mirror of
https://ghfast.top/https://github.com/aeroxw/easy_tdx_max.git
synced 2026-09-12 13:24:18 +08:00
feat(e2e): Playwright E2E 前端测试基建 — 后端合成数据 mock 模式 + 5 用例 + CI
- web/e2e_mock.py：EASY_TDX_E2E_MOCK=1 时 lifespan 替换 TDX/MAC 客户端为 确定性合成数据（CRC32 播种随机游走，分页语义对齐真实 /bars）；回测/WF/ 评估/自选/策略库仍走真实后端，SSE 由 QuoteStreamer 真轮询（mock 下 2s 一拍） - web-ui：@playwright/test + playwright.config.ts（webServer 自动起 serve， EASY_TDX_CONFIG_DIR 指向每轮临时目录）；e2e/ 5 用例覆盖看板五指数/SSE、 自选增删、回测全流程、附加分析（WF 柱状图+一条龙评估卡）、策略库保存 - package.json 加 test:e2e；CI frontend job 追加 E2E；verify_ci.sh 补前端段 - tests/unit/test_e2e_mock.py（11 例）守护 mock 契约；本地 npx playwright test 全绿
This commit is contained in:
GitHub
@@ -76,3 +76,16 @@ jobs:
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working-directory: web-ui
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- run: npm run build
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working-directory: web-ui
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# Playwright E2E（mock 模式）：serve 托管刚构建的 dist，行情全部来自
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# EASY_TDX_E2E_MOCK=1 合成数据，不连真实通达信服务器、不受交易时段限制。
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# 需要 Python 侧 easy-tdx[web]（webServer 用系统 python 启动 serve）。
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- uses: actions/setup-python@v5
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with:
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python-version: "3.13"
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- run: pip install -e ".[web]"
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- run: npx playwright install --with-deps chromium
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working-directory: web-ui
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- run: npm run test:e2e
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working-directory: web-ui
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env:
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EASY_TDX_PYTHON: python
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@@ -32,3 +32,8 @@ CLAUDE.md
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# 代码审计报告（本地产物，不入库）
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audit-report-*.html
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# Playwright E2E 运行产物（trace/截图/视频）与临时配置目录
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web-ui/e2e/.results/
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web-ui/test-results/
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web-ui/playwright-report/
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@@ -2,6 +2,12 @@
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本文件记录 easy-tdx 的版本变更。格式遵循 [Keep a Changelog](https://keepachangelog.com/zh-CN/)。
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## [未发布]
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### 新增
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- **Playwright E2E 前端测试基建**（升级计划 P4-1）——web-ui 引入 `@playwright/test`（`e2e/` + `playwright.config.ts`，`npm run test:e2e`）。**mock 方案选后端合成数据而非 page.route 拦截**：`EASY_TDX_E2E_MOCK=1` 时 serve 的 lifespan 把 TDX/MAC 客户端替换为合成数据客户端（`web/e2e_mock.py`，按 (market, code) CRC32 播种的确定性随机游走，分页语义与真实 /bars 一致），回测/WF/一条龙评估/自选/策略库继续走**真实后端代码**（它们本就不依赖行情连接），SSE 由 QuoteStreamer 真轮询合成数据全链路覆盖（mock 模式下轮询降到 2s 一拍，不受交易时段限制）。用例覆盖：看板五大指数区块+SSE 价格渲染、自选增删、回测全流程（净值图/绩效表/成交记录）、「附加分析」开关（WF 逐窗柱状图+一条龙评估卡）、策略库保存；`EASY_TDX_CONFIG_DIR` 指向每轮独立临时目录（断言可写死、不污染真实 `~/.easy_tdx`）。CI frontend job 追加 E2E 步骤；`verify_ci.sh` 补 `--no-frontend` 与前端 typecheck+build+E2E 段。新增 `tests/unit/test_e2e_mock.py`（11 例）守护 mock 与真实客户端的契约。
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## [1.27.0] — 2026-09-01
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**公式与轮动版本**——升级计划 P3 + P4（部分）落地：通达信公式解析器让写惯公式的用户零 Python 进入筛选/回测，轮动组合引擎补齐「排名换仓」组合形态，附 Docker 部署与一键门禁脚本。
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+22
-5
@@ -1,8 +1,9 @@
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#!/usr/bin/env bash
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# easy-tdx 一键本地门禁（等价 CI 的质量检查，v1.27 新增）。
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# easy-tdx 一键本地门禁（等价 CI 的质量检查，v1.27 新增；v1.28 补前端 E2E）。
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#
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# 用法：bash scripts/verify_ci.sh [--fast]
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# --fast 跳过全量测试（只跑 ruff + mypy + 格式检查）
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# 用法：bash scripts/verify_ci.sh [--fast] [--no-frontend]
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# --fast 跳过全量测试与前端（只跑 ruff + mypy + 格式检查）
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# --no-frontend 跳过前端 typecheck+build+E2E（只跑 Python 侧）
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#
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# 可选安装为 git hook（pre-push）：
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# ln -s ../../scripts/verify_ci.sh .git/hooks/pre-push
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@@ -19,7 +20,13 @@ if [ ! -f "$PY" ]; then
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fi
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FAST=0
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[ "${1:-}" = "--fast" ] && FAST=1
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NO_FRONTEND=0
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for arg in "$@"; do
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case "$arg" in
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--fast) FAST=1 ;;
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--no-frontend) NO_FRONTEND=1 ;;
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esac
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done
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echo "── ruff check ──────────────────────────────────────────"
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"$PY" -m ruff check src/ tests/
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@@ -31,7 +38,7 @@ echo "── mypy --strict ─────────────────
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"$PY" -m mypy src/easy_tdx/
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if [ "$FAST" = "1" ]; then
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echo "── 跳过测试（--fast）───────────────────────────────────"
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echo "── 跳过测试与前端（--fast）─────────────────────────────"
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echo "✓ verify_ci (fast) 全部通过"
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exit 0
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fi
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@@ -39,5 +46,15 @@ fi
