW_OPTIONS,
|
||||
STOCK_SALES_DEFAULT_DAYS,
|
||||
STOCK_SALES_DESCRIPTION,
|
||||
} from '../../constants/stockSalesAnalysis';
|
||||
import './style.css';
|
||||
|
||||
const { Title, Text } = Typography;
|
||||
|
||||
const ALL_WAREHOUSES = '__all__';
|
||||
|
||||
const int = (value) => {
|
||||
if (value === null || value === undefined || value === '') return '—';
|
||||
return Number(value).toLocaleString('zh-CN', { maximumFractionDigits: 0 });
|
||||
};
|
||||
|
||||
const percent = (value) => {
|
||||
if (value === null || value === undefined || value === '') return '—';
|
||||
return `${(Number(value) * 100).toLocaleString('zh-CN', {
|
||||
minimumFractionDigits: 2,
|
||||
maximumFractionDigits: 2,
|
||||
})}%`;
|
||||
};
|
||||
|
||||
const TipTitle = ({ tip, children }) => (
|
||||
<Tooltip title={tip}>
|
||||
<span className="stock-sales-th-tip">{children}</span>
|
||||
</Tooltip>
|
||||
);
|
||||
|
||||
const StockSalesAnalysis = () => {
|
||||
const [loading, setLoading] = useState(false);
|
||||
const [error, setError] = useState('');
|
||||
const [data, setData] = useState(null);
|
||||
const [helpOpen, setHelpOpen] = useState(false);
|
||||
const [days, setDays] = useState(STOCK_SALES_DEFAULT_DAYS);
|
||||
const [warehouse, setWarehouse] = useState(ALL_WAREHOUSES);
|
||||
const [exporting, setExporting] = useState(false);
|
||||
|
||||
const load = useCallback(async (options = {}) => {
|
||||
setLoading(true);
|
||||
setError('');
|
||||
try {
|
||||
const res = await getStockSalesAnalysis({
|
||||
days: options.days ?? STOCK_SALES_DEFAULT_DAYS,
|
||||
...(options.force ? { refresh: '1' } : {}),
|
||||
});
|
||||
setData(res?.data ?? null);
|
||||
} catch (err) {
|
||||
setError(err?.response?.data?.error || err?.message || '库存动销分析数据加载失败');
|
||||
setData(null);
|
||||
} finally {
|
||||
setLoading(false);
|
||||
}
|
||||
}, []);
|
||||
|
||||
useEffect(() => { load({ days: STOCK_SALES_DEFAULT_DAYS }); }, [load]);
|
||||
|
||||
const handleDaysChange = useCallback((value) => {
|
||||
setDays(value);
|
||||
load({ days: value });
|
||||
}, [load]);
|
||||
|
||||
const items = useMemo(() => data?.items ?? [], [data]);
|
||||
const grand = data?.grand ?? null;
|
||||
|
||||
/** 导出「销售=0」档 SKU 明细：跟随当前统计天数与仓库筛选 */
|
||||
const handleExportZero = useCallback(async () => {
|
||||
setExporting(true);
|
||||
try {
|
||||
const wmsCoId = warehouse === ALL_WAREHOUSES
|
||||
? undefined
|
||||
: items.find((it) => it.warehouse === warehouse)?.wmsCoId;
|
||||
const params = { days, format: 'xlsx', ...(wmsCoId != null ? { wmsCoId: String(wmsCoId) } : {}) };
|
||||
const blob = await exportStockSalesZeroDetail(params);
|
||||
const dateKey = (data?.latestBizDate || '').replace(/-/g, '') || '未知日期';
|
||||
const scope = warehouse === ALL_WAREHOUSES ? '' : `-${warehouse}`;
|
||||
const fileName = `库存动销分析-销售0明细${scope}-${dateKey}.xlsx`;
|
||||
downloadBlobAsFile(blob, fileName);
|
||||
message.success(`已开始下载：${fileName}`);
|
||||
} catch (exportError) {
|
||||
message.error(await readBlobErrorMessage(exportError, '导出「销售=0」明细失败'));
|
||||
} finally {
|
||||
setExporting(false);
|
||||
}
|
||||
}, [days, warehouse, items, data?.latestBizDate]);
|
||||
|
||||
const warehouseOptions = useMemo(() => ([
|
||||
{ label: '全部仓库', value: ALL_WAREHOUSES },
|
||||
...items.map((it) => ({ label: it.warehouse, value: it.warehouse })),
|
||||
]), [items]);
|
||||
|
||||
const visibleItems = useMemo(() => (
|
||||
warehouse === ALL_WAREHOUSES ? items : items.filter((it) => it.warehouse === warehouse)
|
||||
), [items, warehouse]);
|
||||
|
||||
/** 表格行：每个仓库 6 个等级 + 1 行汇总；仓库列跨行合并 */
|
||||
const tableRows = useMemo(() => {
|
||||
const rows = [];
|
||||
const pushGroup = (warehouseName, buckets, total, extra = {}) => {
|
||||
// 注意：bucket / total 自带 key（等级 key），必须放在展开之后覆盖，否则跨仓行 key 会重复
|
||||
buckets.forEach((bucket, index) => {
|
||||
rows.push({
|
||||
...bucket,
|
||||
...extra,
|
||||
key: `${warehouseName}::${bucket.key}`,
|
||||
warehouse: warehouseName,
|
||||
warehouseRowSpan: index === 0 ? buckets.length + 1 : 0,
|
||||
grade: bucket.label,
|
||||
});
|
||||
});
|
||||
rows.push({
|
||||
...total,
|
||||
...extra,
|
||||
key: `${warehouseName}::__total__`,
|
||||
warehouse: warehouseName,
|
||||
warehouseRowSpan: 0,
|
||||
grade: total.label,
|
||||
isSubtotal: true,
|
||||
});
|
||||
};
|
||||
|
||||
visibleItems.forEach((item) => pushGroup(item.warehouse, item.buckets, item.total));
|
||||
if (grand && (warehouse === ALL_WAREHOUSES || visibleItems.length === 0)) {
|
||||
pushGroup(grand.warehouse, grand.buckets, grand.total, { isGrand: true });
|
||||
}
|
||||
return rows;
|
||||
}, [visibleItems, grand, warehouse]);
|
||||
|
||||
