249 lines
14 KiB
JavaScript
249 lines
14 KiB
JavaScript
/* 关键前端逻辑单测（node 直跑）：错误翻译 / 结论分档 / 阶段命名 / 本期结论分组 */
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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 src = fs.readFileSync(path.join(__dirname, "..", "webui", "app.js"), "utf-8");
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function extractFn(name) {
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const m = src.match(new RegExp(`function ${name}\\([\\s\\S]*?\\n}`));
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if (!m) throw new Error(`未找到函数 ${name}`);
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return m[0];
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}
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function loadFn(name) {
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// 在独立函数作用域内定义并返回目标函数（规避 eval 严格模式作用域问题）
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return new Function(`${extractFn(name)}; return ${name};`)();
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}
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const friendlyErr = loadFn("friendlyErr");
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const matchAdvice = loadFn("matchAdvice");
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let pass = 0, fail = 0;
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function eq(actual, expected, label) {
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const ok = actual === expected;
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if (ok) pass++; else { fail++; console.error(`FAIL ${label}: 期望 ${JSON.stringify(expected)} 实际 ${JSON.stringify(actual)}`); }
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}
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function includes(hay, needle, label) {
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const ok = String(hay).includes(needle);
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if (ok) pass++; else { fail++; console.error(`FAIL ${label}: ${JSON.stringify(hay)} 不含 ${needle}`); }
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}
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/* friendlyErr：禁止出现 Failed to fetch / 内部文件名 / 接口路径 */
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eq(friendlyErr(new TypeError("Failed to fetch")), "暂时无法连接服务，请检查后端是否已启动", "fetch 失败翻译");
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eq(friendlyErr(new Error("NetworkError when attempting to fetch resource.")), "暂时无法连接服务，请检查后端是否已启动", "NetworkError 翻译");
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eq(friendlyErr(new Error("记录不存在")), "记录不存在", "服务端中文 detail 原样保留");
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eq(friendlyErr(new Error("HTTP 500")), "服务响应异常（500）", "HTTP 状态码中文化");
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eq(friendlyErr(new Error("batch_2019.jsonl#92 读取失败")), "操作失败，请稍后重试", "内部文件名不外显");
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eq(friendlyErr(new Error("")), "操作失败，请稍后重试", "空消息兜底");
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/* matchAdvice：三档结论 */
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includes(matchAdvice(85), "强烈推荐", ">=80 档");
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includes(matchAdvice(72), "补齐核心缺口", "60-80 档");
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includes(matchAdvice(40), "先系统学习", "<60 档");
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includes(matchAdvice(80), "强烈推荐", "边界 80");
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includes(matchAdvice(60), "补齐核心缺口", "边界 60");
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includes(matchAdvice(59.9), "先系统学习", "边界 59.9");
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/* 阶段语义化命名（与 renderPath 内逻辑一致） */
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const STAGE_NAMES = ["基础补齐", "岗位核心", "项目验证"];
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const stageName = (i) => STAGE_NAMES[i] || "综合提升";
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eq(stageName(0), "基础补齐", "阶段1命名");
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eq(stageName(1), "岗位核心", "阶段2命名");
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eq(stageName(2), "项目验证", "阶段3命名");
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eq(stageName(3), "综合提升", "阶段4顺延");
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/* 本期结论分组逻辑（与 renderEvoSummary 一致） */
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const evoEvents = [
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{ window: "2026Q2", change_type: "新增", skill: "Kubernetes", prev_weight: 0, curr_weight: 2.52 },
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{ window: "2026Q2", change_type: "增强", skill: "微服务", prev_weight: 1.3, curr_weight: 2.1 },
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{ window: "2026Q3", change_type: "减弱", skill: "JSP", prev_weight: 0.8, curr_weight: 0.2 },
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{ window: "2026Q3", change_type: "退出", skill: "Struts", prev_weight: 0.1, curr_weight: 0 },
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];
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const wins = [...new Set(evoEvents.map((e) => e.window))].sort().slice(-2);
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eq(wins.join(","), "2026Q2,2026Q3", "最近两个季度窗口");
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const verb = { "新增": "成为新要求", "增强": "需求显著增强", "减弱": "需求明显减弱", "退出": "退出能力画像" };
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eq(verb[evoEvents[1].change_type], "需求显著增强", "增强动词");
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const line = `${evoEvents[1].skill}（需求指数 ${evoEvents[1].prev_weight.toFixed(2)}→${evoEvents[1].curr_weight.toFixed(2)}）`;