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echo "── pytest（全量单元测试）────────────────────────────────"
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"$PY" -m pytest tests/ -q --ignore=tests/integration
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if [ "$NO_FRONTEND" = "0" ] && [ -d web-ui/node_modules ]; then
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echo "── 前端 typecheck + build ──────────────────────────────"
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(cd web-ui && npm run build)
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echo "── Playwright E2E（mock 模式，无需真实行情）────────────"
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(cd web-ui && npm run test:e2e)
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else
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echo "── 跳过前端（--no-frontend 或 web-ui/node_modules 缺失）─"
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fi
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echo ""
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echo "✓ verify_ci 全部通过"
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+39
-12
@@ -63,24 +63,40 @@ def _resolve_web_dist_dir() -> Path | None:
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@asynccontextmanager
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async def lifespan(app: FastAPI) -> AsyncGenerator[None, None]:
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"""管理 TDX 连接生命周期：启动时连接，关闭时断开。"""
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from easy_tdx.client import AsyncTdxClient
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"""管理 TDX 连接生命周期：启动时连接，关闭时断开。
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E2E mock 模式（``EASY_TDX_E2E_MOCK=1``，见 :mod:`easy_tdx.web.e2e_mock`）：
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全部行情连接替换为合成数据客户端（不连真实服务器、不受交易时段限制），
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回测 / 自选 / 策略库等纯计算路径保持真实，供 Playwright E2E 使用。
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"""
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from easy_tdx.web.e2e_mock import is_e2e_mock_enabled, log_mock_banner
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mock_mode = is_e2e_mock_enabled()
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# --- 标准 TDX 客户端 ---
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host = app.state.tdx_host
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port = app.state.tdx_port
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timeout = app.state.tdx_timeout
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client = AsyncTdxClient(host=host, port=port, timeout=timeout)
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try:
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await client.connect()
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logger.info("TDX client connected to %s:%s", host, port)
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except Exception:
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logger.warning("TDX client connection failed — endpoints will return 503")
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client: Any
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if mock_mode:
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from easy_tdx.web.e2e_mock import MockTdxClient
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log_mock_banner()
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client = MockTdxClient()
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else:
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from easy_tdx.client import AsyncTdxClient
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client = AsyncTdxClient(host=host, port=port, timeout=timeout)
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try:
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await client.connect()
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logger.info("TDX client connected to %s:%s", host, port)
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except Exception:
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logger.warning("TDX client connection failed — endpoints will return 503")
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app.state.tdx_client = client
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# --- 实时行情 SSE 推送器（共享轮询 + fan-out） ---
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# --- 实时行情 SSE 推送器（共享轮询 + fan-out；mock 模式轮询合成数据） ---
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try:
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from easy_tdx.models.enums import Market
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from easy_tdx.web.quote_streamer import QuoteStreamer
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@@ -92,7 +108,14 @@ async def lifespan(app: FastAPI) -> AsyncGenerator[None, None]:
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# SQLite 存 "SH"/"SZ"/"BJ" 字符串，轮询器需要 Market 枚举
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return [(Market[mkt], code) for mkt, code in store.symbols()]
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streamer = QuoteStreamer(client.get_security_quotes, _watch_symbols)
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# mock 模式不受真实限流/交易时段约束，缩短轮询间隔让 E2E 的
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# SSE 断言（首帧价格渲染）秒级到达，而不是等盘外 60s 慢拍
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streamer = QuoteStreamer(
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client.get_security_quotes,
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_watch_symbols,
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trading_interval=2.0 if mock_mode else 8.0,
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idle_interval=2.0 if mock_mode else 60.0,
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)
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streamer.start()
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app.state.quote_streamer = streamer
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except Exception:
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@@ -100,9 +123,13 @@ async def lifespan(app: FastAPI) -> AsyncGenerator[None, None]:
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app.state.quote_streamer = None
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# --- MAC 协议客户端 ---
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mac_client = None
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mac_client: Any = None
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enable_mac = getattr(app.state, "enable_mac", True)
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if enable_mac:
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if mock_mode:
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from easy_tdx.web.e2e_mock import MockMacClient
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mac_client = MockMacClient()
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elif enable_mac:
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try:
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from easy_tdx.mac.client import AsyncMacClient
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@@ -0,0 +1,467 @@
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"""E2E 合成行情数据源（``EASY_TDX_E2E_MOCK=1`` 时由 serve 激活）。
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**为什么在 FastAPI 层 mock 而不是用 Playwright ``page.route`` 拦截**：
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1. 回测 / WF / 一条龙评估 / 自选 / 策略库全部走**真实后端代码路径**（纯计算 +
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SQLite CRUD，本来就不依赖行情连接），E2E 能捕获后端 schema 变更；route 拦截
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的静态 JSON 会与后端 schema 漂移，测试通过不代表系统可用。
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2. SSE（``/stream/quotes``，EventSource）无法用 ``page.route`` 稳定 mock（需要
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流式 body）；mock 客户端让 QuoteStreamer 真正轮询合成数据，前端 SSE 链路
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（连接→首帧→快照渲染）也被覆盖。
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3. 任务型端点（提交→task_id→轮询→done）在 route 拦截里要手写状态机，mock
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客户端天然支持。
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代价：本模块必须与真实客户端的方法签名/返回列保持一致——由
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``tests/unit/test_e2e_mock.py`` 与 E2E 套件本身共同守护。
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数据特征：
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- **确定性**：每个 (market, code) 用 CRC32 做随机种子，同一进程内多次调用、
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不同机器上跑 E2E，行情完全一致（回测结果可复现、断言可写死）。
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- **锚定今天**：K 线序列以「今天」为最新一根（bdate_range），与前端默认日期
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范围（开始 2020-01-06 ~ 结束今天）自然咬合。
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- **分页语义**与真实 /bars 一致：``start=0`` 返回最新 ``count`` 根（页内升序），
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``start`` 递增向更早翻页（前端 fetchBars 依赖此语义拼接）。
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"""
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from __future__ import annotations
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import logging
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import zlib
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from datetime import datetime, timedelta
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from typing import Any
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import numpy as np
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import pandas as pd
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logger = logging.getLogger(__name__)
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__all__ = ["MockTdxClient", "MockMacClient", "E2E_MOCK_ENV"]
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#: 激活环境变量名（serve 启动时读取，见 web/app.py lifespan）。
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E2E_MOCK_ENV = "EASY_TDX_E2E_MOCK"
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# 合成 K 线总根数（约 10.4 年日线）。前端默认区间 2020-01-06 ~ 今天约 1660 根，
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# 翻页上限 10×800；2600 根既覆盖默认区间，又让第 3 页就翻到数据起点。
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_HISTORY_BARS = 2600
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# 已知代码 → 中文名（提升 E2E 可读性；未命中用「股票XXXXXX」兜底）。
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_KNOWN_NAMES: dict[str, str] = {
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"600519": "贵州茅台",
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"000001": "平安银行",
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"603986": "兆易创新",
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"600000": "浦发银行",
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"300750": "宁德时代",
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"000001|SH": "上证指数",
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"399001": "深证成指",
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"399006": "创业板指",
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"000688": "科创50",
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"000300": "沪深300",
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}
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|
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|
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def _market_str(market: Any) -> str:
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"""任意市场表示（枚举/int/字符串）→ 规范字符串 SZ/SH/BJ。"""
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mapping = {
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"0": "SZ",
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"1": "SH",
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"2": "BJ",
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"MARKET.SZ": "SZ",
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"MARKET.SH": "SH",
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"MARKET.BJ": "BJ",
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}
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s = str(market).upper()
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return mapping.get(s, s)
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def _seed(market: Any, code: str) -> int:
|
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"""(market, code) → 确定性随机种子（CRC32）。"""
|
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return zlib.crc32(f"{_market_str(market)}{code}".encode())
|
||||
|
||||
|
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def _display_name(market: Any, code: str) -> str:
|
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"""代码 → 中文名。仅 SH 的 000001 有歧义（平安银行 vs 上证指数），用
|
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``code|SH`` 键消歧；其余市场直接按代码查。"""
|
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if _market_str(market) == "SH" and f"{code}|SH" in _KNOWN_NAMES:
|
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return _KNOWN_NAMES[f"{code}|SH"]
|
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return _KNOWN_NAMES.get(code, f"股票{code}")
|
||||
|
||||
|
||||
def _synth_closes(market: Any, code: str, n: int) -> np.ndarray:
|
||||
"""生成 n 根确定性随机游走收盘价（指数基准价位 5~50 元）。"""
|
||||
rng = np.random.default_rng(_seed(market, code))
|
||||
base = 5.0 + rng.uniform(0.0, 45.0)
|