const columns = useMemo(() => STOCK_SALES_COLUMNS.map((col) => ({
|
||||
title: <TipTitle tip={col.tip}>{col.label}</TipTitle>,
|
||||
key: col.key,
|
||||
dataIndex: col.key,
|
||||
align: ['warehouse', 'grade'].includes(col.key) ? 'left' : 'right',
|
||||
width: col.key === 'warehouse' ? 260 : (col.key === 'grade' ? 180 : 130),
|
||||
fixed: col.key === 'warehouse' ? 'left' : undefined,
|
||||
onCell: col.key === 'warehouse'
|
||||
? (record) => ({ rowSpan: record.warehouseRowSpan })
|
||||
: undefined,
|
||||
render: (value, record) => {
|
||||
if (col.key === 'warehouse') {
|
||||
if (record.warehouseRowSpan === 0) return null;
|
||||
return <span className="stock-sales-warehouse">{value}</span>;
|
||||
}
|
||||
if (col.key === 'grade') {
|
||||
return <span className={record.isSubtotal ? 'stock-sales-grade is-total' : 'stock-sales-grade'}>{value}</span>;
|
||||
}
|
||||
if (col.key === 'skuRatio' || col.key === 'stockRatio') return percent(value);
|
||||
return int(value);
|
||||
},
|
||||
})), []);
|
||||
|
||||
const gradeCount = data?.grades?.length ?? 0;
|
||||
|
||||
return (
|
||||
<SycmPage className="stock-sales-page">
|
||||
<div className="stock-sales-header">
|
||||
<div className="stock-sales-header__title">
|
||||
<Title level={4} style={{ margin: 0 }}>库存动销分析</Title>
|
||||
<Button
|
||||
type="text"
|
||||
icon={<InfoCircleOutlined />}
|
||||
onClick={() => setHelpOpen(true)}
|
||||
className="stock-sales-header__help"
|
||||
>
|
||||
口径说明
|
||||
</Button>
|
||||
</div>
|
||||
<div className="stock-sales-header__meta">
|
||||
<span>统计基准日：{data?.latestBizDate || '—'}</span>
|
||||
{data?.shipWindow ? (
|
||||
<span>
|
||||
销量窗口：{data.shipWindow.shipFrom} ~ {data.shipWindow.shipTo}（近 {data.shipWindow.days} 天）
|
||||
</span>
|
||||
) : null}
|
||||
{data?.takenAt ? (
|
||||
<span>库存取数时间：{new Date(data.takenAt).toLocaleString('zh-CN', { hour12: false })}</span>
|
||||
) : null}
|
||||
</div>
|
||||
<Space wrap>
|
||||
<Space size={4}>
|
||||
<Text type="secondary">统计天数</Text>
|
||||
<Select
|
||||
value={days}
|
||||
options={STOCK_SALES_WINDOW_OPTIONS}
|
||||
onChange={handleDaysChange}
|
||||
style={{ width: 120 }}
|
||||
/>
|
||||
</Space>
|
||||
<Select
|
||||
value={warehouse}
|
||||
options={warehouseOptions}
|
||||
onChange={setWarehouse}
|
||||
showSearch
|
||||
optionFilterProp="label"
|
||||
style={{ minWidth: 240 }}
|
||||
placeholder="选择仓库"
|
||||
/>
|
||||
<Button icon={<ReloadOutlined />} onClick={() => load({ days })} loading={loading}>刷新</Button>
|
||||
<Tooltip title="跳过 5 分钟缓存，重新扫描订单明细与库存明细重算（约 5~20 秒）">
|
||||
<Button onClick={() => load({ days, force: true })} loading={loading}>强制重算</Button>
|
||||
</Tooltip>
|
||||
<Tooltip title="导出当前筛选下「销售=0」档的 SKU 明细（仓库 / SKU编码 / SKU名称 / 系统仓位 / 库存数量），跟随统计天数与仓库筛选；每个仓位独立一行，库存数量为该仓位的实际数量，仓位数据未覆盖的 SKU 保留一行（仓位留空、库存为总量）">
|
||||
<Button icon={<DownloadOutlined />} onClick={handleExportZero} loading={exporting}>导出销售=0</Button>
|
||||
</Tooltip>
|
||||
</Space>
|
||||
</div>
|
||||
|
||||
<Alert
|
||||
type="info"
|
||||
showIcon
|
||||
message={`按「单 SKU 日均销量」把库存拆成 ${gradeCount} 个动销等级，全部数值来自业务库实时取数`}
|
||||
description="库存取实时库存表，销量取销售出库单；占比为「该等级 ÷ 该仓库合计」。切换统计天数会按新窗口重算日销与分档。"
|
||||
style={{ marginBottom: 12 }}
|
||||
/>
|
||||
|
||||
{error ? <Alert type="error" showIcon message={error} style={{ marginBottom: 12 }} /> : null}
|
||||
|
||||
<Spin spinning={loading}>
|
||||
<Table
|
||||
className="stock-sales-table"
|
||||
columns={columns}
|
||||
dataSource={tableRows}
|
||||
rowKey="key"
|
||||
size="small"
|
||||
bordered
|
||||
pagination={false}
|
||||
scroll={{ x: 'max-content', y: 'calc(100vh - 320px)' }}
|
||||
rowClassName={(record) => [
|
||||
record?.isGrand ? 'stock-sales-row--grand' : '',
|
||||
record?.isSubtotal ? 'stock-sales-row--subtotal' : '',
|
||||
].filter(Boolean).join(' ')}
|
||||
/>
|
||||
</Spin>
|
||||
|
||||
<Text type="secondary" className="stock-sales-footer">
|
||||
共 {visibleItems.length} 个仓库；每个仓库 {gradeCount} 个动销等级 + 1 行汇总
|
||||
{data?.emptyWarehouseCount > 0 ? `；其中 ${data.emptyWarehouseCount} 个仓在业务库无有效库存或销量` : ''}。
|
||||
</Text>
|
||||
|
||||
<Modal
|
||||
title="计算口径说明"
|
||||
open={helpOpen}
|
||||
onCancel={() => setHelpOpen(false)}
|
||||
footer={null}
|
||||
width={720}
|
||||
>
|
||||
<div className="stock-sales-help">
|
||||
{STOCK_SALES_DESCRIPTION.map((line, i) => (
|
||||
<p key={i} className={line.startsWith(' ') ? 'is-indent' : ''}>{line}</p>
|
||||
))}
|
||||
</div>
|
||||
</Modal>
|
||||
</SycmPage>
|
||||
);
|
||||
};
|
||||
|
||||
export default StockSalesAnalysis;
|
||||
@ -1,90 +0,0 @@
|
||||
.stock-sales-page {
|
||||
padding: 16px 20px 24px;
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 12px;
|
||||
}
|
||||
|
||||
.stock-sales-header {
