test(scripts): 36 个 E2E 与 6 个机械校验工具（1548 条断言）+ 一键交付自检
新增：check-api-parity（契约 121 接口 ↔ 控制器，自带「必须恰好 121」自检）、 check-entity-columns（基类要求的列 vs 迁移建表列，F-35 那个坑踩了四次之后上的工具）、 check-manual（手册引用的错误码与提示文案对得上代码）、check-test-profile（test profile 真起一次）、 e2e-prodguard、load-test（四场景、按端点分别统计）、verify-all（一条命令跑完交付自检）、 dev-seed-audit（界面验收用的演示数据），以及 M1~M9 各轮 E2E。 压测抓到一个真缺陷并修掉（F-92）：门禁 IP 限流原来计「所有请求」，于是一个班连同一个 WiFi 时 60 个不同学生同时核验只过了 20 个 → 改为只计失败 + 单独的成功上限，20/60 → 60/60。 度量工具的偏差会伪装成产品缺陷（F-60/F-77/F-97），所以每个脚本都断言「动作自己的结论字段」 （submitted / created / canExport），而不是 HTTP 200 + code 0。 验证：verify-all.py --quick 5/5；--with-e2e 见 docs/09 §8。
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# -*- coding: utf-8 -*-
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"""压测（M7-09）：门禁并发 / 上传并发 / 读接口 / 导出大任务
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## 为什么值得真跑一次，而不是"看代码觉得没问题"
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这个项目的三个并发热点，每一个都有"看代码看不出来"的地方：
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| 场景 | 直觉 | 实际可能卡在 |
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|---|---|---|
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| 门禁核验（60 人同时扫码） | "就是查一下名册" | 每个请求都要 **AES 解密全表证件号** 逐个比对（密文没法走索引） |
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| 上传（30 人同时传） | "就是写个文件" | 图片压缩是 **CPU 密集**，而 Tomcat 线程数有限 |
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| 读接口（列表/统计） | "加个索引就行" | 连接池只有 20 条，长事务（导出打包）会把池子占死 |
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| 导出大任务 | "异步的，不影响" | 导出**同步**做前置检查 + 打包，而它在一个大事务里 |
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所以这份脚本不做"泛泛压一下"，而是**针对这四个场景各设计一组**，
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并把 p50/p95/p99 与错误码分布打出来 —— **错误码分布比成功率更有信息量**
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（40071 是限流、50000 是内部错、40301 是权限，三种要修的地方完全不同）。
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## 用法
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```bash
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python scripts/load-test.py # 全套（约 2~3 分钟）
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python scripts/load-test.py --only gate # 只跑门禁
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python scripts/load-test.py --conc 40 # 改并发
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```
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⚠️ 它**会往库里写东西**（名册、填报单、材料），结尾会清理；
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中途 Ctrl-C 会留下残留 —— 用 `--clean` 单独清理一次即可。
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"""
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import argparse
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import base64
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import concurrent.futures as cf
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import importlib.util
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import json
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import os
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import statistics
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import subprocess
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import sys
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import time
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import urllib.error
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import urllib.request
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import uuid
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sys.stdout.reconfigure(encoding="utf-8")
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ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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BASE = "http://localhost:8080"
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SUFFIX = uuid.uuid4().hex[:6]
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TMP_ROSTER = os.path.join(ROOT, "scripts", f"_lt-roster-{SUFFIX}.xlsx")
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TMP_IMG = os.path.join(ROOT, "scripts", f"_lt-img-{SUFFIX}.jpg")
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# 压测规模（可按机器调整；--rows 会覆盖 GATE_USERS）
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GATE_USERS = 60 # 名册人数（同时也是门禁的并发用户数）
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READ_CONC = 20 # 读接口并发
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READ_ROUNDS = 8 # 每个并发线程的轮数
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UPLOAD_USERS = 20 # 上传：20 个学生同时传
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UPLOAD_PER_USER = 2 # 每人传几张
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TASK_IDS = []