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rets = rng.normal(0.0004, 0.018, n)
|
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return base * np.cumprod(1.0 + rets)
|
||||
|
||||
|
||||
def _synth_ohlcv(market: Any, code: str, n: int) -> pd.DataFrame:
|
||||
"""生成 n 根升序 OHLCV 日线（datetime 为 pd.Timestamp，MAC 契约）。"""
|
||||
rng = np.random.default_rng(_seed(market, code))
|
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close = _synth_closes(market, code, n)
|
||||
open_ = np.empty(n)
|
||||
open_[0] = close[0]
|
||||
open_[1:] = close[:-1] * (1.0 + rng.normal(0.0, 0.004, n - 1))
|
||||
high = np.maximum(open_, close) * (1.0 + np.abs(rng.normal(0.0, 0.006, n)))
|
||||
low = np.minimum(open_, close) * (1.0 - np.abs(rng.normal(0.0, 0.006, n)))
|
||||
vol = rng.integers(50_000, 5_000_000, n).astype(np.float64)
|
||||
amount = vol * close * 100.0
|
||||
dates = pd.bdate_range(end=pd.Timestamp.now().normalize(), periods=n)
|
||||
return pd.DataFrame(
|
||||
{
|
||||
"datetime": dates,
|
||||
"open": open_,
|
||||
"high": high,
|
||||
"low": low,
|
||||
"close": close,
|
||||
"vol": vol,
|
||||
"amount": amount,
|
||||
}
|
||||
)
|
||||
|
||||
|
||||
def _page_bars(full: pd.DataFrame, start: int, count: int) -> pd.DataFrame:
|
||||
"""按真实 /bars 分页语义切片：start=0 → 最新 count 根（页内升序）。"""
|
||||
n = len(full)
|
||||
lo = max(0, n - start - count)
|
||||
hi = n - start
|
||||
if hi <= 0 or lo >= n:
|
||||
return full.iloc[0:0]
|
||||
return full.iloc[lo:hi]
|
||||
|
||||
|
||||
def _quote_dict(mkt_enum: Any, code: str) -> dict[str, Any]:
|
||||
"""单标的五档快照（列集合对齐 quote_streamer._QUOTE_FIELDS 白名单）。"""
|
||||
closes = _synth_closes(market_enum_key(mkt_enum), code, 30)
|
||||
price = float(closes[-1])
|
||||
pre_close = float(closes[-2])
|
||||
rng = np.random.default_rng(_seed(market_enum_key(mkt_enum), code) ^ 0xBEEF)
|
||||
bid1 = round(price - 0.02, 2)
|
||||
ask1 = round(price + 0.02, 2)
|
||||
return {
|
||||
"market": mkt_enum,
|
||||
"code": code,
|
||||
"price": price,
|
||||
"pre_close": pre_close,
|
||||
"open": float(closes[-1]),
|
||||
"high": round(price * 1.01, 2),
|
||||
"low": round(price * 0.99, 2),
|
||||
"vol": float(rng.integers(10_000, 900_000)),
|
||||
"cur_vol": float(rng.integers(10, 900)),
|
||||
"amount": price * float(rng.integers(10_000, 900_000)) * 100.0,
|
||||
"s_vol": float(rng.integers(1000, 9000)),
|
||||
"b_vol": float(rng.integers(1000, 9000)),
|
||||
"rise_speed": round(float(rng.uniform(-1, 1)), 2),
|
||||
"limit_up": round(pre_close * 1.1, 2),
|
||||
"limit_down": round(pre_close * 0.9, 2),
|
||||
"decimal_point": 2,
|
||||
"server_time": "10:30:00",
|
||||
"trading_status": 0,
|
||||
**{f"bid{i}": round(bid1 - 0.01 * (i - 1), 2) for i in range(1, 6)},
|
||||
**{f"ask{i}": round(ask1 + 0.01 * (i - 1), 2) for i in range(1, 6)},
|
||||
**{f"bid_vol{i}": float(rng.integers(10, 500)) for i in range(1, 6)},
|
||||
**{f"ask_vol{i}": float(rng.integers(10, 500)) for i in range(1, 6)},
|
||||
}
|
||||
|
||||
|
||||
def market_enum_key(mkt_enum: Any) -> str:
|
||||
"""Market 枚举 → 种子用的字符串键（SZ/SH/BJ）。"""
|
||||
from easy_tdx.models.enums import Market
|
||||
|
||||
return {Market.SZ: "SZ", Market.SH: "SH", Market.BJ: "BJ"}.get(mkt_enum, str(mkt_enum))
|
||||
|
||||
|
||||
def _int_market_to_enum(value: int) -> Any:
|
||||
"""int 市场 → Market 枚举（MAC 客户端约定 int）。"""
|
||||
from easy_tdx.models.enums import Market
|
||||
|
||||
return {0: Market.SZ, 1: Market.SH, 2: Market.BJ}.get(int(value), Market.SZ)
|
||||
|
||||
|
||||
class MockTdxClient:
|
||||
"""AsyncTdxClient 的合成数据替身（覆盖 web 路由用到的方法）。"""
|
||||
|
||||
async def close(self) -> None:
|
||||
"""lifespan 关闭时调用（无真实连接，空操作）。"""
|
||||
|
||||
async def get_security_bars(
|
||||
self,
|
||||
market: Any,
|
||||
code: str,
|
||||
category: Any,
|
||||
start: int = 0,
|
||||
count: int = 800,
|
||||
*,
|
||||
bar_time: str = "start",
|
||||
) -> pd.DataFrame:
|
||||
"""个股 K 线（/bars 回退路径，MAC 可用时不会走到）。"""
|
||||
df = _page_bars(_synth_ohlcv(market_enum_key(market), code, _HISTORY_BARS), start, count)
|
||||
daily = _is_daily_category(category)
|
||||
return _bars_to_legacy_cols(df, daily)
|
||||
|
||||
async def get_index_bars(
|
||||
self,
|
||||
market: Any,
|
||||
code: str,
|
||||
category: Any,
|
||||
start: int = 0,
|
||||
count: int = 800,
|
||||
*,
|
||||
bar_time: str = "start",
|
||||
) -> pd.DataFrame:
|
||||
"""指数 K 线（/bars/index，看板迷你 K 线与情绪雷达数据源）。"""
|
||||
df = _page_bars(_synth_ohlcv(market_enum_key(market), code, _HISTORY_BARS), start, count)
|
||||
return _bars_to_legacy_cols(df, _is_daily_category(category))
|
||||
|
||||
async def get_minute_time_data(self, market: Any, code: str) -> pd.DataFrame:
|
||||
"""今日分时（240 点：价格围绕昨收随机游走 + 每分钟量）。"""
|
||||
rng = np.random.default_rng(_seed(market_enum_key(market), code) ^ 0xCAFE)
|
||||
pre_close = float(_synth_closes(market_enum_key(market), code, 30)[-2])
|
||||
prices = pre_close * np.cumprod(1.0 + rng.normal(0.0, 0.0015, 240))
|
||||
t0 = datetime.now().replace(hour=9, minute=30, second=0, microsecond=0)
|
||||
times = [t0 + timedelta(minutes=i) for i in range(240)]
|
||||
return pd.DataFrame(
|
||||
{
|
||||
"datetime": [t.strftime("%H:%M") for t in times],
|
||||
"price": prices,
|
||||
"vol": rng.integers(100, 9000, 240).astype(float),
|
||||
}
|
||||
)
|
||||
|
||||
async def get_security_quotes(self, stocks: list[tuple[Any, str]]) -> pd.DataFrame:
|
||||
"""批量五档快照（POST /quotes + QuoteStreamer SSE 共用）。"""
|
||||
return pd.DataFrame([_quote_dict(m, c) for m, c in stocks])
|
||||
|
||||
async def get_market_stat(self) -> pd.DataFrame:
|
||||
"""全市场涨跌统计（看板「市场统计」卡，单行 df）。"""
|
||||
rng = np.random.default_rng(20260901)
|
||||
up = int(rng.integers(1800, 2800))
|
||||
down = int(rng.integers(1800, 2800))
|
||||
return pd.DataFrame(
|
||||
[
|
||||
{
|
||||
"up_count": up,
|
||||
"down_count": down,
|
||||
"neutral_count": int(rng.integers(100, 300)),
|
||||
"suspended_count": int(rng.integers(10, 60)),
|
||||
"total_count": up + down + 300,
|
||||
"total_amount": float(rng.uniform(7e11, 1.1e12)),
|
||||
"total_volume": float(rng.uniform(6e11, 9e11)),
|
||||
"total_market_cap": float(rng.uniform(6e13, 8.5e13)),
|
||||
"limit_up_count": int(rng.integers(30, 80)),
|
||||
"limit_down_count": int(rng.integers(5, 40)),
|
||||
}
|
||||
]
|
||||
)
|
||||
|
||||
async def get_transaction_data(
|
||||
self, market: Any, code: str, start: int = 0, count: int = 800
|
||||
) -> pd.DataFrame:
|
||||
"""当日逐笔（个股弹窗用；简化为合成 tick 序列）。"""
|
||||
rng = np.random.default_rng(_seed(market_enum_key(market), code) ^ 0x7777)
|
||||
closes = _synth_closes(market_enum_key(market), code, 30)
|
||||
n = max(1, min(count, 200))
|
||||
return pd.DataFrame(
|
||||
{
|
||||
"time": [f"10:{i % 60:02d}" for i in range(n)],
