release: v1.27.0 — 通达信公式解析器三通道 + 轮动组合引擎 + 回测页WF/评估开关 + Docker 部署

升级计划 P3 + P4（部分）。全量 1252 单测、ruff/mypy strict、前端 vue-tsc+vite build 全绿。 - 通达信公式解析器（formula.py）：自建 tokenizer + 递归下降 AST + 30+ 函数白名单求值（不走 Python eval）；命名布尔输出=信号列、数值输出=排名列；除零→NaN、预热期不出信号 - 公式三通道：CLI easy-tdx formula compute|screen|backtest；REST /formula/validate|compute| backtest|screen（run/async）；Python API run_formula_backtest（买/卖列自动挑选） - 轮动组合引擎（rotation.py）：排名定期换仓（打分只用截至当日数据）、槽位等额、跌出排名自动补位、日/周/月刷新、槽内止盈止损；momentum_score/formula_score 打分； REST /backtest/rotation/run/async - 回测页附加分析开关（Web UI）：勾选后随回测并行跑 WF（逐窗红涨绿跌柱状图+汇总卡，窗口数 2~12）与一条龙评估（评分分项条/高适配徽标/买入持有对比/8 项适配检查）；新增 WalkForwardPanel/EvaluatePanel 组件与 store runWalkforward/runEvaluate； WF 端点 ?n_windows= 透传；修复报告 numpy 标量 REST 400（源头清洗） - Docker 部署（Dockerfile + docker-compose.yml，/data 卷 + 健康检查）与 scripts/verify_ci.sh 一键门禁 - 升级计划文档 docs/upgrade-plan-2026H2.md（四阶段全部完成 + 诚实实测数据） - 未做（独立排期）：Playwright E2E、WebSocket 实时联动、引擎逐 bar 向量化
2026-09-12 15:44:18 +08:00 · 2026-09-01 22:17:57 +08:00
parent 9569b2653c
commit 917295edaf
23 changed files with 3135 additions and 5 deletions
@@ -0,0 +1,193 @@
+"""公式回测适配器 + REST 端点测试（三通道一致性）。"""
+
+from __future__ import annotations
+
+import time
+
+import numpy as np
+import pandas as pd
+import pytest
+
+pytest.importorskip("fastapi")
+
+from fastapi.testclient import TestClient  # noqa: E402
+
+from easy_tdx.backtest.formula_strategy import (  # noqa: E402
+    FormulaStrategyError,
+    attach_formula_columns,
+    pick_signal_columns,
+    run_formula_backtest,
+)
+from easy_tdx.formula import compile_formula  # noqa: E402
+
+
+def _df(n: int = 300, seed: int = 3, drift: float = 0.002) -> pd.DataFrame:
+    rng = np.random.default_rng(seed)
+    close = 10.0 * np.cumprod(1.0 + drift + rng.normal(0, 0.012, n))
+    return pd.DataFrame(
+        {
+            "datetime": pd.date_range("2024-01-01", periods=n, freq="B"),
+            "open": close * 0.999,
+            "high": close * 1.02,
+            "low": close * 0.98,
+            "close": close,
+            "vol": 1e6,
+            "amount": close * 1e6,
+        }
+    )
+
+
+_MA_CROSS = "快: MA(C, 5);\n慢: MA(C, 20);\n买入: CROSS(快, 慢);\n卖出: CROSS(慢, 快);"
+
+
+# ── attach / pick ─────────────────────────────────────────────────────────────
+
+
+def test_attach_formula_columns():
+    df = _df(100)
+    enriched, result = attach_formula_columns(df, compile_formula(_MA_CROSS))
+    assert {"快", "慢", "买入", "卖出"} <= set(enriched.columns)
+    assert len(enriched) == len(df)
+    assert df is not enriched  # 副本，不污染原 df
+
+
+def test_pick_signal_columns_by_hint_and_order():
+    _, result = attach_formula_columns(_df(60), compile_formula(_MA_CROSS))
+    buy, sell = pick_signal_columns(result)
+    assert (buy, sell) == ("买入", "卖出")  # 名称提示（买/卖）优先
+
+    _, r2 = attach_formula_columns(_df(60), compile_formula("A: C > MA(C, 5); B: C < MA(C, 5);"))
+    buy2, sell2 = pick_signal_columns(r2)
+    assert (buy2, sell2) == ("A", "B")  # 无提示时按声明顺序
+
+    buy3, _ = pick_signal_columns(r2, buy_col="B")
+    assert buy3 == "B"  # 显式指定优先
+
+
+def test_pick_requires_signal():
+    from easy_tdx.formula import FormulaResult
+
+    result = FormulaResult(columns={"x": np.ones(5)}, values=["x"])
+    with pytest.raises(FormulaStrategyError, match="布尔信号"):
+        pick_signal_columns(result)
+
+
+# ── run_formula_backtest ──────────────────────────────────────────────────────
+
+
+def test_run_formula_backtest_full_report():
+    out = run_formula_backtest(_df(300), _MA_CROSS)
+    assert out["performance"]["total_trades"] >= 1
+    assert out["formula"]["buy_col"] == "买入"