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ROSTER_IDS = []
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UIDS = []
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def _load(name, fn):
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spec = importlib.util.spec_from_file_location(name, os.path.join(ROOT, "scripts", fn))
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mod = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(mod)
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return mod
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R = _load("e2e_m2_roster", "e2e-m2-roster.py")
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def sql(s):
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return R.sql(s)[1]
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def one(s):
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v = sql(s)
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return v.split("\n")[0].strip() if v else ""
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def call(method, path, token=None, body=None, timeout=60):
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return R.call(method, BASE + path, token, body, timeout=timeout)
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# ══════════════ 计时与统计 ══════════════
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class Stat:
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"""一个场景的耗时与错误码统计。"""
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def __init__(self, name):
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self.name = name
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self.lat = []
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self.codes = {}
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self.fail_detail = []
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self.t0 = time.perf_counter()
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self.t1 = None
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def done(self):
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"""场景结束（算吞吐要墙钟时间，不是"平均耗时的倒数"）。"""
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self.t1 = time.perf_counter()
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def add(self, ms, code):
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self.lat.append(ms)
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self.codes[code] = self.codes.get(code, 0) + 1
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def report(self):
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if not self.lat:
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print(" %-22s 没有样本" % self.name)
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return
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s = sorted(self.lat)
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n = len(s)
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ok = self.codes.get(0, 0)
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# ⚠️ 吞吐 = 请求数 / **墙钟耗时**。
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# 原来的式子化简后是 1/平均耗时 —— 那不是吞吐，
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# 而"一行看起来很像结论的数字"最容易被抄进汇报里
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elapsed = (self.t1 or time.perf_counter()) - self.t0
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print(" %-24s 请求 %-5d 成功 %-5d 失败 %-4d "
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"p50 %6.1fms p95 %7.1fms p99 %7.1fms max %7.1fms 吞吐 %5.0f/s"
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% (self.name, n, ok, n - ok,
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s[int(n * 0.50)], s[min(n - 1, int(n * 0.95))],
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s[min(n - 1, int(n * 0.99))], s[-1],
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n / max(0.001, elapsed)))
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# ⚠️ 错误码分布比成功率更有信息量：40071 限流 / 50000 内部错 / 40301 权限
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bad = {k: v for k, v in self.codes.items() if k != 0}
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if bad:
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print(" 失败分布：%s" % json.dumps(bad, ensure_ascii=False))
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if self.fail_detail:
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print(" 首个失败样本：%s" % self.fail_detail[0][:200])
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def timed(fn):
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t0 = time.perf_counter()
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try:
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code, body = fn()
