看股功能更新

backend/app/data/aggregation.py

@@ -4,6 +4,7 @@
 MVP 在应用层用 pandas resample 即可，逻辑等价、便于切换。
 
 OHLCV 聚合规则：开=周期内首根开、高=最高、低=最低、收=末根收、量=求和。
+成交额/换手率为名义量：求和（全缺则保持 None，不伪造 0）。
 """
 from __future__ import annotations
 
@@ -22,6 +23,13 @@ def bars_per_year(timeframe: str) -> int:
     return _BARS_PER_YEAR.get(timeframe, 252)
 
 
+def _sum_or_none(s: pd.Series):
+    """求和；全为 NaN 返回 None（部分缺失则忽略缺失项求和）。"""
+    if s.isna().all():
+        return None
+    return float(s.sum())
+
+
 def resample_bars(bars: list[Bar], timeframe: str) -> list[Bar]:
     """把日线 bars 聚合为目标周期；日线或未知周期原样返回。"""
     if not bars or timeframe in ("1d", "d", "day", "", None):
@@ -31,14 +39,18 @@ def resample_bars(bars: list[Bar], timeframe: str) -> list[Bar]:
         return bars
 
     df = pd.DataFrame(
-        [{"ts": b.ts, "open": b.open, "high": b.high, "low": b.low, "close": b.close, "volume": b.volume}
+        [{"ts": b.ts, "open": b.open, "high": b.high, "low": b.low, "close": b.close,
+          "volume": b.volume,
+          "amount": b.amount if b.amount is not None else float("nan"),
+          "turnover": b.turnover if b.turnover is not None else float("nan")}
          for b in bars]
     ).set_index("ts").sort_index()
 
     agg = (
         df.resample(rule)
-        .agg({"open": "first", "high": "max", "low": "min", "close": "last", "volume": "sum"})
-        .dropna()
+        .agg({"open": "first", "high": "max", "low": "min", "close": "last",
+              "volume": "sum", "amount": _sum_or_none, "turnover": _sum_or_none})
+        .dropna(subset=["open"])
     )
 
     return [
@@ -49,6 +61,8 @@ def resample_bars(bars: list[Bar], timeframe: str) -> list[Bar]:
             low=float(row["low"]),
             close=float(row["close"]),
             volume=float(row["volume"]),
+            amount=row["amount"] if row["amount"] == row["amount"] else None,  # NaN -> None
+            turnover=row["turnover"] if row["turnover"] == row["turnover"] else None,
         )
         for ts, row in agg.iterrows()
     ]