|
||||
display: flex;
|
||||
flex-wrap: wrap;
|
||||
align-items: center;
|
||||
justify-content: space-between;
|
||||
gap: 12px;
|
||||
}
|
||||
|
||||
.stock-sales-header__title {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: 4px;
|
||||
}
|
||||
|
||||
.stock-sales-header__help {
|
||||
font-size: 13px;
|
||||
}
|
||||
|
||||
.stock-sales-header__meta {
|
||||
display: flex;
|
||||
flex-wrap: wrap;
|
||||
gap: 16px;
|
||||
font-size: 13px;
|
||||
color: rgba(0, 0, 0, 0.55);
|
||||
}
|
||||
|
||||
.stock-sales-th-tip {
|
||||
border-bottom: 1px dashed rgba(0, 0, 0, 0.35);
|
||||
cursor: help;
|
||||
white-space: nowrap;
|
||||
}
|
||||
|
||||
.stock-sales-table .ant-table-thead > tr > th {
|
||||
white-space: nowrap;
|
||||
font-size: 12px;
|
||||
padding: 6px 8px;
|
||||
}
|
||||
|
||||
.stock-sales-table .ant-table-tbody > tr > td {
|
||||
padding: 5px 8px;
|
||||
font-size: 13px;
|
||||
vertical-align: middle;
|
||||
}
|
||||
|
||||
.stock-sales-warehouse {
|
||||
white-space: nowrap;
|
||||
}
|
||||
|
||||
.stock-sales-grade {
|
||||
white-space: nowrap;
|
||||
}
|
||||
|
||||
.stock-sales-grade.is-total {
|
||||
font-weight: 600;
|
||||
}
|
||||
|
||||
/* 每个仓库的汇总行 */
|
||||
.stock-sales-table .stock-sales-row--subtotal > td {
|
||||
background: rgba(0, 0, 0, 0.03);
|
||||
font-weight: 600;
|
||||
}
|
||||
|
||||
/* 全仓合计行 */
|
||||
.stock-sales-table .stock-sales-row--grand > td {
|
||||
background: rgba(22, 119, 255, 0.06);
|
||||
font-weight: 600;
|
||||
}
|
||||
|
||||
.stock-sales-footer {
|
||||
font-size: 12px;
|
||||
}
|
||||
|
||||
.stock-sales-help p {
|
||||
margin: 0 0 6px;
|
||||
line-height: 1.7;
|
||||
font-size: 13px;
|
||||
white-space: pre-wrap;
|
||||
}
|
||||
|
||||
.stock-sales-help p.is-indent {
|
||||
padding-left: 16px;
|
||||
color: rgba(0, 0, 0, 0.65);
|
||||
}
|
||||
@ -1,546 +0,0 @@
|
||||
import React, { useCallback, useEffect, useMemo, useState } from 'react';
|
||||
import {
|
||||
Alert, Button, Card, Empty, Modal, Space, Spin, Statistic, Table, Tag, Tooltip, Typography,
|
||||
} from 'antd';
|
||||
import { ReloadOutlined } from '@ant-design/icons';
|
||||
import { SycmPage } from '../../components/Common';
|
||||
import { getWarehouseShipTimeliness } from '../../api/warehouseShipTimeliness';
|
||||
import './style.css';
|
||||
|
||||
const { Title, Text } = Typography;
|
||||
|
||||
// 核验点只有 13:00 / 18:00 两个，10 分钟刷新一次足够。
|
||||
// 接口要扫两张订单表 + 出库表（rpt 下全是视图），冷启动 40~60 秒，别跟着其它页面的轮询节奏跑。
|
||||
const AUTO_REFRESH_MS = 10 * 60 * 1000;
|
||||
|
||||
const number = (value, digits = 0) => (
|
||||
value === null || value === undefined || value === ''
|
||||
? '0'
|
||||
: Number(value).toLocaleString('zh-CN', {
|
||||
minimumFractionDigits: digits,
|
||||
maximumFractionDigits: digits,
|
||||
})
|
||||
);
|
||||
|
||||
// 超时时长（分钟）→「3 小时 20 分」/「12 天 4 小时」。
|
||||
// ⚠️ 口径放开后（含历史未发单）会出现跨天的超时，必须给「天」，否则显示成「8640 小时」。
|
||||
const formatOverdue = (minutes) => {
|
||||
const m = Number(minutes);
|
||||
if (!Number.isFinite(m) || m <= 0) return '—';
|
||||
if (m < 60) return `${m} 分钟`;
|
||||
const h = Math.floor(m / 60);
|
||||
const rest = m % 60;
|
||||
if (h < 24) return rest ? `${h} 小时 ${rest} 分` : `${h} 小时`;
|
||||
const d = Math.floor(h / 24);
|
||||
const hr = h % 24;
|
||||
return hr ? `${d} 天 ${hr} 小时` : `${d} 天`;
|
||||
};
|
||||
|
||||
/**
|
||||
* 「不计考核」清单的列（待审核 / 订单异常）。
|
||||
* 业务反馈（2026-10-20）：贴进来的一批单号在聚水潭查不到，实测真实状态是
|
||||
* 「已取消（发货前售后）」或「异常」—— 这类单不该算仓库超时。
|
||||
* 这里把它们单列出来，回答「为什么这些单没进超时列表」。
|
||||
*/
|
||||
const HELD_COLUMNS = [
|
||||
{ title: '内部单号', dataIndex: 'oId', width: 100 },
|
||||
{ title: '线上订单号', dataIndex: 'soId', width: 170, ellipsis: true },
|
||||
{ title: '店铺', dataIndex: 'shopName', width: 170, ellipsis: true },
|
||||
{ title: '发货仓', dataIndex: 'warehouseName', width: 160, ellipsis: true },
|
||||
{
|
||||
title: '挂起原因',
|
||||
dataIndex: 'holdReason',
|
||||
width: 110,
|
||||
render: (v) => (
|
||||
<Tag bordered={false} color={v === '订单异常' ? 'red' : 'default'}>{v || '—'}</Tag>
|
||||
),
|
||||
},
|
||||
{
|
||||
title: '发货时间',
|
||||
dataIndex: 'sendTime',
|
||||
width: 178,
|
||||
ellipsis: true,
|
||||
render: (v, row) => {
|
||||
if (v) return v;
|
||||
const no = row?.logisticId;
|
||||
if (no) {
|
||||
return (
|
||||
<Tooltip title={`已打单：${row.logisticCompany || ''} ${no}（${row.logisticStatus || '未揽收'}）`}>
|
||||
<Tag bordered={false} color="blue">已打单 · {row.logisticStatus || '未揽收'}</Tag>
|
||||
</Tooltip>
|
||||
);
|
||||
}
|
||||
return <Tag bordered={false} color="default">未发货</Tag>;
|
||||
},
|
||||
},
|
||||
{
|
||||
title: '审核时间',
|
||||
dataIndex: 'auditTime',
|
||||
width: 152,
|
||||
ellipsis: true,
|
||||
render: (v) => (v || <span className="wst-detail__fallback">未审核</span>),