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eq(line, "微服务（需求指数 1.30→2.10）", "需求指数文案");
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/* 热度走势默认近 8 季切片 */
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const heat = Array.from({ length: 30 }, (_, i) => [`20${10 + i}Q1`, i]);
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eq(heat.slice(-8).length, 8, "近8季切片");
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eq(heat.slice(-Infinity).length, 30, "全部范围");
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/* candidateTrust：候选可信等级四指标（JD≥15 / 企业≥5 / 增长趋势 / 差异度≥0.40） */
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const candidateTrust = loadFn("candidateTrust");
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const stageEffortText = loadFn("stageEffortText");
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const existJobs = [{ title: "Java开发工程师", required_skills: ["Java", "MySQL"], preferred_skills: ["Redis"] }];
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const strong = candidateTrust({
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source_count: 31, company_count: 12,
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support_windows: ["2025Q1", "2025Q2", "2025Q3", "2025Q4", "2026Q1", "2026Q2"],
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required_skills: ["RAG", "向量检索"], preferred_skills: [],
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}, existJobs);
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eq(strong.dots.length, 4, "四指标点");
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eq(strong.level, "高", "四指标全达标为高");
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const weak = candidateTrust({
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source_count: 3, company_count: 1, support_windows: ["2026Q2"],
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required_skills: ["Java", "MySQL"], preferred_skills: ["Redis"],
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}, existJobs);
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eq(weak.level, "低", "弱证据且与既有岗位重合为低");
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eq(weak.nearest.title, "Java开发工程师", "识别出最相近既有岗位");
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eq(weak.distinctness, 0, "技能完全重合时差异度为 0");
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/* stageEffortText：阶段预计投入（每周约 8 小时） */
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eq(stageEffortText(2), "2 周 / 约 16 小时", "阶段投入文案");
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eq(stageEffortText(1), "1 周 / 约 8 小时", "单周投入文案");
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/* ganttBars：甘特图横条位置（左偏移/宽度百分比） */
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const ganttBars = loadFn("ganttBars");
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const gb = ganttBars([2, 2, 4]);
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eq(gb.length, 3, "甘特条数");
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eq(gb[0].left + "," + gb[0].width, "0,25", "甘特首条位置");
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eq(gb[2].left + "," + gb[2].width, "50,50", "甘特末条位置");
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eq(ganttBars([4, 4])[1].left, 50, "等长两阶段第二条起点");
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/* diffSkillRows：时点画像 Git 风格差集 */
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const diffSkillRows = loadFn("diffSkillRows");
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const d = diffSkillRows(
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[{ skill: "Java", importance: "required" }, { skill: "JSP", importance: "preferred" }],
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[{ skill: "Java", importance: "preferred" }, { skill: "Kubernetes", importance: "required" }]);
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eq(d.add.map((r) => r.skill).join(","), "Kubernetes", "diff 新增");
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eq(d.del.map((r) => r.skill).join(","), "JSP", "diff 退出");
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eq(d.keep.length, 1, "diff 保留数");
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eq(d.keep[0].up, true, "加分升级必备标记");
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/* easeOutCubic：count-up 缓动曲线（0→1，中点已过 87.5%） */
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const easeOutCubic = loadFn("easeOutCubic");
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eq(easeOutCubic(0), 0, "缓动起点为 0");
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eq(easeOutCubic(1), 1, "缓动终点为 1");
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eq(easeOutCubic(0.5), 0.875, "缓动中点 easeOut 特征");
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eq(easeOutCubic(0.25) < easeOutCubic(0.5), true, "缓动单调递增");
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/* trendSeries：近 n 季度事件序列（总量 + 四类计数） */
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const trendSeries = new Function(
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`const CHANGE_META = { "新增": {}, "增强": {}, "减弱": {}, "退出": {} };\n${extractFn("trendSeries")}; return trendSeries;`)();
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const tsEvts = [
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...Array.from({ length: 9 }, (_, i) => ({ window: `20${10 + i}Q1`, change_type: "新增" })),
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{ window: "2018Q1", change_type: "增强" },
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{ window: "2018Q1", change_type: "退出" },
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{ window: "2018Q1", change_type: "其他" },
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];
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const ts = trendSeries(tsEvts, 8);
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eq(ts.length, 8, "趋势序列只取近 8 季");