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except Exception as e: # noqa: BLE001
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return (time.perf_counter() - t0) * 1000, -1, str(e)
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return (time.perf_counter() - t0) * 1000, code, body
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# ══════════════ 夹具 ══════════════
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def build_fixture(admin):
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"""造一个任务 + N 个名册人（每人一个已知证件号）+ 对应 uid 的 MP token。"""
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_, orgs = call("GET", "/api/v1/orgs/tree", admin)
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classes = []
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def walk(ns):
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for n in ns or []:
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if n.get("orgType") == 3:
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classes.append(n)
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walk(n.get("children"))
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walk(orgs.get("data") or [])
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if not classes:
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raise SystemExit("没有班级节点")
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org = classes[0]
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_, b = call("POST", "/api/v1/tasks", admin, {
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"taskName": f"压测任务 {SUFFIX}", "batchNo": "202609", "majorName": "数控加工",
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"collectMode": 1, "certType": 1,
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"startTime": "2026-01-01", "endTime": "2099-12-31",
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})
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tid = b["data"]["id"]
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TASK_IDS.append(tid)
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call("POST", f"/api/v1/tasks/{tid}/materials", admin, {
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"materialCode": "IDCARD", "materialName": "身份证", "required": True,
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"fileTypes": ["jpg", "jpeg", "png"], "maxSizeKb": 2048, "maxCount": 3,
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"minSizeKb": 1, "minLongSide": 100,
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})
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call("PUT", f"/api/v1/tasks/{tid}/orgs", admin,
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{"orgs": [{"orgId": org["id"], "expectedCount": GATE_USERS}]})
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# N 个证件号（前 17 位递增，校验位由脚本补）
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rows = []
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for i in range(GATE_USERS):
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# ⚠️ 身份证号是**定长**的：6 位地区 + 8 位出生日期 + 3 位顺序 + 1 位校验。
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# 所以任何一段"从序号推出来的值"都必须**取模保证位数** ——
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# 我原来写 `"%03d" % (100 + i)`，i >= 900 时变成 4 位，
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# 号码成了 19 位，2000 人的夹具只导进去 900 个。
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#
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# 这里把序号拆成"地区码分块 + 3 位顺序号"：每 1000 人换一个地区码。
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# 出生日期固定用 20080101（必须是**真实存在的日期** —— 我曾经拼出
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# `20081000`，被导入校验以"出生日期要真实存在"拒掉，而那条校验抓的
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# 不是格式，是"这个号码不可能属于一个人"）。
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area = "%06d" % (361029 + i // 1000)
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seq = "%03d" % (i % 1000)
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idc = R.with_checksum(area + "20080101" + seq)
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rows.append((f"压测{i:04d}", idc))
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build_roster(rows)
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body = R.upload_roster(BASE, admin, tid, TMP_ROSTER,
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extra={"dryRun": "false", "mode": "APPEND", "orgId": org["id"]})
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# ⚠️ **判据是 data.created，不是 code**：导入了 0 行也是 code=0
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# （体检报告在 data 里）。判错的话压测会"没有样本"，