|
||||
},
|
||||
{ title: '付款时间', dataIndex: 'payTime', width: 152, ellipsis: true, render: (v) => v || '—' },
|
||||
{ title: '已挂起', dataIndex: 'heldDays', width: 88, render: (v) => (v > 0 ? `${v} 天` : '—') },
|
||||
];
|
||||
|
||||
const DETAIL_COLUMNS = [
|
||||
// 内部单号 = 聚水潭 o_id（系统内部编号，仓管在系统里按它查单）
|
||||
{ title: '内部单号', dataIndex: 'oId', width: 110 },
|
||||
// 线上订单号 = 平台 so_id（京东/抖音/天猫等平台单号，客服按它对接客户）
|
||||
{
|
||||
title: '线上订单号',
|
||||
dataIndex: 'soId',
|
||||
width: 178,
|
||||
ellipsis: true,
|
||||
render: (v) => (v ? <span className="wst-detail__soid">{v}</span> : '—'),
|
||||
},
|
||||
{
|
||||
title: '店铺',
|
||||
dataIndex: 'shopName',
|
||||
width: 180,
|
||||
ellipsis: true,
|
||||
render: (v) => (v || '—'),
|
||||
},
|
||||
{
|
||||
title: '发货仓',
|
||||
dataIndex: 'warehouseName',
|
||||
width: 170,
|
||||
ellipsis: true,
|
||||
render: (v) => (v || '—'),
|
||||
},
|
||||
{
|
||||
// 发货时间 = 聚水潭回传的发货时间（业务 2026-10-20：明细里不要创建时间，要发货时间）
|
||||
title: (
|
||||
<Tooltip title="聚水潭回传的发货时间（send_time）。为空但有运单号的，说明仓库已打单、还没揽收/回传发货时间，会显示成「已打单」">
|
||||
<span>发货时间</span>
|
||||
</Tooltip>
|
||||
),
|
||||
dataIndex: 'sendTime',
|
||||
width: 178,
|
||||
ellipsis: true,
|
||||
render: (v, row) => {
|
||||
if (v) return v;
|
||||
const no = row?.logisticId;
|
||||
if (no) {
|
||||
return (
|
||||
<Tooltip title={`已打单：${row.logisticCompany || ''} ${no}（${row.logisticStatus || '未揽收'}）。聚水潭还没回传发货时间，所以还没从超时列表里消失`}>
|
||||
<Tag bordered={false} color="blue">已打单 · {row.logisticStatus || '未揽收'}</Tag>
|
||||
</Tooltip>
|
||||
);
|
||||
}
|
||||
return <Tag bordered={false} color="default">未发货</Tag>;
|
||||
},
|
||||
},
|
||||
{
|
||||
// 审核时间 = **考核基准**，取聚水潭「审核时间」列（最后一次审核，重审会刷新）
|
||||
title: (
|
||||
<Tooltip title="= 聚水潭订单列表「审核时间」那一列（最后一次审核，重新审核会刷新）。今天 7:00 前审核的 13:00 核验；截止 16:00 前审核的（含今天之前未发的历史单）18:00 核验，已等时长也从它算">
|
||||
<span>审核时间</span>
|
||||
</Tooltip>
|
||||
),
|
||||
dataIndex: 'auditTime',
|
||||
width: 152,
|
||||
ellipsis: true,
|
||||
render: (v, row) => (v
|
||||
? v
|
||||
: (
|
||||
<Tooltip title="没取到审核时间，已回退创建/付款时间参与分轮与计时">
|
||||
<span className="wst-detail__fallback">{row?.benchmarkTime || '—'} *</span>
|
||||
</Tooltip>
|
||||
)),
|
||||
},
|
||||
// 付款时间 = 客户付款那一刻（并列展示，方便对账）
|
||||
{ title: '付款时间', dataIndex: 'payTime', width: 152, ellipsis: true, render: (v) => v || '—' },
|
||||
{
|
||||
// 发货状态：聚水潭实时状态（发货中 = 已审核未发货，即考核对象）
|
||||
title: (
|
||||
<Tooltip title="聚水潭订单实时状态。发货中 = 已审核、仓库还没发货">
|
||||
<span>发货状态</span>
|
||||
</Tooltip>
|
||||
),
|
||||
dataIndex: 'state',
|
||||
width: 104,
|
||||
render: (v) => (
|
||||
<Tag bordered={false} color={v === '发货中' ? 'orange' : 'default'}>{v || '—'}</Tag>
|
||||
),
|
||||
},
|
||||
{
|
||||
title: '物流状态',
|
||||
dataIndex: 'logisticStatus',
|
||||
width: 100,
|
||||
render: (v) => (v ? <Tag bordered={false}>{v}</Tag> : '—'),
|
||||
},
|
||||
{
|
||||
title: (
|
||||
<Tooltip title="从审核时间到本轮核验时刻（13:00 / 18:00）等了多久">
|
||||
<span>已等时长</span>
|
||||
</Tooltip>
|
||||
),
|
||||
dataIndex: 'overdueMinutes',
|
||||
width: 112,
|
||||
render: (v) => <span className="wst-detail__overdue">{formatOverdue(v)}</span>,
|
||||
},
|
||||
];
|
||||
|
||||
/**
|
||||
* 仓储中心 24 小时发货时效（独立页面）
|
||||
* ────────────────────────────────────────────────────────────────
|
||||
* 业务口径（yanhui 2026-10-20）：
|
||||
* · 11 个主仓，子仓并入主仓一起算；
|
||||
* · 今天 07:00 前**审核**的订单 13:00 核验，截止今天 16:00 前审核的单 18:00 核验
|
||||
* （含 7 点前未发出的、含今天之前审核至今未发的历史单；山东两仓 15:00、河南洛宁 13:00）；
|
||||
* 今天之前审核仍未发的（历史未发）两个轮次都算；
|
||||
* **到核验时刻未发即超时**，没有「满 24 小时」门槛（业务纠偏点）；
|
||||
* 轮次归属和「已等时长」都按**审核时间**算（聚水潭「审核时间」列，最后一次审核）；
|
||||
* · **13:00 之前不核验**，直接显示「未到核验时间」，不拿昨天的结果冒充今天；
|
||||
* · 已出库 / 待出库以**聚水潭发货时间**为准（有 send_time = 已发）；
|
||||
* · 只显示超时未出库（发完的仓显示「—」），点仓库可筛右侧明细。
|
||||
*
|
||||
* 数据来自 /api/warehouse-ship-timeliness/list（service 层见
|
||||
* backend/src/services/warehouseShipTimelinessService.js）。
|
||||
*/
|
||||
function WarehouseShipTimeliness() {
|
||||
const [data, setData] = useState(null);
|
||||
const [loading, setLoading] = useState(false);
|
||||
const [error, setError] = useState('');
|
||||
// 选中的主仓：为空时右侧展示全部仓的超时明细
|
||||
const [activeCenter, setActiveCenter] = useState('');
|
||||
// 「业务挂起（疑问单）」明细弹窗
|
||||
const [heldOpen, setHeldOpen] = useState(false);
|
||||
|
||||
// force=true 时带 force=1 让后端绕过 5 分钟结果缓存重查库；
|
||||
// 定时轮询走缓存（这张视图单次要几十秒，每轮都重查会把库压死）
|
||||
const load = useCallback(async (force = false) => {
|
||||
setLoading(true);
|
||||
setError('');
|
||||
try {
|
||||
const result = await getWarehouseShipTimeliness({ limit: 1000, force: force ? 1 : 0 });
|
||||
if (!result || result.success === false) {
|
||||
setError(result?.error || '加载发货时效失败');
|
||||
return;
|
||||
}
|
||||