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eq(ts[7].window, "2018Q1", "最近窗口在序列末尾");
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eq(ts[7].total, 4, "末季总量含未分类事件");
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eq(ts[7].byType["新增"], 1, "末季新增计数");
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eq(ts[7].byType["增强"], 1, "末季增强计数");
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eq(ts[7].byType["退出"], 1, "末季退出计数");
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eq(trendSeries([], 8).length, 0, "空事件空序列");
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/* computeReplaceBuckets：能力更替三桶（旧核心 / 持续 / 新核心，近 4 季度口径） */
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const computeReplaceBuckets = loadFn("computeReplaceBuckets");
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const rpWins = ["2025Q2", "2025Q3", "2025Q4", "2026Q1", "2026Q2", "2026Q3"];
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const rpEdges = [
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{ target: "JSP", intervals: [["2020Q1", "2025Q4"]] }, // 已退出 → 旧核心
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{ target: "Java", intervals: [["2020Q1", null]] }, // 持续
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{ target: "Kubernetes", intervals: [["2026Q1", null]] }, // 近 4 季进入 → 新核心
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{ target: "Docker", intervals: [["2025Q2", null]] }, // 起点不在近 4 季 → 持续
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];
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const rp = computeReplaceBuckets(rpEdges, rpWins);
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eq(rp.oldCore.map((e) => e.target).join(","), "JSP", "旧核心=已退出");
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eq(rp.cont.map((e) => e.target).join(","), "Java,Docker", "持续=生效且非近期进入");
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eq(rp.newCore.map((e) => e.target).join(","), "Kubernetes", "新核心=近 4 季进入");
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eq(computeReplaceBuckets(rpEdges, []).newCore.length, 0, "无窗口时无新核心");
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/* radarValues：双雷达候选人四维归一化（缺失 0 / 超界截断） */
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const radarValues = new Function(
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`const RADAR_KEYS = ["required", "preferred", "experience", "scenario"];\n${extractFn("radarValues")}; return radarValues;`)();
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eq(radarValues({ required: 80, preferred: 50, experience: 100, scenario: 0 }).join(","), "0.8,0.5,1,0", "雷达四维映射");
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eq(radarValues({ required: 120 }).join(","), "1,0,0,0", "雷达超界截断");
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eq(radarValues(null).join(","), "0,0,0,0", "雷达空对象兜底");
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/* graph.js 纯逻辑：时序边生效判定 / 职级带归属（函数在 IIFE 内，按两空格缩进闭合提取） */
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const gsrc = fs.readFileSync(path.join(__dirname, "..", "webui", "graph.js"), "utf-8");
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function loadGraphFns(names) {
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const code = names.map((n) => {
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const m = gsrc.match(new RegExp(`function ${n}\\([\\s\\S]*?\\n \\}`));
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if (!m) throw new Error(`graph.js 未找到函数 ${n}`);
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return m[0];
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}).join("\n");
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return new Function(`${code}; return { ${names.join(", ")} };`)();
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}
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const gf = loadGraphFns(["jobLevel", "levelBandOf", "edgeActiveAt"]);
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eq(gf.edgeActiveAt({ intervals: [] }, "2026Q1"), true, "无区间边始终生效");
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eq(gf.edgeActiveAt({ intervals: [["2025Q1", "2025Q3"]] }, "2025Q2"), true, "区间内生效");
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eq(gf.edgeActiveAt({ intervals: [["2025Q1", "2025Q3"]] }, "2025Q3"), false, "结束边界半开不生效");
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eq(gf.edgeActiveAt({ intervals: [["2025Q1", "2025Q3"]] }, "2024Q4"), false, "起点前不生效");
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eq(gf.edgeActiveAt({ intervals: [["2025Q1", null]] }, "2026Q4"), true, "开放区间持续生效");
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eq(gf.jobLevel({ expected_years: 1 }), "初级", "≤2年初级");
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eq(gf.jobLevel({ expected_years: 4 }), "中级", "3-5年中级");
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eq(gf.jobLevel({ expected_years: 8 }), "高级", ">5年高级");
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eq(gf.levelBandOf({ type: "Job", expected_years: 1 }), 0, "初级岗位入带0");
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eq(gf.levelBandOf({ type: "Job", expected_years: 8 }), 2, "高级岗位入带2");
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eq(gf.levelBandOf({ type: "Skill", level: "L1" }), 0, "L1技能入带0");
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eq(gf.levelBandOf({ type: "Skill", level: "L3" }), 2, "L3技能入带2");
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eq(gf.levelBandOf({ type: "Skill" }), 1, "无级别技能默认中级带");
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/* graph.js 纯逻辑：搜索排序 / 岗位对比 / 时序季度摘要 */
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const gf2 = loadGraphFns(["searchRank", "compareJobs", "windowDigest"]);
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const SN = [