|
||||
"price": closes[-1] * (1.0 + rng.normal(0.0, 0.002, n)),
|
||||
"vol": rng.integers(1, 500, n).astype(float),
|
||||
"buyorsell": rng.integers(0, 2, n).astype(int),
|
||||
}
|
||||
)
|
||||
|
||||
|
||||
class MockMacClient:
|
||||
"""AsyncMacClient 的合成数据替身（覆盖 web 路由用到的方法）。"""
|
||||
|
||||
async def close(self) -> None:
|
||||
"""lifespan 关闭时调用（无真实连接，空操作）。"""
|
||||
|
||||
async def get_stock_kline(
|
||||
self,
|
||||
market: Any,
|
||||
code: str,
|
||||
period: Any,
|
||||
start: int = 0,
|
||||
count: int = 800,
|
||||
times: int = 1,
|
||||
*,
|
||||
adjust: Any = None,
|
||||
bar_time: str = "start",
|
||||
) -> pd.DataFrame:
|
||||
"""个股 K 线（/bars 主路径）。market 为 int（MAC 协议约定）。
|
||||
|
||||
返回 MAC 契约列：datetime（含 00:00 时分）+ OHLC + vol/amount +
|
||||
float_shares（会被 bars 路由的 _normalize_mac_df 丢弃/规整）。
|
||||
"""
|
||||
df = _page_bars(
|
||||
_synth_ohlcv(market_enum_key(_int_market_to_enum(int(market))), code, _HISTORY_BARS),
|
||||
start,
|
||||
count,
|
||||
)
|
||||
out = df.copy()
|
||||
out["float_shares"] = 1.5e9
|
||||
return out
|
||||
|
||||
async def get_symbol_info(self, *, market: Any, code: str) -> pd.DataFrame:
|
||||
"""证券名称快照（/mac/symbol-info，自选补名用）。"""
|
||||
return pd.DataFrame(
|
||||
[{"market": int(market), "code": code, "name": _display_name(market, code)}]
|
||||
)
|
||||
|
||||
async def get_stock_quotes_list(
|
||||
self,
|
||||
*,
|
||||
category: Any = None,
|
||||
start: int = 0,
|
||||
count: int = 80,
|
||||
sort_type: Any = None,
|
||||
sort_order: Any = None,
|
||||
exclude_flags: Any = None,
|
||||
) -> pd.DataFrame:
|
||||
"""排行行情（/mac/quote-list，看板涨跌榜/分布懒加载）。
|
||||
|
||||
固定 40 只合成标的，按 close/pre_close 排序返回 count 根（封顶 200，
|
||||
避免分布懒加载的 3000 只请求生成过大 df）。
|
||||
"""
|
||||
rng = np.random.default_rng(0xE2E5)
|
||||
n = 40
|
||||
codes = [f"6{i:05d}" for i in range(n // 2)] + [f"0{i:05d}" for i in range(n - n // 2)]
|
||||
rows = []
|
||||
for i, code in enumerate(codes):
|
||||
closes = _synth_closes("SH" if code.startswith("6") else "SZ", code, 30)
|
||||
rows.append(
|
||||
{
|
||||
"market": 1 if code.startswith("6") else 0,
|
||||
"code": code,
|
||||
"name": _display_name("SH" if code.startswith("6") else "SZ", code),
|
||||
"close": float(closes[-1]),
|
||||
"pre_close": float(closes[-2]),
|
||||
"vol": float(rng.integers(10_000, 900_000)),
|
||||
"amount": float(closes[-1]) * float(rng.integers(10_000, 900_000)),
|
||||
"turnover_rate": round(float(rng.uniform(0.1, 25.0)), 2),
|
||||
}
|
||||
)
|
||||
df = pd.DataFrame(rows)
|
||||
df["_pct"] = df["close"] / df["pre_close"] - 1.0
|
||||
df = df.sort_values("_pct", ascending=(str(sort_order).upper() == "ASC"))
|
||||
df = df.drop(columns=["_pct"]).iloc[start : start + min(count, 200)]
|
||||
return df.reset_index(drop=True)
|
||||
|
||||
async def get_board_list(
|
||||
self, *, board_type: Any = None, count: int = 500, sort_column: Any = None
|
||||
) -> pd.DataFrame:
|
||||
"""板块列表（/board-mac/list，看板行业/概念热度榜）。"""
|
||||
rng = np.random.default_rng(0xB0AD)
|
||||
names = [
|
||||
"银行",
|
||||
"证券",
|
||||
"半导体",
|
||||
"白酒",
|
||||
"新能源车",
|
||||
"光伏",
|
||||
"军工",
|
||||
"医药",
|
||||
"房地产",
|
||||
"煤炭",
|
||||
"钢铁",
|
||||
"传媒",
|
||||
"计算机",
|
||||
"通信",
|
||||
"家电",
|
||||
"食品饮料",
|
||||
]
|
||||
rows = []
|
||||
for i, name in enumerate(names):
|
||||
closes = _synth_closes("BOARD", name, 30)
|
||||
rows.append(
|
||||
{
|
||||
"code": f"8810{i % 10}{i:02d}",
|
||||
"name": name,
|
||||
"price": float(closes[-1]),
|
||||
"pre_close": float(closes[-2]),
|
||||
"sort_value": float(rng.uniform(-5, 5)),
|
||||
}
|
||||
)
|
||||
df = pd.DataFrame(rows)
|
||||
df["_pct"] = df["price"] / df["pre_close"] - 1.0
|
||||
df = df.sort_values("_pct", ascending=False).drop(columns=["_pct"])
|
||||
return df.head(min(count, len(df))).reset_index(drop=True)
|
||||
|
||||
async def get_board_members(
|
||||
self, *, board_symbol: str, count: int = 100, sort_type: Any = None, sort_order: Any = None
|
||||
) -> pd.DataFrame:
|
||||
"""板块成分股（板块弹窗）。"""
|
||||
return await self.get_stock_quotes_list(
|
||||
count=count, sort_type=sort_type, sort_order=sort_order
|
||||
)
|
||||
|
||||
async def get_belong_board(self, *, market: Any, code: str) -> pd.DataFrame:
|
||||
"""个股所属板块（个股弹窗）。"""
|
||||
return pd.DataFrame(
|
||||
[
|
||||
{"code": "881001", "name": "银行"},
|
||||
{"code": "881101", "name": "上证主力"},
|
||||
]
|
||||
)
|
||||
|
||||
async def get_unusual(
|
||||
self, *, market: Any = None, start: int = 0, count: int = 50
|
||||
) -> pd.DataFrame:
|
||||
"""市场异动流（看板异动雷达）。"""
|
||||
rng = np.random.default_rng(_seed("UNUSUAL", str(market)) ^ 0x5EED)
|
||||
descs = ["火箭发射", "大笔买入", "封涨停板", "打开跌停板", "快速反弹", "有大买盘"]
|
||||
rows = []
|
||||
for i in range(min(count, 12)):
|
||||
mkt_int = int(market) if market is not None else 1
|
||||
prefix = "6" if mkt_int == 1 else "0" # SH→6 开头，SZ→0 开头
|
||||
code = f"{prefix}{int(rng.integers(0, 99999)):05d}"
|
||||
hh = 9 + int(i / 12 * 6)
|
||||
mm = int(rng.integers(0, 60))
|
||||
rows.append(
|
||||
{
|
||||
"time": f"{hh:02d}:{mm:02d}:{int(rng.integers(0, 60)):02d}",
|
||||
"code": code,
|
||||
"name": _display_name(market, code),
|
||||
"desc": str(rng.choice(descs)),
|
||||
"value": f"+{rng.uniform(2, 11):.1f}%",
|
||||
}
|
||||
)
|
||||
return pd.DataFrame(rows)
|
||||
|
||||
|
||||
# ── 内部辅助 ─────────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def _is_daily_category(category: Any) -> bool:
|
||||
"""日线及以上周期 → True（复用 bars 路由的判定口径）。"""
|
||||
from easy_tdx._df import _category_to_minutes
|
||||
|
||||
return _category_to_minutes(int(category)) is None
|
||||
|
||||
|
||||
def _bars_to_legacy_cols(df: pd.DataFrame, daily: bool) -> pd.DataFrame:
|
||||
"""把内部 datetime OHLCV 规整为旧 /bars 契约（日线 date / 分钟 datetime）。"""
|
||||
if df.empty:
|
||||
return df
|
||||
out = df.copy()
|
||||
col = "date" if daily else "datetime"
|
||||
if daily:
|
||||
out["datetime"] = pd.to_datetime(out["datetime"]).dt.strftime("%Y-%m-%d")
|
||||
else:
|
||||
out["datetime"] = pd.to_datetime(out["datetime"]).dt.strftime("%Y-%m-%d %H:%M:%S")
|
||||
return out.rename(columns={"datetime": col})
|
||||
|
||||
|
||||
def is_e2e_mock_enabled() -> bool:
|
||||
"""当前进程是否处于 E2E mock 模式。"""
|
||||
import os
|
||||
|
||||
return os.environ.get(E2E_MOCK_ENV) == "1"
|
||||
|
||||
|
||||
def log_mock_banner() -> None:
|
||||
"""serve 启动时打一行显式提示（避免误把 mock 数据当真实行情）。"""
|
||||
logger.warning(
|
||||
"[E2E-MOCK] EASY_TDX_E2E_MOCK=1 — 行情接口返回合成数据（仅限 Playwright E2E 使用）"
|
||||
)
|
||||
@@ -0,0 +1,170 @@
|
||||
"""E2E 合成数据源（web/e2e_mock.py）单元测试。
|
||||
|
||||
守护两件事：
|
||||
1. mock 客户端与真实客户端的**契约**（方法签名可用、返回列覆盖前端字段）；
|
||||
2. 数据的**确定性与分页语义**（E2E 断言可复现的前提）。
|
||||
|
||||
另有一个 TestClient 端到端用例：EASY_TDX_E2E_MOCK=1 下 /bars、/market/stat、