setData(result.data || null);
|
||||
} catch (loadError) {
|
||||
setError(loadError?.response?.data?.error || loadError?.message || '加载发货时效失败');
|
||||
} finally {
|
||||
setLoading(false);
|
||||
}
|
||||
}, []);
|
||||
|
||||
useEffect(() => {
|
||||
load();
|
||||
const timer = window.setInterval(() => load(), AUTO_REFRESH_MS);
|
||||
return () => window.clearInterval(timer);
|
||||
}, [load]);
|
||||
|
||||
const centers = useMemo(() => (Array.isArray(data?.centers) ? data.centers : []), [data]);
|
||||
const orders = useMemo(() => (Array.isArray(data?.orders) ? data.orders : []), [data]);
|
||||
// 业务挂起（疑问单）—— 与 orders 互斥，两者相加才是待出库池
|
||||
const heldOrders = useMemo(
|
||||
() => (Array.isArray(data?.heldOrders) ? data.heldOrders : []),
|
||||
[data]
|
||||
);
|
||||
const summary = data?.summary || {};
|
||||
const round = data?.round || null;
|
||||
const freshness = data?.freshness || null;
|
||||
// 13:00 之前后端返回 round=null + notStarted=true：此时**不展示任何超时数字**
|
||||
const notStarted = Boolean(data?.notStarted);
|
||||
const hasRound = Boolean(round);
|
||||
const cutoffText = String(round?.windowEnd || '').slice(11, 16);
|
||||
const windowEndText = String(data?.window?.end || '').slice(11, 16);
|
||||
// 仓级例外窗口：18:00 轮里 山东两仓 15:00、河南洛宁 13:00（业务 2026-10-20 指定）
|
||||
const windowOverrides = Array.isArray(data?.window?.overrides) ? data.window.overrides : [];
|
||||
const overrideText = windowOverrides
|
||||
.map((o) => `${o.name} ${String(o.hour).padStart(2, '0')}:00`)
|
||||
.join('、');
|
||||
// 未到核验时间时的提示文案，全部由后端给，前端不写死时刻
|
||||
const nextRoundText = String(data?.nextRoundAt || '').slice(11, 16) || '13:00';
|
||||
const nextWindowEndText = String(data?.nextWindowEnd || '').slice(11, 16) || '07:00';
|
||||
|
||||
const activeCenterName = useMemo(() => {
|
||||
if (!activeCenter) return '';
|
||||
const hit = centers.find((c) => c.key === activeCenter);
|
||||
return hit ? hit.name : activeCenter;
|
||||
}, [activeCenter, centers]);
|
||||
|
||||
const detailOrders = useMemo(() => (
|
||||
activeCenter ? orders.filter((o) => o.centerKey === activeCenter) : orders
|
||||
), [activeCenter, orders]);
|
||||
|
||||
return (
|
||||
<SycmPage className="wst-page">
|
||||
<header className="wst-header">
|
||||
<Title level={3}>仓储中心 24 小时发货时效</Title>
|
||||
<Text type="secondary">
|
||||
按聚水潭订单实时状态核验 11 个主仓是否在承诺时效内完成发货，只列超时未发货的单量。
|
||||
</Text>
|
||||
<Text type="secondary" className="wst-note">
|
||||
每天 <b>13:00</b> 核验「<b>今天 07:00 前审核</b>」、<b>18:00</b> 核验「<b>截止 16:00 前审核</b>」、
|
||||
到核验时刻仍未发货的订单；两个轮次都<b>包含今天之前审核、至今未发的历史未发单</b>
|
||||
（18:00 轮也会带上 7 点前审核、13:00 还没发出的那批）—— 滚动待发池，不按自然日切。
|
||||
13:00 之前不核验，显示「未到核验时间」。
|
||||
<b>到点还没发就算超时 —— 不设「满 24 小时」门槛</b>（早上 7 点前那份单，13:00 还没走就是超时）。
|
||||
<b>仓级例外</b>：18:00 轮里 <b>山东青岗集仓 / 山东品牌仓</b> 只看 <b>15:00 前审核</b>的单、
|
||||
<b>河南洛宁仓</b> 只看 <b>13:00 前审核</b>的单（核验时刻仍是 18:00）。
|
||||
<b>轮次与「已等时长」都按审核时间算</b>（= 聚水潭「审核时间」列，最后一次审核）；
|
||||
明细并列「审核时间 / 发货时间」，方便直接和聚水潭对账。
|
||||
<b>已发 / 未发以聚水潭发货时间为准</b>：有发货时间就是已发，不再用订单表的发货字段反推
|
||||
—— 该字段经常不回写，会把早就发货的单误判成超时。
|
||||
<b>已打单但还没揽收的</b>（聚水潭已生成运单号、发货时间还空着）会标成「已打单 · 未揽收」，
|
||||
鼠标悬停能看到运单号 —— 这类单还留在列表里，等聚水潭回传发货时间才消失。
|
||||
<b>自提 / 中铁 / 壹米滴答 三个快递不考核</b>（客户自提或专线大件，仓库控制不了运输），
|
||||
已按物流公司自动剔除。
|
||||
<b>「已支付待审核」和「异常」的单不计考核</b>（仓库还没接到或订单本身有问题），单独归入「不计考核」并给出明细；
|
||||
<b>作废单（已取消，含发货前售后）不考核也不展示</b> —— 客户付款后取消的单仓库本就不该发。
|
||||
</Text>
|
||||
</header>
|
||||
|
||||
<Card className="wst-status" bordered={false}>
|
||||
<div className="wst-status__row">
|
||||
<div className="wst-status__round">
|
||||
{hasRound ? (
|
||||
<>
|
||||
<span className="wst-status__badge">{round.label}</span>
|
||||
<span className="wst-status__label">
|
||||
核验今天 {cutoffText} 前审核的订单
|
||||
</span>
|
||||
<span className="wst-status__window">
|
||||
含历史未发 · 到点未发即超时
|
||||
{overrideText ? `（${overrideText} 为仓级例外）` : ''}
|
||||
</span>
|
||||
</>
|
||||
) : (
|
||||
<>
|
||||
<span className="wst-status__badge wst-status__badge--idle">未到核验时间</span>
|
||||
<span className="wst-status__label">
|
||||
{nextRoundText} 开始首轮核验
|
||||
（核验今天 {nextWindowEndText} 前审核的订单）
|
||||
</span>
|
||||
</>
|
||||
)}
|
||||
</div>
|
||||
<Space size={8}>
|
||||
{data?.generatedAt ? (
|
||||
<Text type="secondary" className="wst-status__time">
|
||||
数据更新于 {String(data.generatedAt).slice(11, 19)}
|
||||
{data?.cached ? `（缓存 ${data.cacheAgeSec || 0}s，点刷新重查）` : ''}
|
||||
</Text>
|
||||
) : null}
|
||||
<Button icon={<ReloadOutlined />} onClick={() => load(true)} loading={loading}>刷新</Button>
|
||||
</Space>
|
||||
</div>
|
||||
</Card>
|
||||
|
||||
{error ? (
|
||||
<Alert
|
||||
type="error"
|
||||
showIcon
|
||||
className="wst-alert"
|
||||
message={error}
|
||||
action={<Button size="small" onClick={load}>重试</Button>}
|
||||
/>
