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 +1,214 @@
+"""通达信公式解析器测试（tokenizer / AST / 白名单求值 / 信号归类 / 安全性）。"""
+
+from __future__ import annotations
+
+import numpy as np
+import pandas as pd
+import pytest
+
+from easy_tdx.formula import FormulaError, compile_formula
+
+
+def _df(n: int = 60, seed: int = 3) -> pd.DataFrame:
+    rng = np.random.default_rng(seed)
+    dates = pd.date_range("2024-01-01", periods=n, freq="B")
+    close = 10.0 * np.cumprod(1.0 + 0.002 + rng.normal(0, 0.015, n))
+    return pd.DataFrame(
+        {
+            "datetime": dates,
+            "open": close * 0.999,
+            "high": close * 1.02,
+            "low": close * 0.98,
+            "close": close,
+            "vol": rng.uniform(1e6, 5e6, n),
+            "amount": close * rng.uniform(1e6, 5e6, n),
+        }
+    )
+
+
+# ── 编译与语法 ───────────────────────────────────────────────────────────────
+
+
+def test_compile_and_outputs():
+    formula = compile_formula(
+        """
+        N := 9;
+        RSV := (C - LLV(L, N)) / (HHV(H, N) - LLV(L, N)) * 100;
+        K := SMA(RSV, 3, 1);
+        金叉: CROSS(K, 20);
+        强度: K;
+        """
+    )
+    res = formula.compute(_df())
+    assert "金叉" in res.signals
+    assert "强度" in res.values
+    frame = res.to_frame()
+    assert list(frame.columns) == ["金叉", "强度"]
+    assert len(frame) == 60
+
+
+def test_syntax_error_has_position():
+    with pytest.raises(FormulaError):
+        compile_formula("A := ;")
+    with pytest.raises(FormulaError):
+        compile_formula("A := UNKNOWN_FUNC(C)")
+    with pytest.raises(FormulaError):
+        compile_formula("A := B + ")  # 引用未定义变量且语法断裂
+
+
+def test_unknown_variable_rejected():
+    with pytest.raises(FormulaError, match="未知变量"):
+        compile_formula("A: X1;").compute(_df())
+
+
+def test_unknown_function_rejected():
+    with pytest.raises(FormulaError, match="白名单"):
+        compile_formula("A: EVAL(C);").compute(_df())
+
+
+def test_empty_formula_rejected():
+    with pytest.raises(FormulaError, match="为空"):
+        compile_formula("{只有注释}")
+
+
+def test_no_python_eval_injection():
+    """公式层不走 Python eval：危险标识符按未知变量/函数拒绝。"""
+    with pytest.raises(FormulaError):
+        compile_formula("__import__('os'): 1;").compute(_df())
+    with pytest.raises(FormulaError):
+        compile_formula("A: OPEN(C);").compute(_df())
+
+
+# ── 语义正确性 ───────────────────────────────────────────────────────────────
+
+
+def test_series_aliases():
+    """C/O/H/L/V/AMOUNT 别名与底层列一致。"""
+    df = _df(50)
+    res = compile_formula("高价: H; 低价: L; 收盘: CLOSE; 量: VOL; 额: AMOUNT;").compute(df)
+    assert np.allclose(res.columns["高价"], df["high"])
+    assert np.allclose(res.columns["收盘"], df["close"])
+    assert np.allclose(res.columns["量"], df["vol"])
+
+
+def test_ma_matches_mytt():
+    from easy_tdx.MyTT import MA
+
+    df = _df(50)
+    res = compile_formula("均线: MA(C, 5);").compute(df)
+    assert np.allclose(res.columns["均线"], MA(df["close"].to_numpy(), 5), equal_nan=True)
+
+
+def test_cross_semantics():
+    """CROSS(A,B)：A 上穿 B 的那一根为 1，其余 0。"""
+    df = _df(50)
+    res = compile_formula(
+        """