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# 而那个现象看起来像压测脚本坏了 —— 与 F-84 是同一个坑
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rep = body.get("data") or {}
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if body.get("code") != 0 or rep.get("created") != GATE_USERS:
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raise SystemExit("夹具名册导入没达标：code=%s created=%s errors=%s"
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% (body.get("code"), rep.get("created"),
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json.dumps(rep.get("errors"), ensure_ascii=False)[:300]))
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ids = sql(f"select id, id_card_no from collect_roster where task_id={tid} "
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f"and deleted=0 order by id;")
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# ⚠️ 证件号在库里是密文，压测要的是**明文**（门禁接口收明文），所以直接用生成的
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roster_rows = []
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for idx, line in enumerate([x for x in ids.split("\n") if x.strip()]):
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rid = int(line.split("|")[0])
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ROSTER_IDS.append(rid)
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roster_rows.append({"rosterId": rid, "name": rows[idx][0], "idCardNo": rows[idx][1]})
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if len(roster_rows) != GATE_USERS:
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raise SystemExit("夹具名册行数不对：期望 %d，实际 %d"
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% (GATE_USERS, len(roster_rows)))
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call("POST", f"/api/v1/tasks/{tid}/publish", admin, {"force": True})
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cfg = R.read_dev_config()
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tokens = []
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for i, r in enumerate(roster_rows):
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uid = 998000 + i
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UIDS.append(uid)
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tokens.append({"uid": uid, "token": R.mint_mp_token(
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cfg["jwt_secret"], cfg["issuer"], uid, 1, ["STUDENT"], 4),
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"name": r["name"], "idCardNo": r["idCardNo"], "rosterId": r["rosterId"]})
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return tid, tokens
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def build_roster(rows):
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from openpyxl import Workbook
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wb = Workbook()
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ws = wb.active
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ws.title = "压测班"
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header = ["序号", "姓名", "身份证号", "学历", "联系电话", "工作单位",
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"报考职业", "报考工种", "报考等级", "是否补考",
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"补考理论", "补考实操", "补考综合", "是否在校生",
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"在读学校", "所学专业", "入学时间"]
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for c, t in enumerate(header, start=1):
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ws.cell(row=1, column=c, value=t)
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for i, (name, idc) in enumerate(rows):
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vals = [i + 1, name, idc, "中专", "138001399%02d" % (i % 100), "无",
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"车工", "数控车工", "四级", "否", "", "", "", "是",
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"示范职业学校", "数控加工", "2024-09-01"]
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for c, v in enumerate(vals, start=1):
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if v != "":
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ws.cell(row=i + 2, column=c, value=v)
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wb.save(TMP_ROSTER)
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def make_img(size_kb=400):
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"""造一张尽量接近真实照片的图（纯色会被压得很小，失真）。"""
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import random
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random.seed(7)
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# 最小合法 JPEG 头 + 随机填充（不是真 JPEG，但上传接口只看扩展名与大小）
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with open(TMP_IMG, "wb") as f:
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f.write(b"\xff\xd8\xff\xe0\x00\x10JFIF\x00\x01\x01\x00\x00\x01\x00\x01\x00\x00")
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f.write(bytes(random.getrandbits(8) for _ in range(size_kb * 1024)))
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f.write(b"\xff\xd9")
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def reset_gate():
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"""清门禁限流（每用户 10 次/小时）。压测每个用户只核验 1 次，理论上不触发；
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但重复跑会累积，所以开跑前清一次。"""
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for uid in UIDS:
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os.system('docker exec xt-redis redis-cli -a redis_dev_pwd --no-auth-warning '
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'DEL xt:mp:gate:user:%d > NUL 2>&1' % uid)
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# ══════════════ 场景 ══════════════
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def scenario_gate(tid, tokens, conc):
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"""门禁核验：N 个学生同时扫码。"""
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st = Stat("门禁核验")
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reset_gate()
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def one_req(t):
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def go():
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c, b = call("POST", "/api/v1/mp/roster/match", t["token"],
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{"taskId": tid, "realName": t["name"], "idCardNo": t["idCardNo"]},
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timeout=60)
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return c if c == 200 else c, b
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ms, code, body = timed(go)
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# 业务码在 body 里（HTTP 200 + code != 0），要分开统计
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biz = body.get("code") if isinstance(body, dict) else None
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return ms, int(biz if biz is not None else code), body
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with cf.ThreadPoolExecutor(max_workers=conc) as ex:
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for ms, code, body in ex.map(one_req, tokens):
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st.add(ms, code)
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if code != 0 and len(st.fail_detail) < 3:
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st.fail_detail.append(json.dumps(body, ensure_ascii=False))
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st.done()
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st.report()
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return st
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def scenario_read(tid, admin, conc, rounds):
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"""
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读接口：任务列表 / 名册列表 / 任务统计 / 待办。
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|
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⚠️ **按端点分开统计**，不要只报一个"混合 p95"：
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压测的目的就是回答"该优化哪个"，而混在一起的数字回答不了 ——
|
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四个接口里可能有一个占掉 90% 的耗时，而混合 p95 会把它的形状抹平。
|
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"""
|
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paths = [
|
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("GET", f"/api/v1/tasks?pageNum=1&pageSize=20", "任务列表"),
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("GET", f"/api/v1/tasks/{tid}/roster?pageNum=1&pageSize=50", "名册列表(50/页)"),
|
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("GET", f"/api/v1/tasks/{tid}/roster?pageNum=1&pageSize=200", "名册列表(200/页)"),
|
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("GET", f"/api/v1/tasks/{tid}/statistics", "任务统计"),
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("GET", f"/api/v1/audit/todos?pageNum=1&pageSize=20", "审核待办"),
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]
|
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stats = {label: Stat(label) for _m, _p, label in paths}
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|
||||
def worker(_):
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out = []
|
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for _r in range(rounds):
|
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for m, p, label in paths:
|
||||
def go():
|
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c, b = call(m, p, admin)