|
||||
) : null}
|
||||
|
||||
{freshness && (freshness.stale || freshness.coversDeadline === false) ? (
|
||||
<Alert
|
||||
// 快照没覆盖到核验时刻 → 数字必然偏大，用红色；只是滞后用黄色
|
||||
type={freshness.coversDeadline === false ? 'error' : 'warning'}
|
||||
showIcon
|
||||
className="wst-alert"
|
||||
message={freshness.coversDeadline === false ? '数据未覆盖本轮核验时刻，超时单量偏大' : '发货数据可能滞后'}
|
||||
description={freshness.hint}
|
||||
/>
|
||||
) : null}
|
||||
|
||||
<div className="wst-stats">
|
||||
<Card bordered={false} className="wst-stat">
|
||||
<Statistic
|
||||
title={(
|
||||
<Tooltip title="到 13:00 / 18:00 核验时刻仍未发货的订单（按审核时间分轮），不设满 24 小时门槛">
|
||||
<span>超时未发货</span>
|
||||
</Tooltip>
|
||||
)}
|
||||
value={notStarted ? 0 : (summary.overdueUnshipped ?? 0)}
|
||||
suffix="单"
|
||||
formatter={(v) => (notStarted ? '—' : number(v))}
|
||||
valueStyle={{ color: (summary.overdueUnshipped || 0) > 0 ? '#cf1322' : undefined }}
|
||||
/>
|
||||
</Card>
|
||||
<Card
|
||||
bordered={false}
|
||||
className="wst-stat wst-stat--held"
|
||||
onClick={() => setHeldOpen(true)}
|
||||
>
|
||||
<Statistic
|
||||
title={(
|
||||
<Tooltip title="已支付待审核（还没审单，仓库没接到）和订单异常的单。这类单不进仓库考核，点开看明细。">
|
||||
<span>不计考核 <span className="wst-stat__more">明细</span></span>
|
||||
</Tooltip>
|
||||
)}
|
||||
value={notStarted ? 0 : (summary.heldCount ?? 0)}
|
||||
suffix="单"
|
||||
formatter={(v) => (notStarted ? '—' : number(v))}
|
||||
valueStyle={{ color: (summary.heldCount || 0) > 0 ? '#8c8c8c' : undefined }}
|
||||
/>
|
||||
</Card>
|
||||
<Card bordered={false} className="wst-stat">
|
||||
<Statistic
|
||||
title="涉及仓库"
|
||||
value={notStarted ? 0 : (summary.overdueCenterCount ?? 0)}
|
||||
suffix="个"
|
||||
formatter={(v) => (notStarted ? '—' : number(v))}
|
||||
/>
|
||||
</Card>
|
||||
<Card bordered={false} className="wst-stat">
|
||||
<Statistic
|
||||
title="最久未发货"
|
||||
value={notStarted ? 0 : (summary.oldestDays ?? 0)}
|
||||
suffix="天"
|
||||
formatter={(v) => (notStarted ? '—' : number(v))}
|
||||
valueStyle={{ color: (summary.oldestDays || 0) >= 7 ? '#d46b08' : undefined }}
|
||||
/>
|
||||
</Card>
|
||||
</div>
|
||||
|
||||
<div className="wst-body">
|
||||
<Card
|
||||
bordered={false}
|
||||
className="wst-centers"
|
||||
title="仓储中心"
|
||||
extra={<Text type="secondary" className="wst-centers__hint">点仓库看明细</Text>}
|
||||
>
|
||||
<Spin spinning={loading && !data} size="small">
|
||||
<ul className="wst-centers__list">
|
||||
{centers.map((c) => {
|
||||
const isActive = activeCenter === c.key;
|
||||
const disabled = c.placeholder || notStarted;
|
||||
return (
|
||||
<li key={c.key}>
|
||||
<Tooltip
|
||||
placement="right"
|
||||
title={c.placeholder
|
||||
? '系统仓库表中暂无同名仓，待上游建仓后自动接入'
|
||||
: notStarted
|
||||
? `今日 ${nextRoundText} 首轮核验开始后才展示超时数据`
|
||||
: `${c.name}：本轮核验 ${String(c.windowEnd || '').slice(11, 16) || windowEndText} 前审核的单，`
|
||||
+ `超时未发货 ${c.overdueUnshipped} 单`
|
||||
+ `${c.oldestDays > 0 ? `（最久已等 ${c.oldestDays} 天）` : ''}`
|
||||
+ `${c.heldCount > 0 ? `\n另有不计考核（待审核/异常）${c.heldCount} 单` : ''}`
|
||||
+ (c.warehouseCount > 1 ? `\n含子仓 ${c.warehouseCount} 个` : '')}
|
||||
>
|
||||
<button
|
||||
type="button"
|
||||
className={[
|
||||
'wst-center',
|
||||
isActive ? 'is-active' : '',
|
||||
!c.overdueUnshipped ? 'is-empty' : '',
|
||||
disabled ? 'is-disabled' : '',
|
||||
].filter(Boolean).join(' ')}
|
||||
onClick={() => {
|
||||
if (disabled) return;
|
||||
setActiveCenter(isActive ? '' : c.key);
|
||||
}}
|
||||
>
|
||||
<span className="wst-center__name">{c.name}</span>
|
||||
{c.placeholder ? (
|
||||
<span className="wst-center__badge wst-center__badge--none">未接入</span>
|
||||
) : (
|
||||
<span className={`wst-center__badge${c.overdueUnshipped > 0 ? ' is-warn' : ''}`}>
|
||||
{notStarted ? '—' : (c.overdueUnshipped > 0 ? c.overdueUnshipped : '—')}
|
||||
</span>
|
||||
)}
|
||||
</button>
|
||||
</Tooltip>
|
||||
</li>
|
||||
);
|
||||
})}
|
||||
</ul>
|
||||
</Spin>
|
||||
</Card>
|
||||
|
||||
<Card
|
||||
bordered={false}
|
||||
className="wst-detail"
|
||||
title={(
|
||||
<span>
|
||||
超时未发货订单
|
||||
<span className="wst-detail__scope">
|
||||
{activeCenterName || '全部仓库'} · {detailOrders.length} 单
|
||||
{data?.truncated && detailOrders.length >= (data?.detailLimit || 0)
|
||||
? `（已截断，仅显示前 ${data.detailLimit} 条）`
|
||||
: ''}
|
||||
</span>
|
||||
</span>
|
||||
)}
|
||||
extra={activeCenter ? (
|
||||
<button type="button" className="wst-detail__clear" onClick={() => setActiveCenter('')}>查看全部</button>
|
||||
) : null}
|
||||
>
|
||||
<Spin spinning={loading && !data}>
|
||||
{notStarted ? (
|
||||
<Empty
|
||||
image={Empty.PRESENTED_IMAGE_SIMPLE}
|
||||
description={`未到核验时间，今日 ${nextRoundText} 开始首轮核验`}
|
||||
/>
|
||||
) : detailOrders.length ? (