|
||||
/mac/quote-list 返回合成数据（不连真实服务器）。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import pandas as pd
|
||||
import pytest
|
||||
|
||||
from easy_tdx.models.enums import Market
|
||||
from easy_tdx.web.e2e_mock import (
|
||||
E2E_MOCK_ENV,
|
||||
MockMacClient,
|
||||
MockTdxClient,
|
||||
_page_bars,
|
||||
_synth_ohlcv,
|
||||
)
|
||||
|
||||
pytest.importorskip("fastapi")
|
||||
|
||||
|
||||
# ── 数据生成内核 ─────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_synth_ohlcv_deterministic() -> None:
|
||||
"""同一 (market, code) 两次生成结果逐位一致（E2E 断言可复现的前提）。"""
|
||||
a = _synth_ohlcv("SH", "600519", 300)
|
||||
b = _synth_ohlcv("SH", "600519", 300)
|
||||
pd.testing.assert_frame_equal(a, b)
|
||||
assert list(a.columns) == ["datetime", "open", "high", "low", "close", "vol", "amount"]
|
||||
|
||||
|
||||
def test_synth_ohlcv_differs_across_symbols() -> None:
|
||||
"""不同标的应有不同行情（避免看板五指数全长得一样）。"""
|
||||
a = _synth_ohlcv("SH", "000001", 100)["close"].iloc[-1]
|
||||
b = _synth_ohlcv("SZ", "000001", 100)["close"].iloc[-1]
|
||||
assert a != b
|
||||
|
||||
|
||||
def test_page_bars_newest_first_page() -> None:
|
||||
"""分页语义与真实 /bars 一致：start=0 取最新 count 根，页内升序。"""
|
||||
df = _synth_ohlcv("SH", "600519", 1000)
|
||||
page0 = _page_bars(df, 0, 800)
|
||||
assert len(page0) == 800
|
||||
assert page0["datetime"].iloc[-1] == df["datetime"].iloc[-1] # 最新一根在页尾
|
||||
assert page0["datetime"].is_monotonic_increasing
|
||||
|
||||
page1 = _page_bars(df, 800, 800)
|
||||
assert len(page1) == 200
|
||||
assert page1["datetime"].iloc[-1] < page0["datetime"].iloc[0] # 更早一段
|
||||
|
||||
assert len(_page_bars(df, 5000, 800)) == 0 # 越界翻页返回空
|
||||
|
||||
|
||||
# ── Mock 客户端契约 ──────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
async def test_mock_tdx_quotes_contract() -> None:
|
||||
"""quotes df：market 列是 Market 枚举（QuoteStreamer._df_to_dicts 依赖）、
|
||||
字段覆盖 SSE 白名单（前端行情表 + 看板指数卡）。"""
|
||||
client = MockTdxClient()
|
||||
df = await client.get_security_quotes([(Market.SH, "000001"), (Market.SZ, "000001")])
|
||||
assert len(df) == 2
|
||||
# pandas 会把 IntEnum 列统一为 int64（真实客户端同样如此）；
|
||||
# QuoteStreamer._df_to_dicts 依赖 IntEnum 哈希相等完成 int → "SH" 映射
|
||||
assert df["market"].iloc[0] == Market.SH
|
||||
from easy_tdx.web.quote_streamer import _MARKET_NAMES
|
||||
|
||||
assert _MARKET_NAMES.get(df["market"].iloc[0]) == "SH"
|
||||
for col in ("price", "pre_close", "open", "high", "low", "vol", "amount", "bid1", "ask_vol5"):
|
||||
assert col in df.columns
|
||||
# 指数与个股同名代码（SH000001 上证指数 / SZ000001 平安银行）行情不同
|
||||
assert df["price"].iloc[0] != df["price"].iloc[1]
|
||||
|
||||
|
||||
async def test_mock_tdx_bars_daily_date_column() -> None:
|
||||
"""日线返回 date 列（旧 /bars 契约），分页 start/count 生效。"""
|
||||
client = MockTdxClient()
|
||||
df = await client.get_security_bars(Market.SH, "600519", 4, 0, 50) # 4 = DAY
|
||||
assert "date" in df.columns and "datetime" not in df.columns
|
||||
assert len(df) == 50
|
||||
assert df["date"].is_monotonic_increasing
|
||||
|
||||
|
||||
async def test_mock_tdx_minute_and_stat() -> None:
|
||||
"""分时 240 点 + 市场统计单行（看板两块数据源）。"""
|
||||
client = MockTdxClient()
|
||||
minute = await client.get_minute_time_data(Market.SH, "000001")
|
||||
assert len(minute) == 240
|
||||
assert {"datetime", "price", "vol"} <= set(minute.columns)
|
||||
|
||||
stat = await client.get_market_stat()
|
||||
assert len(stat) == 1
|
||||
for col in ("up_count", "down_count", "total_count", "total_amount"):
|
||||
assert col in stat.columns
|
||||
|
||||
|
||||
async def test_mock_mac_kline_contract() -> None:
|
||||
"""MAC get_stock_kline：datetime 列 + float_shares（bars 路由规整依赖）。"""
|
||||
client = MockMacClient()
|
||||
df = await client.get_stock_kline(1, "600519", 4, 0, 30, 1, adjust=None)
|
||||
assert "datetime" in df.columns
|
||||
assert "float_shares" in df.columns
|
||||
assert len(df) == 30
|
||||
|
||||
|
||||
async def test_mock_mac_quote_list_sort_and_columns() -> None:
|
||||
"""排行行情：涨跌幅排序生效、列覆盖前端 RankRow 渲染需求。"""
|
||||
client = MockMacClient()
|
||||
desc = await client.get_stock_quotes_list(count=20, sort_order="DESC")
|
||||
asc = await client.get_stock_quotes_list(count=20, sort_order="ASC")
|
||||
assert len(desc) == 20
|
||||
for col in ("market", "code", "name", "close", "pre_close", "amount"):
|
||||
assert col in desc.columns
|
||||
d_pct = desc["close"] / desc["pre_close"]
|
||||
a_pct = asc["close"] / asc["pre_close"]
|
||||
assert d_pct.iloc[0] >= d_pct.iloc[-1]
|
||||
assert a_pct.iloc[0] <= a_pct.iloc[-1]
|
||||
|
||||
|
||||
async def test_mock_mac_board_and_unusual() -> None:
|
||||
"""板块列表/异动流：非空、字段齐（看板热度榜与异动雷达）。"""
|
||||
client = MockMacClient()
|
||||
boards = await client.get_board_list(count=500)
|
||||
assert len(boards) > 0
|
||||
assert {"code", "name", "price", "pre_close"} <= set(boards.columns)
|
||||
|
||||
unusual = await client.get_unusual(market=1, count=60)
|
||||
assert 0 < len(unusual) <= 12
|
||||
assert {"time", "code", "name", "desc", "value"} <= set(unusual.columns)
|
||||
|
||||
|
||||
async def test_mock_close_is_noop() -> None:
|
||||
"""lifespan 关闭路径调用 close() 不抛异常。"""
|
||||
await MockTdxClient().close()
|
||||
await MockMacClient().close()
|
||||
|
||||
|
||||
# ── TestClient 端到端（mock 模式 lifespan）───────────────────────────────────
|
||||
|
||||
|
||||
def test_app_serves_synthetic_data_in_mock_mode(monkeypatch: pytest.MonkeyPatch) -> None:
|
||||
"""EASY_TDX_E2E_MOCK=1 时全应用 lifespan 用合成客户端，行情端点 200。"""
|
||||
from fastapi.testclient import TestClient
|
||||
|
||||
from easy_tdx.web import create_app
|
||||
|
||||
monkeypatch.setenv(E2E_MOCK_ENV, "1")
|
||||
app = create_app()
|
||||
with TestClient(app) as client:
|
||||
bars = client.get(
|
||||
"/api/v1/bars",
|
||||
params={"market": "SH", "code": "600519", "category": "DAY", "count": 30},
|
||||
)
|
||||
assert bars.status_code == 200
|
||||
assert len(bars.json()["data"]) == 30
|
||||
|
||||
stat = client.get("/api/v1/market/stat")
|
||||
assert stat.status_code == 200
|
||||
assert stat.json()["data"][0]["up_count"] > 0
|
||||
|
||||
rank = client.get("/api/v1/mac/quote-list", params={"count": 10})
|
||||
assert rank.status_code == 200
|
||||
assert len(rank.json()["data"]) == 10
|
||||
@@ -0,0 +1,57 @@
|
||||
# easy-tdx Web UI — Playwright E2E
|
||||
|
||||
无头浏览器端到端测试，覆盖：市场看板（五大指数 SSE）、自选增删、回测全流程
|
||||
（取行情→净值图→绩效表→成交记录）、「附加分析」开关（WF 逐窗柱状图 + 一条龙
|
||||
评估卡）、策略库保存。
|
||||
|
||||
## Mock 方案：后端合成数据（EASY_TDX_E2E_MOCK=1），不是 page.route 拦截
|
||||
|
||||
两种可行路径的取舍：
|
||||
|
||||
| | 后端 mock（已选） | Playwright `page.route` 拦截 |
|
||||
|---|---|---|
|
||||
| 回测/WF/评估/自选/策略库 | **走真实后端代码**，schema 变更会被 E2E 捕获 | 静态 JSON，会与后端 schema 漂移 |
|
||||
