fix(live): 市值改本地估值委托——开盘不再依赖盘中Capital下载(策略session 08-24移交P0)——实锤:开盘miniQMT Capital表下载常超时(代码注释自曝trading hours常超时)→close×total_capital=NaN→策略sort_values无操作保持代码序,平安银行(≈3800亿)混进small_cap买入清单。修=get_fundamentals_df组装后增Step3.5:_apply_local_market_caps把market_cap/circulating_market_cap优先委托self._unified.get_fundamentals_df(fields=两列,估值parquet EOD,亿元同单位,全池同一时点口径);单股本地缺(NaN/新股)保留xt Capital已算值,unified整体异常静默回退开盘永不挂;date=None传今天(EOD取最新≤今天);_fetch_close本就读xtdata本地缓存不动。+6测试(本地优先/补NaN/空回退/异常回退/NaN不清值/date=None传today);628绿。验收=部署后首个9:30 small_cap买入清单不再0000xx连号不含超大盘 [vps]

sanguo_portfolio/providers/sanguo_fundamentals.py

@@ -483,6 +483,11 @@ class SanguoMiniQmtProvider(MiniQMTProvider):  # type: ignore[misc]
             row = self._build_row(jq_code, qmt_code, stock_fin, close)
             rows.append(row)
 
+        # Step 3.5: 市值本地委托覆盖(2026-08-24 P0)。开盘 Capital 下载常超时 →
+        # close×total_capital=NaN → 策略 sort_values 无操作保持代码序, small_cap
+        # 买入清单混入超大盘(平安银行实锤)。本地估值 parquet(EOD)不依赖盘中下载。
+        self._apply_local_market_caps(rows, stocks, date_str)
+
         df = pd.DataFrame(rows)
         if "code" in df.columns:
             df = df.set_index("code", drop=False)
@@ -491,6 +496,41 @@ class SanguoMiniQmtProvider(MiniQMTProvider):  # type: ignore[misc]
             df = df[keep]
         return df
 
+    def _apply_local_market_caps(
+        self,
+        rows: List[Dict[str, Any]],
+        stocks: List[str],
+        date_str: Optional[str],
+    ) -> None:
+        """market_cap/circulating_market_cap 优先本地 unified 估值 parquet(亿元)。
+
+        全池同一时点口径(EOD 快照), 盘中 Capital 缓存缺/旧不再影响市值排序;
+        单股本地缺(新股未入昨日估值表/NaN)保留 _build_row 已算值回退 xt 路径;
+        unified 整体异常静默回退——开盘永不因本地读挂死。fields 按需短路只读
+        估值表, 大池(全市场)亦在秒级(LocalParquetProvider 批量路径实证)。
+        """
+        try:
+            df = self._unified.get_fundamentals_df(
+                stocks,
+                date=(date_str or datetime.now().strftime("%Y-%m-%d")),
+                fields=["market_cap", "circulating_market_cap"],
+            )
+        except Exception as exc:  # noqa: BLE001 - 本地失败回退 Capital 路径
+            logger.warning("本地市值委托失败, 回退 Capital 路径: %s", exc)
+            return
+        if df is None or df.empty or "code" not in df.columns:
+            return
+        by_code = {r["code"]: r for _, r in df.iterrows()}
+        for row in rows:
+            local = by_code.get(row.get("code"))
+            if local is None:
+                continue
+            for col in ("market_cap", "circulating_market_cap"):
+                v = local.get(col)
+                if v is None or pd.isna(v):
+                    continue
+                row[col] = float(v)
+
     def get_fundamentals_df_ex(
         self,
         stocks: List[str],

tests/portfolio/test_provider.py

@@ -6,6 +6,7 @@ xtquant 没 装,通过 mock_xtquant fixture 注入 sys.modules。
 from __future__ import annotations
 
 import math
+from unittest.mock import MagicMock
 
 import pandas as pd
 import pytest
@@ -90,6 +91,80 @@ class TestGetFundamentalsDf:
         assert df.empty
 