|
||||
<Table
|
||||
rowKey={(r) => `${r.source}-${r.oId}`}
|
||||
size="small"
|
||||
pagination={{ pageSize: 20, size: 'small', showSizeChanger: false, showTotal: (t) => `共 ${t} 单` }}
|
||||
dataSource={detailOrders}
|
||||
columns={DETAIL_COLUMNS}
|
||||
scroll={{ x: 1642 }}
|
||||
/>
|
||||
) : (
|
||||
<Empty image={Empty.PRESENTED_IMAGE_SIMPLE} description="本轮没有超时未发货的订单" />
|
||||
)}
|
||||
</Spin>
|
||||
</Card>
|
||||
</div>
|
||||
|
||||
<Modal
|
||||
title={`不计考核（待审核 / 异常）· ${heldOrders.length} 单`}
|
||||
open={heldOpen}
|
||||
onCancel={() => setHeldOpen(false)}
|
||||
footer={null}
|
||||
width={1080}
|
||||
destroyOnClose
|
||||
>
|
||||
<Alert
|
||||
type="info"
|
||||
showIcon
|
||||
className="wst-alert"
|
||||
message="「已支付待审核」= 还没审单，仓库根本没接到；「订单异常」= 聚水潭标记异常（缺货/地址/风控等）。两类都不该算仓库超时，故单列于此。"
|
||||
/>
|
||||
{heldOrders.length ? (
|
||||
<Table
|
||||
rowKey={(r) => `${r.oId}`}
|
||||
size="small"
|
||||
pagination={{ pageSize: 10, size: 'small', showSizeChanger: false, showTotal: (t) => `共 ${t} 单` }}
|
||||
dataSource={heldOrders}
|
||||
columns={HELD_COLUMNS}
|
||||
scroll={{ x: 1280 }}
|
||||
/>
|
||||
) : (
|
||||
<Empty image={Empty.PRESENTED_IMAGE_SIMPLE} description="本轮没有待审核 / 异常的单" />
|
||||
)}
|
||||
</Modal>
|
||||
|
||||
<Text type="secondary" className="wst-foot">
|
||||
说明：<b>今天 7:00 前审核</b>的订单 13:00 核验；<b>截止 16:00 前审核</b>的单 18:00 核验
|
||||
（含 7 点前审核、13:00 还没发出的，也含今天之前审核至今未发的历史单）。
|
||||
<b>到点仍未发货即超时</b>（不设「满 24 小时」门槛）；
|
||||
轮次与「已等时长」都按审核时间（聚水潭显示值）算。
|
||||
发货 = 聚水潭回传的发货时间。
|
||||
<b>作废单不考核</b>（被合并 / 拆单父单 / 已取消，或订单表已有发货时间）
|
||||
{summary.voidCount > 0 ? ` —— 本轮已自动剔除 ${summary.voidCount} 单` : ''}；
|
||||
<b>自提 / 中铁 / 壹米滴答不考核</b>
|
||||
{summary.carrierSkipped > 0 ? ` —— 本轮已剔除 ${summary.carrierSkipped} 单` : ''}；
|
||||
已支付待审核、订单异常的单归入「不计考核」，避免冤枉仓库。
|
||||
</Text>
|
||||
</SycmPage>
|
||||
);
|
||||
}
|
||||
|
||||
export default WarehouseShipTimeliness;
|
||||
@ -1,255 +0,0 @@
|
||||
.wst-page {
|
||||
padding: 16px 20px 24px;
|
||||
}
|
||||
|
||||
.wst-header {
|
||||
margin-bottom: 14px;
|
||||
}
|
||||
|
||||
.wst-header .ant-typography {
|
||||
margin-bottom: 4px;
|
||||
}
|
||||
|
||||
.wst-note {
|
||||
display: block;
|
||||
max-width: 1180px;
|
||||
margin-top: 8px;
|
||||
padding: 10px 14px;
|
||||
/* 页面顶部是深色渐变，直接放浅色小字会看不清，给口径说明一块浅底 */
|
||||
background: var(--sycm-bg-container);
|
||||
border: 1px solid var(--sycm-border-color);
|
||||
border-radius: 8px;
|
||||
font-size: 12px;
|
||||
line-height: 1.75;
|
||||
}
|
||||
|
||||
/* ============ 轮次状态条 ============ */
|
||||
.wst-status {
|
||||
margin-bottom: 12px;
|
||||
}
|
||||
|
||||
.wst-status__row {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: space-between;
|
||||
gap: 12px;
|
||||
flex-wrap: wrap;
|
||||
}
|
||||
|
||||
.wst-status__round {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: 10px;
|
||||
flex-wrap: wrap;
|
||||
}
|
||||
|
||||
.wst-status__badge {
|
||||
padding: 1px 8px;
|
||||
border-radius: 4px;
|
||||
background: rgba(22, 119, 255, 0.12);
|
||||
color: #0958d9;
|
||||
font-size: 12px;
|
||||
font-weight: 600;
|
||||
line-height: 20px;
|
||||
}
|
||||
|
||||
.wst-status__badge--idle {
|
||||
background: rgba(136, 135, 128, 0.14);
|
||||
color: var(--sycm-text-tertiary);
|
||||
}
|
||||
|
||||
.wst-status__label {
|
||||
font-size: 13px;
|
||||
color: var(--sycm-text-primary);
|
||||
}
|
||||
|
||||
.wst-status__window,
|
||||
.wst-status__time {
|
||||
font-size: 12px;
|
||||
color: var(--sycm-text-tertiary);
|
||||
}
|
||||
|
||||
.wst-alert {
|
||||
margin-bottom: 12px;
|
||||
}
|
||||
|
||||
/* ============ 统计卡 ============ */
|
||||
/* 5 张卡（超时未出库 / 业务挂起 / 涉及仓库 / 最久未出库 / 合计金额）
|
||||
用 grid 而不是 Row/Col：24 栅格除不尽 5，Row/Col 会把第 5 张挤到下一行。 */
|
||||
.wst-stats {
|
||||
display: grid;
|
||||
grid-template-columns: repeat(4, minmax(0, 1fr));
|
||||
gap: 12px;
|
||||
margin-bottom: 12px;
|
||||
}
|
||||
|
||||
@media (max-width: 1500px) {
|
||||
.wst-stats { grid-template-columns: repeat(2, minmax(0, 1fr)); }
|
||||
}
|
||||
|
||||
@media (max-width: 900px) {
|
||||
.wst-stats { grid-template-columns: repeat(2, minmax(0, 1fr)); }
|
||||
}
|
||||
|
||||
.wst-stat {
|
||||
height: 100%;
|
||||
}
|
||||
|
||||
/* 「业务挂起」卡可点开明细 */
|
||||
.wst-stat--held {
|
||||
cursor: pointer;
|
||||
transition: box-shadow 0.2s;
|
||||
}
|
||||
|
||||
.wst-stat--held:hover {
|
||||
box-shadow: 0 2px 10px rgba(0, 0, 0, 0.1);
|
||||
}
|
||||
|
||||
.wst-stat__more {
|
||||
font-size: 12px;
|
||||
font-weight: 400;
|
||||
color: #1677ff;
|
||||
}
|
||||
|
||||
/* ============ 主从两栏 ============ */
|
||||
.wst-body {
|
||||
display: flex;
|
||||
align-items: flex-start;
|
||||
gap: 14px;
|
||||
}
|
||||
|
||||
.wst-centers {
|
||||
flex: none;
