完善知行短线

backend/app/api.py

@@ -3,6 +3,7 @@
   GET  /api/health               健康检查
   GET  /api/candles/{sym}        取 K 线（支持 1d/1w/1M/1y 周期，日线为基底聚合）
   GET  /api/stocks               全市场股票列表（基本信息 + 最新行情 + 缓存条数）
+  GET  /api/stock/{code}/chips   个股筹码峰（cyq_chips/cyq_perf，按复权口径换算）
   GET  /api/market/overview      主页大盘总览（A 股/港美指数 + 两市市值成交统计）
   POST /api/backtest             跑回测，返回 K线+指标+买卖点+净值+绩效
   POST /api/screener/run         智能选股：自然语言 -> 条件 -> 全市场筛选
@@ -11,6 +12,7 @@
 """
 from __future__ import annotations
 
+import asyncio
 import bisect
 import json
 from datetime import datetime
@@ -27,7 +29,7 @@ from .auth import require_user
 from .backtest.events import EventEngineError, run_event_backtest
 from .backtest.strategies import build_strategy
 from .config import settings
-from .data import fetcher, repository
+from .data import fetcher, repository, tushare_provider
 from .data.aggregation import bars_per_year, resample_bars
 from .data.market_overview import MarketOverviewError, fetch_overview
 from .data.symbols import plain_code
@@ -50,6 +52,8 @@ from .schemas import (
     BacktestRequest,
     BacktestResponse,
     CandleOut,
+    ChipRowOut,
+    ChipsResponse,
     EquityPoint,
     EventBacktestRequest,
     EventBacktestResponse,
@@ -982,3 +986,78 @@ async def screener_preview(
                            candles=candles, indicators=indicators, has_more=has_more)
     await cache.cache_set(f"pv:{cache_key}", resp.model_dump(mode="json"), ttl=600)
     return resp
+
+
+@router.get("/stock/{ts_code}/chips", response_model=ChipsResponse)
+async def stock_chips(
+    ts_code: str, date: str | None = None, adjust: str = "qfq",
+    session: AsyncSession = Depends(get_session),
+) -> ChipsResponse:
+    """个股筹码峰（Tushare cyq_chips + cyq_perf，数据自 2018 年起）。
+
+    date=YYYY-MM-DD 为参考日（日 K 传当日；周/月 K 由前端传周期末）：返回
+    <=date 的最近有筹码数据的交易日截面；缺省取最新。
+    价格/成本均按 adjust（bfq/qfq/hfq）用 adj_factor 本地换算，与 K 线同口径。
+    """
+    if adjust not in _ADJUST_MODES:
+        raise HTTPException(status_code=400, detail=f"adjust 仅支持 {'/'.join(_ADJUST_MODES)}")
+    ref: str | None = None
+    if date:
+        try:
+            ref = datetime.strptime(date.strip()[:10], "%Y-%m-%d").strftime("%Y%m%d")
+        except ValueError:
+            raise HTTPException(status_code=400, detail="date 格式应为 YYYY-MM-DD")
+
+    # 历史截面不可变；键带 candles 版本号（adj_factor 随同步更新后旧缓存失效）
+    cache_key = cache.digest("chips", ts_code, ref or "latest", adjust, await cache.get_version("candles"))
+    cached = await cache.cache_get(f"chips:{cache_key}")
+    if cached is not None:
+        return ChipsResponse.model_validate(cached)
+
+    try:
+        perf, rows = await asyncio.to_thread(tushare_provider.fetch_chips, ts_code, ref)
+    except Exception as e:  # noqa: BLE001
+        raise HTTPException(status_code=502, detail=f"筹码数据获取失败: {e}")
+    if not perf:
+        resp = ChipsResponse(
+            ts_code=ts_code, trade_date=None, adjust=adjust,
+            error="无筹码数据（cyq 数据自 2018 年起，或参考日早于数据起点）",
+        )
+        await cache.cache_set(f"chips:{cache_key}", resp.model_dump(mode="json"), ttl=3600)
+        return resp
+
+    d = datetime.strptime(str(perf["trade_date"]), "%Y%m%d")
+
+    # 复权换算（与 _adjust_bars 同口径）：qfq=f(d)/f_latest，hfq=f(d)，bfq=1
+    mult = 1.0
+    if adjust != "bfq":
+        factors = (await session.execute(
+            select(AdjFactor).where(AdjFactor.ts_code == ts_code, AdjFactor.trade_date <= d)
+            .order_by(AdjFactor.trade_date)
+        )).scalars().all()
+        if factors:
+            latest_f = (await session.execute(
+                select(AdjFactor).where(AdjFactor.ts_code == ts_code)
+                .order_by(AdjFactor.trade_date.desc()).limit(1)
+            )).scalars().first()
+            f_at = float(factors[-1].adj_factor)  # <=d 的最近因子（因子是阶梯函数）
+            f_latest = float(latest_f.adj_factor) if latest_f else f_at
+            mult = f_at / f_latest if adjust == "qfq" else f_at
+
+    def _px(v) -> float | None:
+        return None if v is None or v != v else round(float(v) * mult, 3)
+
+    resp = ChipsResponse(
+        ts_code=ts_code,
+        trade_date=str(perf["trade_date"]),
+        adjust=adjust,
+        rows=[ChipRowOut(price=round(p * mult, 3), percent=v) for p, v in rows],
+        his_low=_px(perf.get("his_low")), his_high=_px(perf.get("his_high")),
+        cost_5pct=_px(perf.get("cost_5pct")), cost_15pct=_px(perf.get("cost_15pct")),
+        cost_50pct=_px(perf.get("cost_50pct")), cost_85pct=_px(perf.get("cost_85pct")),
+        cost_95pct=_px(perf.get("cost_95pct")),
+        weight_avg=_px(perf.get("weight_avg")),
+        winner_rate=_px(perf.get("winner_rate")),
+    )
+    await cache.cache_set(f"chips:{cache_key}", resp.model_dump(mode="json"), ttl=21600)
+    return resp