 
+class TestFundamentalsMarketCapLocalization:
+    """2026-08-24 P0: 市值改本地估值委托, 开盘不再依赖盘中 Capital 下载。
+
+    实锤: 开盘 Capital 下载常超时 → close×total_capital=NaN → 策略 sort_values
+    无操作保持代码序, 平安银行(≈3800亿)混进 small_cap 买入清单。修 = market_cap/
+    circulating_market_cap 优先本地 unified 估值 parquet(EOD, 亿元同单位, 全池
+    同一时点口径); 本地缺/异常静默回退 xt Capital 路径。"""
+
+    @staticmethod
+    def _local_unified(rows=None, side_effect=None):
+        m = MagicMock()
+        if side_effect is not None:
+            m.get_fundamentals_df.side_effect = side_effect
+        else:
+            m.get_fundamentals_df.return_value = pd.DataFrame(rows or [])
+        return m
+
+    def test_local_market_cap_wins_over_capital_path(self, mock_xtquant):
+        """本地有值 → 覆盖 close×Capital(全池同口径优先, 非「仅补 NaN」)。"""
+        provider = SanguoMiniQmtProvider({"mode": "backtest", "auto_download": False})
+        provider._unified = self._local_unified([
+            {"code": "600519.XSHG", "market_cap": 3500.0,
+             "circulating_market_cap": 3400.0},
+        ])
+        df = provider.get_fundamentals_df(["600519.XSHG"], date="2024-09-30")
+        assert abs(float(df.iloc[0]["market_cap"]) - 3500.0) < 1e-6
+        assert abs(float(df.iloc[0]["circulating_market_cap"]) - 3400.0) < 1e-6
+
+    def test_local_fills_nan_when_capital_missing(self, mock_xtquant):
+        """Capital 缺(盘中下载超时形态) → 本地补上, 不再 NaN。"""
+        mock_xtquant["xtdata"].get_financial_data.return_value = {}  # 无任何表
+        provider = SanguoMiniQmtProvider({"mode": "backtest", "auto_download": False})
+        provider._unified = self._local_unified([
+            {"code": "600519.XSHG", "market_cap": 21000.0,
+             "circulating_market_cap": 21000.0},
+        ])
+        df = provider.get_fundamentals_df(["600519.XSHG"], date="2024-09-30")
+        assert abs(float(df.iloc[0]["market_cap"]) - 21000.0) < 1e-6
+
+    def test_fallback_to_capital_when_local_empty(self, mock_xtquant):
+        provider = SanguoMiniQmtProvider({"mode": "backtest", "auto_download": False})
+        provider._unified = self._local_unified([])
+        df = provider.get_fundamentals_df(["600519.XSHG"], date="2024-09-30")
+        mc = float(df.iloc[0]["market_cap"])
+        assert 19000 < mc < 22000  # close×Capital 原路径(≈20096 亿)
+
+    def test_fallback_when_local_raises(self, mock_xtquant):
+        provider = SanguoMiniQmtProvider({"mode": "backtest", "auto_download": False})
+        provider._unified = self._local_unified(side_effect=RuntimeError("parquet io"))
+        df = provider.get_fundamentals_df(["600519.XSHG"], date="2024-09-30")
+        assert 19000 < float(df.iloc[0]["market_cap"]) < 22000
+
+    def test_local_nan_keeps_capital_value(self, mock_xtquant):
+        """本地 NaN(新股未入估值表)不清掉可算值; 同行其它列正常覆盖。"""
+        provider = SanguoMiniQmtProvider({"mode": "backtest", "auto_download": False})
+        provider._unified = self._local_unified([
+            {"code": "600519.XSHG", "market_cap": float("nan"),
+             "circulating_market_cap": 999.0},
+        ])
+        df = provider.get_fundamentals_df(["600519.XSHG"], date="2024-09-30")
+        assert 19000 < float(df.iloc[0]["market_cap"]) < 22000  # NaN 不覆盖
+        assert abs(float(df.iloc[0]["circulating_market_cap"]) - 999.0) < 1e-6
+
+    def test_none_date_passes_today_to_unified(self, mock_xtquant):
+        """live date=None(9:30 选股) → 本地委托收到今天(EOD 估值取最新≤今天)。"""
+        from datetime import datetime as _dt
+        provider = SanguoMiniQmtProvider({"mode": "backtest", "auto_download": False})
+        provider._unified = self._local_unified([])
+        provider.get_fundamentals_df(["600519.XSHG"], date=None)
+        kwargs = provider._unified.get_fundamentals_df.call_args.kwargs
+        assert kwargs["date"] == _dt.now().strftime("%Y-%m-%d")
+        assert kwargs["fields"] == ["market_cap", "circulating_market_cap"]
+
+
 class TestGetFundamentalsQueryDictMode:
     def test_dict_with_stocks_returns_dataframe(self, mock_xtquant):
         provider = SanguoMiniQmtProvider({"mode": "backtest", "auto_download": False})