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backend/app/api/backtest.py

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+"""回测域路由：策略回测（旧 API，K线+指标+买卖点+净值）+ 自然语言事件回测。"""
+from __future__ import annotations
+
+import json
+
+import pandas as pd
+from fastapi import APIRouter, Depends, HTTPException
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from ..backtest.engine import BacktestConfig, run_backtest
+from ..backtest.events import EventEngineError, run_event_backtest
+from ..backtest.strategies import build_strategy
+from ..data import fetcher, repository
+from ..data.aggregation import bars_per_year, resample_bars
+from ..data.symbols import is_etf_symbol
+from ..db import get_session
+from ..models import BacktestRun
+from ..schemas import (
+    BacktestRequest,
+    BacktestResponse,
+    CandleOut,
+    EquityPoint,
+    EventBacktestRequest,
+    EventBacktestResponse,
+    IndicatorOut,
+    MetricsOut,
+    SignalOut,
+)
+from ..screener.llm import parse_event_spec, ScreenerError
+from ._deps import rows_to_bars, series_to_jsonable
+
+router = APIRouter()
+
+
+@router.post("/backtest", response_model=BacktestResponse)
+async def backtest(
+    req: BacktestRequest,
+    session: AsyncSession = Depends(get_session),
+) -> BacktestResponse:
+    # 真实数据：本地无缓存则先拉取
+    if not await fetcher.is_cached(session, req.symbol):
+        try:
+            await fetcher.sync_symbol(session, req.symbol, source="auto")
+        except Exception as e:  # noqa: BLE001
+            raise HTTPException(status_code=502, detail=f"数据拉取失败: {e}")
+
+    # 日线为基底，聚合到请求周期
+    rows = await repository.get_candles(
+        session, req.symbol, "1d", start=req.start, end=req.end, limit=100000
+    )
+    if not rows:
+        raise HTTPException(status_code=404, detail=f"无数据: symbol={req.symbol}")
+
+    bars = resample_bars(rows_to_bars(rows), req.timeframe)
+    if len(bars) < 2:
+        raise HTTPException(status_code=400, detail=f"周期 {req.timeframe} 下数据不足，无法回测")
+
+    try:
+        strategy = build_strategy(req.strategy, req.params)
+    except Exception as e:  # noqa: BLE001
+        raise HTTPException(status_code=400, detail=f"策略构建失败: {e}")
+    cfg = BacktestConfig(
+        initial_cash=req.initial_cash,
+        fast_mode=req.fast_mode,
+        bars_per_year=bars_per_year(req.timeframe),
+        is_fund=is_etf_symbol(req.symbol),  # ETF 免印花税/过户费
+    )
+    result = run_backtest(bars, strategy, cfg)
+
+    df: pd.DataFrame = result["df"]
+    m = result["metrics"]
+
+    # 记录到回测运行注册表（可复现/可审计的基础）
+    session.add(
+        BacktestRun(
+            symbol=req.symbol,
+            strategy=req.strategy,
+            timeframe=req.timeframe,
+            params_json=json.dumps(req.params, ensure_ascii=False),
+            initial_cash=req.initial_cash,
+            total_return=m["total_return"],
+            max_drawdown=m["max_drawdown"],
+            sharpe=m["sharpe"],
+            num_trades=m["num_trades"],
+        )
+    )
+    await session.commit()
+
+    candles = [
+        CandleOut(ts=r["ts"], open=r["open"], high=r["high"], low=r["low"],
+                  close=r["close"], volume=r["volume"],
+                  amount=r["amount"] if "amount" in df.columns else None,
+                  turnover=r["turnover"] if "turnover" in df.columns else None)
+        for _, r in df.iterrows()
+    ]
+    signals = [
+        SignalOut(ts=f.ts, side=f.side.value, price=f.price, qty=f.qty)
+        for f in result["fills"]
+    ]
+    indicators = IndicatorOut(
+        strategy=req.strategy,
+        data={col: series_to_jsonable(df[col]) for col in result["indicator_cols"]},
+    )
+    equity = [EquityPoint(ts=t.to_pydatetime(), value=float(v))
+              for t, v in result["equity"].items()]
+
+    return BacktestResponse(
+        symbol=req.symbol,
+        timeframe=req.timeframe,
+        strategy=req.strategy,
+        candles=candles,
+        indicators=indicators,
+        signals=signals,
+        equity=equity,
+        metrics=MetricsOut(**m),
+        final_cash=result["final_cash"],
+        final_position=result["final_position"],
+        initial_cash=req.initial_cash,
+    )
+
+
+@router.post("/backtest/event", response_model=EventBacktestResponse)
+async def backtest_event(
+    req: EventBacktestRequest,
+    session: AsyncSession = Depends(get_session),
+) -> EventBacktestResponse:
+    """自然语言事件回测：入场条件命中 -> 次日买入 -> 持有 N 日，单股或全市场汇总统计。
+    直传 spec 则跳过 LLM（前端调参重跑）。"""
+    try:
+        spec = req.spec or await parse_event_spec(req.text)
+        result = await run_event_backtest(
+            session, spec,
+            ts_code=req.ts_code,
+            start=req.start.date() if req.start else None,
+            end=req.end.date() if req.end else None,
+        )
+    except ScreenerError as e:
+        raise HTTPException(status_code=502, detail=str(e))
+    except EventEngineError as e:
+        raise HTTPException(status_code=400, detail=str(e))
+    except Exception as e:  # noqa: BLE001
+        raise HTTPException(status_code=500, detail=f"事件回测失败: {e}")
+    return EventBacktestResponse(
+        text=req.text,
+        spec=result["spec"],
+        universe=result["universe"],
+        start=result["start"],
+        end=result["end"],
+        stats=result["stats"],
+        trades=result["trades"],
+        total=result["total"],
+    )