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