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{ id: "job_Java开发工程师", type: "Job", title: "Java开发工程师" },
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{ id: "job_Java架构师", type: "Job", title: "Java架构师" },
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{ id: "JavaScript", type: "Skill", title: "JavaScript" },
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{ id: "Docker", type: "Skill", title: "Docker" },
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];
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eq(gf2.searchRank(SN, "").length, 0, "搜索：空串无结果");
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eq(gf2.searchRank(SN, "架构").map((n) => n.id).join(","), "job_Java架构师", "搜索：中文子串命中");
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eq(gf2.searchRank(SN, "javascript")[0].id, "JavaScript", "搜索：大小写不敏感");
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eq(gf2.searchRank(SN, "java")[0].type, "Job", "搜索：并列时岗位优先于技能");
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const CE = [
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{ source: "A", target: "Java", rel: "REQUIRES", importance: "required" },
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{ source: "A", target: "MySQL", rel: "REQUIRES", importance: "required" },
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{ source: "B", target: "Java", rel: "REQUIRES", importance: "required" },
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{ source: "B", target: "Go", rel: "REQUIRES", importance: "required" },
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{ source: "B", target: "K8s", rel: "REQUIRES", importance: "preferred" },
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{ source: "A", target: "X场景", rel: "APPLIES_TO" },
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{ source: "B", target: "Y技能", rel: "REQUIRES", importance: "required", pending: true },
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];
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const cmp = gf2.compareJobs(CE, "A", "B");
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eq(cmp.shared.map((x) => x.skill).join(","), "Java", "对比：共有技能（忽略非技能关系与待审核边）");
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eq(cmp.onlyA.map((x) => x.skill).join(","), "MySQL", "对比：A 独有");
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eq(cmp.onlyB.map((x) => x.skill).join(","), "Go,K8s", "对比：B 独有");
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eq(cmp.gaps.join(","), "Go", "对比：转岗必备缺口只算 required");
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eq(cmp.bReq, 2, "对比：目标必备总数");
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eq(cmp.covered, 1, "对比：必备已覆盖数");
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eq(cmp.ready, 0.5, "对比：就绪度=覆盖/必备");
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const WE = [
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{ source: "job_A", target: "Java", intervals: [["2025Q1", null]] },
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{ source: "job_A", target: "K8s", intervals: [["2026Q1", null]] },
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{ source: "job_B", target: "Go", intervals: [["2026Q1", null]] },
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];
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const WEV = [
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{ window: "2026Q1", change_type: "新增", skill: "K8s", job_id: "job_A" },
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{ window: "2026Q1", change_type: "退出", skill: "JSP", job_id: "job_A" },
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{ window: "2025Q4", change_type: "增强", skill: "Java", job_id: "job_A" },
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];
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const WN = [
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{ id: "job_A", type: "Job", title: "A工程师" },
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{ id: "job_B", type: "Job", title: "B工程师" },
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];
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const dg = gf2.windowDigest(WE, WEV, WN, "2026Q1");
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eq(dg.newEdges.length, 2, "摘要：当季新增关系数");
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eq(dg.newJobs.join(","), "B工程师", "摘要：当季新晋岗位按首次出现窗口判定");
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eq(dg.added.length, 1, "摘要：当季新增事件");
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eq(dg.exited.length, 1, "摘要：当季退出事件");
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eq(dg.boosted.length, 0, "摘要：非当季事件不计入");
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/* graph.js 纯逻辑：凸包（技术栈类别气泡轮廓） */
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const gf3 = loadGraphFns(["convexHull"]);
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const sq = [{ x: 0, y: 0 }, { x: 10, y: 0 }, { x: 10, y: 10 }, { x: 0, y: 10 }, { x: 5, y: 5 }];
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eq(gf3.convexHull(sq).length, 4, "凸包：内部点被剔除");
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eq(gf3.convexHull([{ x: 0, y: 0 }, { x: 5, y: 5 }]).length, 2, "凸包：两点原样返回");
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eq(gf3.convexHull([{ x: 0, y: 0 }, { x: 5, y: 0 }, { x: 10, y: 0 }]).length, 2, "凸包：共线点只留端点");
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const hullPt = gf3.convexHull(sq);
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eq(hullPt.some((p) => p.x === 5 && p.y === 5), false, "凸包：中心点不在顶点中");
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console.log(`\n${pass} passed, ${fail} failed`);
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process.exit(fail ? 1 : 0);
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