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return c, b
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ms, code, body = timed(go)
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biz = body.get("code") if isinstance(body, dict) else None
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out.append((label, ms, int(biz if biz is not None else code), body))
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return out
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|
||||
with cf.ThreadPoolExecutor(max_workers=conc) as ex:
|
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for results in ex.map(worker, range(conc)):
|
||||
for label, ms, code, body in results:
|
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st = stats[label]
|
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st.add(ms, code)
|
||||
if code != 0 and len(st.fail_detail) < 3:
|
||||
st.fail_detail.append(json.dumps(body, ensure_ascii=False))
|
||||
for st in stats.values():
|
||||
st.done()
|
||||
for label in [x[2] for x in paths]:
|
||||
stats[label].report()
|
||||
return stats
|
||||
|
||||
|
||||
def scenario_upload(tid, tokens, conc):
|
||||
"""上传：并发上传图片（压缩是 CPU 密集）。"""
|
||||
st = Stat("材料上传")
|
||||
make_img()
|
||||
sub_ids = {}
|
||||
# 每个用户先建草稿
|
||||
for t in tokens[:conc]:
|
||||
c, b = call("POST", "/api/v1/mp/submissions", t["token"], {"taskId": tid})
|
||||
if c == 200 and isinstance(b, dict) and b.get("code") == 0:
|
||||
sub_ids[t["uid"]] = b["data"]["id"]
|
||||
|
||||
def one_req(t):
|
||||
sid = sub_ids.get(t["uid"])
|
||||
if sid is None:
|
||||
return 0.0, -2, {"msg": "没有草稿"}
|
||||
def go():
|
||||
return upload_file("/api/v1/mp/files/upload", t["token"], sid, TMP_IMG)
|
||||
ms, code, body = timed(go)
|
||||
biz = body.get("code") if isinstance(body, dict) else None
|
||||
return ms, int(biz if biz is not None else code), body
|
||||
|
||||
jobs = []
|
||||
for t in tokens[:conc]:
|
||||
for _ in range(UPLOAD_PER_USER):
|
||||
jobs.append(t)
|
||||
with cf.ThreadPoolExecutor(max_workers=conc) as ex:
|
||||
for ms, code, body in ex.map(one_req, jobs):
|
||||
st.add(ms, code)
|
||||
if code != 0 and len(st.fail_detail) < 3:
|
||||
st.fail_detail.append(json.dumps(body, ensure_ascii=False))
|
||||
st.done()
|
||||
st.report()
|
||||
return st
|
||||
|
||||
|
||||
def upload_file(path, token, submission_id, file_path, timeout=180):
|
||||
boundary = "----lt" + uuid.uuid4().hex[:12]
|
||||
name = os.path.basename(file_path)
|
||||
with open(file_path, "rb") as f:
|
||||
content = f.read()
|
||||
|
||||
def part(field, value):
|
||||
return (f"--{boundary}\r\nContent-Disposition: form-data; name=\"{field}\"\r\n\r\n"
|
||||
f"{value}\r\n").encode("utf-8")
|
||||
|
||||
body = b""
|
||||
body += part("submissionId", submission_id)
|
||||
body += part("materialCode", "IDCARD")
|
||||
body += (f"--{boundary}\r\nContent-Disposition: form-data; name=\"file\"; "
|
||||
f"filename=\"{name}\"\r\nContent-Type: image/jpeg\r\n\r\n").encode("utf-8")
|
||||
body += content + b"\r\n" + f"--{boundary}--\r\n".encode("utf-8")
|
||||
|
||||
req = urllib.request.Request(BASE + path, data=body, method="POST", headers={
|
||||
"Content-Type": f"multipart/form-data; boundary={boundary}",
|
||||
"Authorization": f"Bearer {token}",
|
||||
})
|
||||
try:
|
||||
with urllib.request.urlopen(req, timeout=timeout) as resp:
|
||||
return resp.status, json.loads(resp.read().decode("utf-8"))
|
||||
except urllib.error.HTTPError as e:
|
||||
return e.code, {"msg": e.read().decode("utf-8", "replace")[:200]}
|
||||
except Exception as e: # noqa: BLE001
|
||||
return -1, {"msg": str(e)}
|
||||
|
||||
|
||||
def scenario_export(tid, admin):
|
||||
"""导出：前置检查（只读）+ 创建（同步打包）。"""
|
||||
st_pre = Stat("导出前置检查")
|
||||
ms, code, body = timed(lambda: call("GET", f"/api/v1/exports/precheck?taskId={tid}", admin))
|
||||
st_pre.add(ms, int((body or {}).get("code", code)))
|
||||
st_pre.done()
|
||||
st_pre.report()
|
||||
if code != 200 or (body or {}).get("code") != 0:
|
||||
print(" 前置检查没通过，跳过创建：%s" % json.dumps(body, ensure_ascii=False)[:200])
|
||||
return
|
||||
pre = (body or {}).get("data") or {}
|
||||
can = pre.get("canExport")
|
||||
ms, code, body = timed(lambda: call("POST", "/api/v1/exports", admin, {
|
||||
"taskId": tid, "exportName": f"压测导出 {SUFFIX}", "onlyApproved": False,
|
||||
}, timeout=600))
|
||||
biz = int((body or {}).get("code", code))
|
||||
msg = (body or {}).get("msg") or ""
|
||||
if can is False:
|
||||
# ⚠️ 前置检查不通过时，创建接口**必须也拒绝** —— 这是契约里那条铁律
|
||||
# （`canExport=false` 时禁用按钮、不弹警告放行）的服务端一半。
|
||||
# 把它报成"压测失败"是误导：它会让人以为导出坏了。
|