+        快: MA(C, 3);
+        慢: MA(C, 10);
+        金叉: CROSS(快, 慢);
+        """
+    ).compute(df)
+    golden = res.columns["金叉"]
+    assert set(np.unique(golden[np.isfinite(golden)])).issubset({0.0, 1.0})
+    assert golden.sum() >= 0  # 结构完整（趋势数据至少存在或为 0）
+    # CROSS 手工复算对拍
+    from easy_tdx.MyTT import CROSS, MA
+
+    fast = MA(df["close"].to_numpy(), 3)
+    slow = MA(df["close"].to_numpy(), 10)
+    assert np.allclose(golden, CROSS(fast, slow), equal_nan=True)
+
+
+def test_safe_division_zero_denominator_nan():
+    """除零 → NaN（不炸、不 inf）。"""
+    df = _df(30)
+    res = compile_formula("比值: C / (C - C);").compute(df)  # 分母全 0
+    assert np.isnan(res.columns["比值"]).all()
+
+
+def test_logic_operators():
+    df = _df(40)
+    res = compile_formula(
+        """
+        条件1: C > MA(C, 5);
+        条件2: C > MA(C, 20);
+        同时: 条件1 AND 条件2;
+        任一: 条件1 OR 条件2;
+        取反: NOT(条件1);
+        """
+    ).compute(df)
+    c1 = res.columns["条件1"] > 0.5
+    c2 = res.columns["条件2"] > 0.5
+    assert np.allclose(res.columns["同时"] > 0.5, c1 & c2)
+    assert np.allclose(res.columns["任一"] > 0.5, c1 | c2)
+    assert np.allclose(res.columns["取反"] > 0.5, ~c1)
+
+
+def test_comparison_and_unary():
+    df = _df(30)
+    res = compile_formula("跌幅: -(C - REF(C, 1)) / REF(C, 1) * 100; 平: C == C;").compute(df)
+    assert (res.columns["平"] == 1.0).all()
+    assert "跌幅" in res.values
+
+
+def test_warmup_nan_not_signal():
+    """预热期 NaN 不产生信号（比较含 NaN → 0）。"""
+    df = _df(30)
+    res = compile_formula("信号: CROSS(MA(C, 20), MA(C, 25));").compute(df)
+    sig = res.columns["信号"]
+    assert np.nanmax(np.nan_to_num(sig[:25])) <= 1.0
+    assert np.isnan(sig).sum() == 0  # 布尔输出不含 NaN
+
+
+def test_output_classification_boolean_vs_numeric():
+    """比较/逻辑输出 → 信号；数值输出 → 数值列；0/1 值域数值也归信号。"""
+    df = _df(40)
+    res = compile_formula(
+        """
+        布尔输出: C > REF(C, 1);
+        数值输出: MA(C, 5) - MA(C, 20);
+        """
+    ).compute(df)
+    assert res.signals == ["布尔输出"]
+    assert res.values == ["数值输出"]
+
+
+def test_last_row_for_screening():
+    df = _df(30)
+    res = compile_formula("买入: CROSS(MA(C, 3), MA(C, 10)); 值: MA(C, 5);").compute(df)
+    last = res.last_row()
+    assert set(last) == {"买入", "值"}
+    assert last["买入"] in (0.0, 1.0)
+
+
+def test_chinese_identifier_and_comment():
+    df = _df(30)
+    formula = compile_formula(
+        """
+        {这是注释：N 周期}
+        周期 := 5;
+        均线: MA(C, 周期);
+        """
+    )
+    res = formula.compute(df)
+    assert res.columns["均线"][0] != res.columns["均线"][-1]
+
+
+def test_compiled_formula_reusable_across_frames():
+    f = compile_formula("值: MA(C, 5);")
+    r1 = f.compute(_df(30, seed=1))
+    r2 = f.compute(_df(40, seed=2))
+    assert len(r1.columns["值"]) == 30
+    assert len(r2.columns["值"]) == 40
+
+
+def test_compiled_formula_is_dataclass_safe():
+    """CompiledFormula 可 pickle（进程池/后台任务传输）。"""
+    import pickle
+
+    f = compile_formula("值: MA(C, 5);")
+    f2 = pickle.loads(pickle.dumps(f))
+    assert np.allclose(
+        f.compute(_df(20)).columns["值"], f2.compute(_df(20)).columns["值"], equal_nan=True
+    )