| SSE `/stream/quotes`（EventSource） | QuoteStreamer 真轮询合成数据，SSE 全链路被覆盖 | 无法稳定 mock（需流式 body） |
|
||||
| 任务型端点（提交→轮询→done） | 天然支持 | 要手写状态机 |
|
||||
| 代价 | 后端多一个 `src/easy_tdx/web/e2e_mock.py`（约 400 行，由单测守护契约） | 无后端改动 |
|
||||
|
||||
实现：`playwright.config.ts` 的 `webServer` 以 `EASY_TDX_E2E_MOCK=1` 启动
|
||||
`easy-tdx serve --port 8001`，lifespan 把 TDX/MAC 客户端替换为合成数据客户端
|
||||
（确定性随机游走、按 (market, code) 播种，逐轮结果完全一致）。
|
||||
`EASY_TDX_CONFIG_DIR` 指向每轮独立的临时目录——自选/策略库/任务从空开始，
|
||||
断言可以写死，也不污染真实 `~/.easy_tdx`。
|
||||
|
||||
## 本地跑法
|
||||
|
||||
```bash
|
||||
# 仓库根（Python 侧，一次性）
|
||||
pip install -e ".[web]" # fastapi + uvicorn
|
||||
|
||||
cd web-ui
|
||||
npm install
|
||||
npx playwright install chromium # 首次下载浏览器（约 115MB）
|
||||
npm run build # 必须：serve 从 ../web-ui/dist 托管前端
|
||||
npm run test:e2e # = npx playwright test（无头）
|
||||
```
|
||||
|
||||
- Python 解释器自动探测仓库 `.venv`；没有 `.venv` 时用 `EASY_TDX_PYTHON`
|
||||
环境变量指定（CI 里是系统 `python`）。
|
||||
- 调试：`npx playwright test --headed`，或 `--ui` 打开交互式运行器；
|
||||
失败时自动留 trace/截图在 `e2e/.results/`（已 gitignore）。
|
||||
- 想复用已启动的 serve：直接跑即可（`reuseExistingServer`，本地非 CI 默认开），
|
||||
但注意该 serve 必须带 `EASY_TDX_E2E_MOCK=1` 才有合成行情。
|
||||
|
||||
## CI
|
||||
|
||||
`.github/workflows/ci.yml` 的 `frontend` job 在 typecheck+build 后追加：
|
||||
安装 Python + `pip install -e ".[web]"` → `npx playwright install chromium` →
|
||||
`npm run test:e2e`（mock 模式，不需要任何真实行情连接）。
|
||||
|
||||
## 用例清单
|
||||
|
||||
| 文件 | 覆盖 |
|
||||
|---|---|
|
||||
| `dashboard.spec.ts` | 五大指数区块渲染 + SSE 首帧价格 + 市场统计卡 |
|
||||
| `watchlist.spec.ts` | 自选加入（含名称补全）/删除/空态 |
|
||||
| `backtest.spec.ts` | 策略下拉 + 回测全流程 + WF 柱状图 + 一条龙评估卡 |
|
||||
| `strategies.spec.ts` | 保存策略对话框 + 策略库页可见 |
|
||||
@@ -0,0 +1,54 @@
|
||||
// 回测页 E2E：选策略 → 开始回测（自动取行情）→ 净值图 + 绩效表 + 成交记录。
|
||||
//
|
||||
// 行情来自 mock /bars（确定性合成 OHLCV），回测跑真实引擎；
|
||||
// URL query 指定较短日期区间加快取数（页面 onMounted 回填 startDate/endDate）。
|
||||
|
||||
import { expect, test } from '@playwright/test'
|
||||
|
||||
test('回测全流程出净值图与绩效表', async ({ page }) => {
|
||||
await page.goto('/backtest?startDate=2024-01-01&endDate=2025-12-31')
|
||||
|
||||
// 策略下拉加载出内置策略，默认 ma_cross
|
||||
const strategySelect = page.locator('.strategy-picker select')
|
||||
await expect(strategySelect).toHaveValue('ma_cross')
|
||||
const optionCount = await strategySelect.locator('option').count()
|
||||
expect(optionCount).toBeGreaterThanOrEqual(18)
|
||||
|
||||
// 取行情（mock /bars）+ 回测（真实引擎）
|
||||
await page.getByRole('button', { name: '开始回测' }).click()
|
||||
|
||||
// 报告区：净值曲线（echarts canvas）+ 绩效指标 + 成交记录
|
||||
await expect(page.getByRole('heading', { name: '净值曲线与回撤' })).toBeVisible({ timeout: 60_000 })
|
||||
await expect(page.locator('.report-section canvas').first()).toBeVisible()
|
||||
await expect(page.getByRole('heading', { name: '绩效指标' })).toBeVisible()
|
||||
await expect(page.getByRole('heading', { name: /成交记录（\d+ 笔）/ })).toBeVisible()
|
||||
|
||||
// 绩效表渲染出具体数值（总收益/夏普等指标行）
|
||||
const perfSection = page.locator('.report-section', { hasText: '绩效指标' })
|
||||
await expect(perfSection.locator('td, .metric-value, .mono').first()).toBeVisible()
|
||||
})
|
||||
|
||||
test('勾选附加分析后出现 WF 逐窗柱状图与一条龙评估卡', async ({ page }) => {
|
||||
await page.goto('/backtest?startDate=2023-01-01&endDate=2025-12-31')
|
||||
|
||||
// 勾选两个「附加分析」开关（v1.27 新增）
|
||||
await page.getByLabel('Walk-Forward 样本外验证').check()
|
||||
await expect(page.getByLabel('一条龙评估')).toBeVisible()
|
||||
await page.getByLabel('一条龙评估').check()
|
||||
|
||||
await page.getByRole('button', { name: '开始回测' }).click()
|
||||
|
||||
// WF：先出现「验证中…」区块，随后逐窗柱状图（echarts canvas）+ 稳定性汇总
|
||||
await expect(page.getByRole('heading', { name: 'Walk-Forward 样本外验证' })).toBeVisible({
|
||||
timeout: 60_000,
|
||||
})
|
||||
await expect(page.locator('.wf-chart canvas')).toBeVisible({ timeout: 120_000 })
|
||||
await expect(page.getByText('盈利窗占比', { exact: true })).toBeVisible()
|
||||
await expect(page.locator('.wf-summary .stat')).toHaveCount(6)
|
||||
|
||||
// 一条龙评估：综合评分 + 高适配徽标 + 基准对比
|
||||
await expect(page.locator('.eval-panel')).toBeVisible({ timeout: 120_000 })
|
||||
await expect(page.getByText('综合评分')).toBeVisible()
|
||||
await expect(page.getByText('对比买入持有')).toBeVisible()
|
||||
await expect(page.getByText(/适配性体检 \d+\/\d+/)).toBeVisible()
|
||||
})
|
||||
@@ -0,0 +1,23 @@
|
||||
// 看板 E2E：五大指数区块加载 + SSE 合成行情到达后价格渲染。
|
||||
//
|
||||
// 数据链路：QuoteStreamer 轮询 mock 客户端 → SSE /stream/quotes →
|
||||
// quoteStore → .idx-card。首帧在打开页面后 1~3 秒内到达（轮询循环
|
||||
// 「无订阅 1s 待命 → 有订阅立即拉一轮」），盘外时段也不受影响。
|
||||
|
||||
import { expect, test } from '@playwright/test'
|
||||
|
||||
test('市场看板加载五大指数区块并渲染实时价格', async ({ page }) => {
|
||||
await page.goto('/')
|
||||
|
||||
const cards = page.locator('.idx-card')
|
||||
await expect(cards).toHaveCount(5)
|
||||
|
||||
const names = cards.locator('.idx-name')
|
||||
await expect(names).toHaveText(['上证指数', '深证成指', '创业板指', '科创50', '沪深300'])
|
||||
|
||||
// SSE 首帧到达前价格是占位符「—」；合成行情到达后变为数值
|
||||
await expect(cards.first().locator('.idx-price')).toHaveText(/\d/, { timeout: 30_000 })
|
||||
|
||||
// 市场统计卡也从 mock /market/stat 拿到数据（不再是「加载中…」）
|
||||
await expect(page.locator('.card', { hasText: '市场统计' }).locator('.stat-nums')).toBeVisible()
|
||||
})
|
||||
@@ -0,0 +1,25 @@
|
||||
// 策略库 E2E：回测出结果 → 保存策略（含成绩快照）→ 策略库页可见。
|
||||
|
||||
import { expect, test } from '@playwright/test'
|
||||
|
||||
test('回测结果保存到策略库并在策略库页可见', async ({ page }) => {
|
||||
await page.goto('/backtest?startDate=2024-01-01&endDate=2025-12-31')
|
||||
|
||||
// 跑一次回测拿到结果（保存按钮只在有结果时出现）
|
||||
await page.getByRole('button', { name: '开始回测' }).click()
|
||||
await expect(page.getByRole('button', { name: '💾 保存策略' })).toBeVisible({ timeout: 60_000 })
|
||||
|
||||
// 打开保存对话框（名称已预填「双均线交叉 · 000001」）
|
||||
await page.getByRole('button', { name: '💾 保存策略' }).click()
|
||||
await expect(page.locator('.modal')).toBeVisible()
|
||||
const nameInput = page.getByPlaceholder('给这个策略起个名')
|
||||
await expect(nameInput).toHaveValue('双均线交叉 · 000001')
|
||||
await nameInput.fill('E2E 冒烟策略')
|
||||
|
||||
await page.locator('.modal-actions .primary').click()
|
||||
await expect(page.getByText('✓ 已保存到策略库')).toBeVisible()
|
||||
|
||||
// 策略库页列出刚保存的条目（SQLite strategies.db 落在临时 EASY_TDX_CONFIG_DIR）
|
||||
await page.goto('/strategies')
|
||||
await expect(page.getByText('E2E 冒烟策略').first()).toBeVisible({ timeout: 30_000 })
|
||||
})
|
||||
@@ -0,0 +1,24 @@
|
||||
// 自选页 E2E：加入自选（行情校验 + 名称补全走 mock）→ 表格出现 → 删除 → 消失。
|
||||
//
|
||||
// 每轮 E2E 用独立的临时 EASY_TDX_CONFIG_DIR，自选从空开始，断言可写死。
|
||||
|
||||
import { expect, test } from '@playwright/test'
|
||||
|
||||
test('自选页增删自选', async ({ page }) => {
|
||||
await page.goto('/watchlist')
|
||||
|
||||
// 初始为空（临时配置目录）
|
||||