|
||||
width: 264px;
|
||||
}
|
||||
|
||||
.wst-centers__hint {
|
||||
font-size: 11px;
|
||||
}
|
||||
|
||||
.wst-centers__list {
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
list-style: none;
|
||||
}
|
||||
|
||||
.wst-center {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: space-between;
|
||||
gap: 8px;
|
||||
width: 100%;
|
||||
padding: 6px 8px;
|
||||
margin-bottom: 2px;
|
||||
border: 1px solid transparent;
|
||||
border-radius: 6px;
|
||||
background: transparent;
|
||||
font-size: 13px;
|
||||
text-align: left;
|
||||
color: var(--sycm-text-primary);
|
||||
cursor: pointer;
|
||||
transition: background 0.12s ease;
|
||||
}
|
||||
|
||||
.wst-center:hover {
|
||||
background: var(--sycm-bg-subtle);
|
||||
}
|
||||
|
||||
.wst-center.is-active {
|
||||
border-color: rgba(22, 119, 255, 0.45);
|
||||
background: rgba(22, 119, 255, 0.08);
|
||||
}
|
||||
|
||||
.wst-center.is-empty .wst-center__name {
|
||||
color: var(--sycm-text-tertiary);
|
||||
}
|
||||
|
||||
.wst-center.is-disabled {
|
||||
cursor: not-allowed;
|
||||
opacity: 0.6;
|
||||
}
|
||||
|
||||
.wst-center__name {
|
||||
overflow: hidden;
|
||||
white-space: nowrap;
|
||||
text-overflow: ellipsis;
|
||||
}
|
||||
|
||||
.wst-center__badge {
|
||||
flex: none;
|
||||
min-width: 24px;
|
||||
padding: 0 6px;
|
||||
border-radius: 9px;
|
||||
background: rgba(136, 135, 128, 0.12);
|
||||
font-size: 11px;
|
||||
font-weight: 600;
|
||||
line-height: 17px;
|
||||
text-align: center;
|
||||
color: var(--sycm-text-tertiary);
|
||||
font-variant-numeric: tabular-nums;
|
||||
}
|
||||
|
||||
.wst-center__badge.is-warn {
|
||||
background: rgba(255, 77, 79, 0.16);
|
||||
color: #cf1322;
|
||||
}
|
||||
|
||||
.wst-center__badge--none {
|
||||
font-weight: 400;
|
||||
}
|
||||
|
||||
.wst-detail {
|
||||
flex: 1 1 auto;
|
||||
min-width: 0;
|
||||
}
|
||||
|
||||
.wst-detail__scope {
|
||||
margin-left: 8px;
|
||||
font-size: 12px;
|
||||
font-weight: 400;
|
||||
color: var(--sycm-text-tertiary);
|
||||
}
|
||||
|
||||
.wst-detail__clear {
|
||||
padding: 0;
|
||||
border: none;
|
||||
background: transparent;
|
||||
font-size: 12px;
|
||||
color: #1677ff;
|
||||
cursor: pointer;
|
||||
}
|
||||
|
||||
.wst-detail__overdue {
|
||||
color: #cf1322;
|
||||
font-variant-numeric: tabular-nums;
|
||||
}
|
||||
|
||||
/* 创建时间没补到、回退成付款时间时的提示色（带 * 号，tooltip 有说明） */
|
||||
.wst-detail__fallback {
|
||||
color: var(--sycm-text-tertiary);
|
||||
font-style: italic;
|
||||
}
|
||||
|
||||
.wst-foot {
|
||||
display: block;
|
||||
margin-top: 12px;
|
||||
font-size: 12px;
|
||||
color: var(--sycm-text-tertiary);
|
||||
}
|
||||
|
||||
/* 窄屏：仓库列表改为两列网格，明细整行下移 */
|
||||
@media (max-width: 1200px) {
|
||||
.wst-body {
|
||||
flex-direction: column;
|
||||
}
|
||||
|
||||
.wst-centers {
|
||||
width: 100%;
|
||||
}
|
||||
|
||||
.wst-centers__list {
|
||||
display: grid;
|
||||
grid-template-columns: repeat(2, minmax(0, 1fr));
|
||||
gap: 2px 10px;
|
||||
}
|
||||
}
|
||||
@ -19,10 +19,7 @@ const OpsBIncentiveBoard = lazy(() => import('../pages/PlanningUpload/OpsBIncent
|
||||
const ProductMonitoring = lazy(() => import('../pages/ProductMonitoring'));
|
||||
const ModularStockMonitor = lazy(() => import('../pages/ModularStockMonitor'));
|
||||
const MkhBomData = lazy(() => import('../pages/MkhBomData'));
|
||||
const WarehouseShipTimeliness = lazy(() => import('../pages/WarehouseShipTimeliness'));
|
||||
const DailyInventory = lazy(() => import('../pages/DailyInventory'));
|
||||
const StockSalesAnalysis = lazy(() => import('../pages/StockSalesAnalysis'));
|
||||
const PickingBinSalesAnalysis = lazy(() => import('../pages/PickingBinSalesAnalysis'));
|
||||
const ReturnsInventoryMonitor = lazy(() => import('../pages/ReturnsInventoryWarning/Monitor'));
|
||||
|
||||
const lazyLoadingElement = <PageLoadingFallback />;
|
||||
@ -116,22 +113,10 @@ const router = createBrowserRouter([
|
||||
path: 'planning/operation/mkh-bom-data',
|
||||
element: renderLazyComponent(MkhBomData),
|
||||
},
|
||||
{
|
||||
path: 'planning/operation/warehouse-ship-timeliness',
|
||||
element: renderLazyComponent(WarehouseShipTimeliness),
|
||||
},
|
||||
{
|
||||
path: 'planning/operation/daily-inventory',
|
||||
element: renderLazyComponent(DailyInventory),
|
||||
},
|
||||
{
|
||||
path: 'planning/operation/stock-sales-analysis',
|
||||
element: renderLazyComponent(StockSalesAnalysis),
|
||||
},
|
||||
{
|
||||
path: 'planning/operation/picking-bin-sales-analysis',
|
||||
element: renderLazyComponent(PickingBinSalesAnalysis),
|
||||
},
|
||||
// 客退数据监控（5 张看板共用同一个页面，靠 warehouseKey 区分取哪个仓；
|
||||
// 单一「退货库存预警」视图，原 明细/超期/汇总/差异 四个页签已下线）
|
||||
{
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user