||||
blocked = biz == 40035
|
||||
print(" 前置检查：canExport=false（%d 项 blocking）→ 创建接口%s"
|
||||
% (len(pre.get("blocking") or []),
|
||||
"**正确拒绝**（40035）✓ 铁律在服务端也生效" if blocked
|
||||
else "竟然放行了 ✗（msg=%s）" % msg[:80]))
|
||||
if not blocked:
|
||||
print(" ⚠️ 这是**缺陷**：界面靠 canExport 禁用按钮，"
|
||||
"而这里是最后一道服务端防线 —— 它必须自己拦一次")
|
||||
else:
|
||||
st_new = Stat("导出创建（同步打包）")
|
||||
st_new.add(ms, biz)
|
||||
st_new.done()
|
||||
st_new.report()
|
||||
if biz == 0:
|
||||
eid = (body.get("data") or {}).get("id")
|
||||
print(" 导出任务 id=%s（异步打包，这里只量「创建+排队」的耗时）" % eid)
|
||||
|
||||
|
||||
# ══════════════ 清理 ══════════════
|
||||
|
||||
def cleanup():
|
||||
for tid in TASK_IDS:
|
||||
for tbl in ("collect_validation_issue", "collect_audit_record", "collect_notify_record",
|
||||
"collect_file", "collect_submission", "collect_roster",
|
||||
"collect_task_org", "collect_material_def"):
|
||||
sql("delete from %s where task_id=%s;" % (tbl, tid))
|
||||
sql("delete from collect_task where id=%s;" % tid)
|
||||
for uid in UIDS:
|
||||
sql("delete from collect_message where user_id=%d;" % uid)
|
||||
for p in (TMP_ROSTER, TMP_IMG):
|
||||
if os.path.exists(p):
|
||||
os.remove(p)
|
||||
print(" 已清理：压测任务 / 名册 / 材料 / 消息 / 临时文件")
|
||||
|
||||
|
||||
def main():
|
||||
# ⚠️ `global` 必须出现在**同一函数里第一次使用该名字之前** ——
|
||||
# 放晚了会报 "name 'X' is used prior to global declaration"
|
||||
global GATE_USERS
|
||||
|
||||
ap = argparse.ArgumentParser(description="压测（门禁/上传/读/导出）")
|
||||
ap.add_argument("--only", default="", help="只跑一个场景：gate / read / upload / export")
|
||||
ap.add_argument("--conc", type=int, default=0, help="覆盖并发数")
|
||||
ap.add_argument("--clean", action="store_true", help="只清理上次残留")
|
||||
ap.add_argument("--rows", type=int, default=0,
|
||||
help="名册人数（默认 %d）。⚠️ 谈响应时间必须带上规模" % GATE_USERS)
|
||||
ap.add_argument("--with-upload", action="store_true",
|
||||
help="跑上传压测（⚠️ 会往真实对象存储写文件，默认关闭）")
|
||||
args = ap.parse_args()
|
||||
|
||||
if args.rows > 0:
|
||||
GATE_USERS = args.rows
|
||||
|
||||
if args.clean:
|
||||
# 残留任务按名字前缀找
|
||||
for line in sql("select id from collect_task where task_name like '压测任务 %';").split("\n"):
|
||||
if line.strip().isdigit():
|
||||
TASK_IDS.append(int(line.strip()))
|
||||
cleanup()
|
||||
return 0
|
||||
|
||||
print("=" * 100)
|
||||
print(" 压测（M7-09） 后端：%s" % BASE)
|
||||
print(" 规模：名册/门禁 %d 人 读 %d 并发 × %d 轮 上传 %d×%d（需 --with-upload）"
|
||||
% (GATE_USERS, READ_CONC, READ_ROUNDS, UPLOAD_USERS, UPLOAD_PER_USER))
|
||||
print(" ⚠️ 读接口的结果**必须带规模看**：同一个接口在 60 行与 2000 行上是两件事")
|
||||
print("=" * 100)
|
||||
|
||||
for acct in ("admin",):
|
||||
os.system('docker exec xt-redis redis-cli -a redis_dev_pwd --no-auth-warning '
|
||||
'DEL xt:login:fail:%s > NUL 2>&1' % acct)
|
||||
_, adm = R.login(BASE, "admin", "Admin@123", "demo")
|
||||
if adm.get("code") != 0:
|
||||
print("管理员登录失败：" + str(adm))
|
||||
return 2
|
||||
admin = adm["data"]["token"]
|
||||
|
||||
print("\n── 造夹具 ──")
|
||||
t0 = time.perf_counter()
|
||||
tid, tokens = build_fixture(admin)
|
||||
print(" 任务 %d，名册 %d 人，夹具耗时 %.1fs"
|
||||
% (tid, len(tokens), time.perf_counter() - t0))
|
||||
|
||||
stats = {}
|
||||
conc = args.conc
|
||||
try:
|
||||
if args.only in ("", "gate"):
|
||||
print("\n── ① 门禁核验（%d 人同时扫码，每个都要 AES 解密全表比对）──" % GATE_USERS)
|
||||
stats["gate"] = scenario_gate(tid, tokens, conc or GATE_USERS)
|
||||
if args.only in ("", "read"):
|
||||
print("\n── ② 读接口（任务/名册/统计/待办 混合，%d 并发 × %d 轮）──"
|
||||
% (READ_CONC, READ_ROUNDS))
|
||||
stats["read"] = scenario_read(tid, admin, conc or READ_CONC, READ_ROUNDS)
|
||||
if args.only == "upload" or (args.with_upload and args.only == ""):
|
||||
print("\n── ③ 材料上传（%d 人同时传，压缩是 CPU 密集）──" % UPLOAD_USERS)
|
||||
stats["upload"] = scenario_upload(tid, tokens, conc or UPLOAD_USERS)
|
||||
if args.only == "" and not args.with_upload:
|
||||
print("\n── ③ 材料上传（**默认跳过**）──")
|
||||
print(" ⚠️ 当前 dev 的存储是七牛**真实空间**（见 backend/application-local.yml），")
|
||||
print(" 压测上传会打到外部服务并把测试文件灌进真实桶。要跑就加 --with-upload，")
|
||||
print(" 且最好先把存储切成本地：XT_STORAGE_PROVIDER=local 重启后端。")
|
||||
if args.only in ("", "export"):
|
||||
print("\n── ④ 导出（前置检查 + 创建）──")
|
||||
scenario_export(tid, admin)
|
||||
finally:
|
||||
print("\n── 清理 ──")
|
||||
cleanup()
|
||||
|
||||
print("\n" + "=" * 100)
|
||||
print(" 结论：看 p95 与**失败分布**。失败码的含义：")
|
||||
print(" 40071 门禁限流（每用户 10 次/小时）—— 说明压测把同一个用户重复用了")
|
||||
print(" 42901 接口限流 50000 内部错（去看 backend/_dev-log.txt） 40301 权限")
|
||||
print("=" * 100)
|
||||
sys.stdout.flush()
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
raise SystemExit(main())
|
||||
Reference in New Issue
Block a user