+    assert out["formula"]["sell_col"] == "卖出"
+    assert out["grade"]["grade"] in ("S", "A", "B", "C", "D")
+    assert 0 <= out["score"]["total"] <= 100
+    assert "trades" in out and "equity_curve" in out
+
+
+def test_run_formula_backtest_no_sell_col_holds():
+    """只有买入列 → 买入后持有到末尾（1 笔完成交易=0 卖出，持仓中）。"""
+    out = run_formula_backtest(_df(200, drift=0.004), "买入: CROSS(MA(C,3), MA(C,30));")
+    assert out["formula"]["sell_col"] is None
+    assert out["performance"]["total_return"] > 0
+
+
+def test_run_formula_backtest_accepts_compiled():
+    compiled = compile_formula(_MA_CROSS)
+    out = run_formula_backtest(_df(200), compiled)
+    assert out["formula"]["buy_col"] == "买入"
+
+
+def test_run_formula_backtest_rejects_no_signal():
+    with pytest.raises(ValueError, match="布尔信号"):
+        run_formula_backtest(_df(60), "数值: MA(C, 5);")
+
+
+def test_run_formula_backtest_json_serializable():
+    import json
+
+    out = run_formula_backtest(_df(150), _MA_CROSS)
+    json.dumps(out, default=str)
+
+
+# ── REST 端点 ─────────────────────────────────────────────────────────────────
+
+
+def _client() -> TestClient:
+    from easy_tdx.web import create_app
+
+    return TestClient(create_app())
+
+
+def _ohlcv(n: int = 200) -> list[dict[str, object]]:
+    df = _df(n)
+    df["datetime"] = df["datetime"].dt.strftime("%Y-%m-%d")
+    return json_records(df)
+
+
+def json_records(df: pd.DataFrame) -> list[dict[str, object]]:
+    import json
+
+    return json.loads(df.to_json(orient="records", force_ascii=False))
+
+
+def test_rest_formula_validate_ok_and_error():
+    client = _client()
+    r = client.post(
+        "/api/v1/formula/validate", json={"text": "金叉: CROSS(MA(C,5), MA(C,20)); 强度: MA(C,5);"}
+    )
+    assert r.status_code == 200
+    body = r.json()
+    assert body["ok"] is True
+    assert body["signals"] == ["金叉"]
+    assert body["values"] == ["强度"]
+
+    r2 = client.post("/api/v1/formula/validate", json={"text": "A := ;"})
+    assert r2.status_code == 200
+    assert r2.json()["ok"] is False
+    assert r2.json()["error"]
+
+
+def test_rest_formula_compute_inline_ohlcv():
+    client = _client()
+    r = client.post(
+        "/api/v1/formula/compute",
+        json={"text": "买入: C > REF(C, 1); 值: MA(C, 5);", "ohlcv": _ohlcv(100), "tail": 5},
+    )
+    assert r.status_code == 200, r.text
+    body = r.json()
+    assert body["signals"] == ["买入"]
+    assert "last_row" in body and "值" in body["last_row"]
+    assert len(body["recent"]) == 5
+
+
+def test_rest_formula_backtest_async_task():
+    client = _client()
+    r = client.post(
+        "/api/v1/formula/backtest/run/async",
+        json={"text": _MA_CROSS, "ohlcv": _ohlcv(300), "cash": 100000.0},
+    )
+    assert r.status_code == 202, r.text
+    task_id = r.json()["task_id"]
+    for _ in range(200):
+        st = client.get(f"/api/v1/backtest/tasks/{task_id}").json()
+        if st["status"] in ("done", "failed"):
+            break
+        time.sleep(0.05)
+    assert st["status"] == "done", st.get("error")
+    result = st["result"]
+    assert result["formula"]["buy_col"] == "买入"
+    assert result["performance"]["total_trades"] >= 1
+
+
+def test_rest_formula_screen_async_task():
+    client = _client()
+    # 两份不同行情：A 上涨（末根 C>REF(C,1) 大概率真）、B 构造末根下跌
+    up = _ohlcv(120)
+    r = client.post(
+        "/api/v1/formula/screen/run/async",
+        json={"text": "买入: C > REF(C, 1);", "symbols": ["SH:600519"], "ohlcv": up[:0]},
+    )
+    # symbols 路径需要行情连接——离线环境预期 400/500（无 mock client）
+    # 这里只验证请求校验（symbols 非空）不炸
+    assert r.status_code in (400, 500, 202)