await expect(page.locator('.empty-row')).toBeVisible()
|
||||
|
||||
// 加入 600519（市场自动识别 SH；名称走 mock /mac/symbol-info → 贵州茅台）
|
||||
await page.fill('.code-input', '600519')
|
||||
await page.getByRole('button', { name: '加入自选' }).click()
|
||||
await expect(page.locator('.data-row')).toHaveCount(1, { timeout: 30_000 })
|
||||
await expect(page.locator('.data-row .cell-name')).toHaveText('贵州茅台')
|
||||
await expect(page.locator('.data-row .cell-code')).toHaveText('SH600519')
|
||||
|
||||
// 删除后表格回到空态
|
||||
await page.locator('.data-row .del').first().click()
|
||||
await expect(page.locator('.data-row')).toHaveCount(0)
|
||||
await expect(page.locator('.empty-row')).toBeVisible()
|
||||
})
|
||||
Generated
+64
@@ -14,6 +14,7 @@
|
||||
"vue-router": "^4.6.4"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@playwright/test": "^1.62.1",
|
||||
"@types/node": "^24.13.2",
|
||||
"@vitejs/plugin-vue": "^6.0.7",
|
||||
"@vue/tsconfig": "^0.9.1",
|
||||
@@ -137,6 +138,22 @@
|
||||
"url": "https://github.com/sponsors/Boshen"
|
||||
}
|
||||
},
|
||||
"node_modules/@playwright/test": {
|
||||
"version": "1.62.1",
|
||||
"resolved": "https://registry.npmjs.org/@playwright/test/-/test-1.62.1.tgz",
|
||||
"integrity": "sha512-DTcUc8qii+cpHvtOwggMtBRMjKZHXYWdw8syRYu2vtzuq4Wxphqq4NfCs5Zt44L6mA8rfDfj+PHnxFc/FeK6mQ==",
|
||||
"dev": true,
|
||||
"license": "Apache-2.0",
|
||||
"dependencies": {
|
||||
"playwright": "1.62.1"
|
||||
},
|
||||
"bin": {
|
||||
"playwright": "cli.js"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=20"
|
||||
}
|
||||
},
|
||||
"node_modules/@rolldown/binding-android-arm64": {
|
||||
"version": "1.1.4",
|
||||
"resolved": "https://registry.npmjs.org/@rolldown/binding-android-arm64/-/binding-android-arm64-1.1.4.tgz",
|
||||
@@ -1122,6 +1139,53 @@
|
||||
}
|
||||
}
|
||||
},
|
||||
"node_modules/playwright": {
|
||||
"version": "1.62.1",
|
||||
"resolved": "https://registry.npmjs.org/playwright/-/playwright-1.62.1.tgz",
|
||||
"integrity": "sha512-0M+L3LAD8/nm554LOla9Ayx0j0tmFZ0FBcoQ7F1VuVHpM/XpiC8RcDzBQB8W5+hA8L22THxELzeF+2WcUzvcLg==",
|
||||
"dev": true,
|
||||
"license": "Apache-2.0",
|
||||
"dependencies": {
|
||||
"playwright-core": "1.62.1"
|
||||
},
|
||||
"bin": {
|
||||
"playwright": "cli.js"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=20"
|
||||
},
|
||||
"optionalDependencies": {
|
||||
"fsevents": "2.3.2"
|
||||
}
|
||||
},
|
||||
"node_modules/playwright-core": {
|
||||
"version": "1.62.1",
|
||||
"resolved": "https://registry.npmjs.org/playwright-core/-/playwright-core-1.62.1.tgz",
|
||||
"integrity": "sha512-wPYSwEBJY9GHraISXqyqtx0na0LpO3XEX7jNDhntbex7tzUS7kLnZsOlFruFJB4Hi/rhDMjXGqHewDZ68nYZVw==",
|
||||
"dev": true,
|
||||
"license": "Apache-2.0",
|
||||
"bin": {
|
||||
"playwright-core": "cli.js"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=20"
|
||||
}
|
||||
},
|
||||
"node_modules/playwright/node_modules/fsevents": {
|
||||
"version": "2.3.2",
|
||||
"resolved": "https://registry.npmjs.org/fsevents/-/fsevents-2.3.2.tgz",
|
||||
"integrity": "sha512-xiqMQR4xAeHTuB9uWm+fFRcIOgKBMiOBP+eXiyT7jsgVCq1bkVygt00oASowB7EdtpOHaaPgKt812P9ab+DDKA==",
|
||||
"dev": true,
|
||||
"hasInstallScript": true,
|
||||
"license": "MIT",
|
||||
"optional": true,
|
||||
"os": [
|
||||
"darwin"
|
||||
],
|
||||
"engines": {
|
||||
"node": "^8.16.0 || ^10.6.0 || >=11.0.0"
|
||||
}
|
||||
},
|
||||
"node_modules/postcss": {
|
||||
"version": "8.5.26",
|
||||
"resolved": "https://registry.npmjs.org/postcss/-/postcss-8.5.26.tgz",
|
||||
|
||||
+3
-1
@@ -6,7 +6,8 @@
|
||||
"scripts": {
|
||||
"dev": "vite",
|
||||
"build": "vue-tsc -b && vite build",
|
||||
"preview": "vite preview"
|
||||
"preview": "vite preview",
|
||||
"test:e2e": "playwright test"
|
||||
},
|
||||
"dependencies": {
|
||||
"echarts": "^6.1.0",
|
||||
@@ -15,6 +16,7 @@
|
||||
"vue-router": "^4.6.4"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@playwright/test": "^1.62.1",
|
||||
"@types/node": "^24.13.2",
|
||||
"@vitejs/plugin-vue": "^6.0.7",
|
||||
"@vue/tsconfig": "^0.9.1",
|
||||
|
||||
@@ -0,0 +1,70 @@
|
||||
// Playwright E2E 配置：mock 模式的 easy-tdx serve + 已构建的前端 dist。
|
||||
//
|
||||
// 运行前置：
|
||||
// 1. `npm run build`（serve 从仓库根 web-ui/dist 托管前端，SPA fallback）；
|
||||
// 2. 后端可用（仓库根 `pip install -e ".[web]"`）——自动探测仓库 .venv，
|
||||
// 否则可用 EASY_TDX_PYTHON 指定解释器（CI 里是 `python`）。
|
||||
//
|
||||
// 行情全部来自合成数据（EASY_TDX_E2E_MOCK=1，见 src/easy_tdx/web/e2e_mock.py），
|
||||
// 不连真实通达信服务器、不受交易时段限制；回测/WF/评估/自选/策略库走真实后端。
|
||||
// 详见 e2e/README.md。
|
||||
|
||||
import { existsSync, mkdtempSync } from 'node:fs'
|
||||
import { tmpdir } from 'node:os'
|
||||
import path from 'node:path'
|
||||
import { fileURLToPath } from 'node:url'
|
||||
|
||||
import { defineConfig } from '@playwright/test'
|
||||
|
||||
const PORT = Number(process.env.E2E_PORT ?? 8001)
|
||||
const BASE_URL = `http://127.0.0.1:${PORT}`
|
||||
const WEB_UI_DIR = path.dirname(fileURLToPath(import.meta.url))
|
||||
|
||||
/** 启动 serve 的 Python 解释器：优先仓库 .venv（开发态 editable 安装），
|
||||
* 没有则回退 EASY_TDX_PYTHON / 系统 python（CI 态 pip install -e 之后）。 */
|
||||
function resolvePython(): string {
|
||||
const repoRoot = path.resolve(WEB_UI_DIR, '..')
|
||||
if (existsSync(path.join(repoRoot, '.venv/Scripts/python.exe'))) {
|
||||
return path.join(repoRoot, '.venv/Scripts/python.exe')
|
||||
}
|
||||
if (existsSync(path.join(repoRoot, '.venv/bin/python'))) {
|
||||
return path.join(repoRoot, '.venv/bin/python')
|
||||
}
|
||||
return process.env.EASY_TDX_PYTHON ?? 'python'
|
||||
}
|
||||
|
||||
// 每次运行独立的临时配置目录：watchlist.db / strategies.db / tasks.db 写在这里，
|
||||
// 不污染真实 ~/.easy_tdx，且每轮 E2E 从空自选、空策略库开始（断言可写死）。
|
||||
const RUNTIME_CONFIG_DIR = mkdtempSync(path.join(tmpdir(), 'easy-tdx-e2e-'))
|
||||
|
||||
export default defineConfig({
|
||||
testDir: './e2e',
|
||||
timeout: 180_000,
|
||||
// 单 worker 串行：全部用例共享同一个 serve（SQLite 自选/策略库会互相干扰）
|
||||
workers: 1,
|
||||
fullyParallel: false,
|
||||
retries: process.env.CI ? 1 : 0,
|
||||
reporter: [['list']],
|
||||
use: {
|
||||
baseURL: BASE_URL,
|
||||
headless: true,
|
||||
locale: 'zh-CN',
|
||||
trace: 'retain-on-failure',
|
||||
screenshot: 'only-on-failure',
|
||||
actionTimeout: 15_000,
|
||||
},
|
||||
expect: {
|
||||
timeout: 20_000,
|
||||
},
|
||||
outputDir: './e2e/.results',
|
||||
webServer: {
|
||||
command: `${resolvePython()} -m easy_tdx serve --host 127.0.0.1 --port ${PORT} --no-open-browser`,
|
||||
url: `${BASE_URL}/api/v1/backtest/strategies`,
|
||||
reuseExistingServer: !process.env.CI,
|
||||
timeout: 120_000,
|
||||
env: {
|
||||
EASY_TDX_E2E_MOCK: '1',
|
||||
EASY_TDX_CONFIG_DIR: RUNTIME_CONFIG_DIR,
|
||||
},
|
||||
},
|
||||
})
|
||||
Reference in New Issue
Block a user