diff --git a/sanguo_data/datareader.py b/sanguo_data/datareader.py
index 8abae60..af19278 100644
--- a/sanguo_data/datareader.py
+++ b/sanguo_data/datareader.py
@@ -110,61 +110,60 @@ def read_parquet_15min(symbol: str, start: str, end: str, cfg, dir_key: str = "m
 
 def read_index_daily(code: str, start, end, cfg) -> pd.DataFrame:
     """
-    读指数日线数据（sh000300/sz399001 等），从 vnpy DB 读取（统一数据源）。
-    parquet 仅作原始备份，不再读取。返回类型保持 pd.DataFrame（cta_engine 消费不变）。
+    读指数日线数据（sh000300/sz399001 等），从 dbbardata 读取（2026-08-01 切自 vnpy DbBarData）。
+
+    指数点位已由 sina_index_eod 灌入 dbbardata exchange=SSE（16 个中证指数含 000300 沪深300）。
+    中证指数须用 sh 前缀（点位在 SSE）；深证指数 sz 前缀。cta_engine benchmark 用 sh000300。
+    切 dbbardata 后不再调 get_database() → 消除覆写 vnpy SETTINGS 副作用（cta_engine.py:73/199）。
 
     Args:
         code: 指数代码，带交易所前缀，如 "sh000300"（沪深300）、"sz399001"（深证成指）
-        start: 起始日期（str "YYYY-MM-DD" / date / datetime）
-        end: 结束日期（str "YYYY-MM-DD" / date / datetime）
-        cfg: 数据配置对象
+        start/end: 日期（str "YYYY-MM-DD" / date / datetime）
+        cfg: 数据配置对象（data_paths.vnpy_db 指向含 dbbardata 表的 quant_trading.db）
 
     Returns:
-        pd.DataFrame: date/open/high/low/close/volume 列；无数据返回空 DataFrame。
+        pd.DataFrame: date/open/high/low/close/volume 列（date 为 Timestamp）；无数据返回空 DataFrame。
     """
-    from vnpy.trader.database import get_database  # lazy：避免模块 import 依赖数据库驱动
+    import sqlite3
 
-    # 前缀解析交易所（指数不能用 guess_exchange：000300 以 0 开头会被误判成 SZSE，
-    # 但 000300 实际属于 SSE）。sh → SSE，sz → SZSE。
+    # 前缀解析交易所（指数不能用 guess_exchange：000300 以 0 开头会误判 SZSE，但属 SSE）。
     symbol = code[2:]
-    exchange = Exchange.SSE if code.startswith("sh") else Exchange.SZSE
+    exchange = "SSE" if code.startswith("sh") else "SZSE"
 
-    # 日期归一化：str → parse, date → combine, datetime → as-is
-    def _to_dt(s, is_start: bool) -> datetime:
+    # 日期归一化 -> 'YYYY-MM-DD'
+    def _to_str(s) -> str:
         if isinstance(s, datetime):
-            return s
+            return s.strftime("%Y-%m-%d")
         if isinstance(s, date):
-            return datetime.combine(s, datetime.min.time() if is_start else datetime.max.time())
-        return datetime.strptime(s, "%Y-%m-%d")
+            return s.strftime("%Y-%m-%d")
+        return str(s)[:10]
 
-    start_dt = _to_dt(start, True)
-    end_dt = _to_dt(end, False)
+    start_str = _to_str(start)
+    end_str = _to_str(end)
 
-    # 配置 vnpy DB（与 read_db_daily 同模式）
-    SETTINGS["database.name"] = "sqlite"
-    vnpy_db = getattr(cfg, "data_paths", {}).get("vnpy_db")
-    if not vnpy_db:
+    db_path = getattr(cfg, "data_paths", {}).get("vnpy_db")
+    if not db_path:
         raise RuntimeError("config 缺 data_paths.vnpy_db — 检查 backtest.yaml 初始化")
-    SETTINGS["database.database"] = vnpy_db
 
-    db = get_database()
-    bars = db.load_bar_data(
-        symbol=symbol,
-        exchange=exchange,
-        interval=Interval.DAILY,
-        start=start_dt,
-        end=end_dt,
-    )
+    conn = sqlite3.connect(db_path, timeout=30)
+    conn.execute("PRAGMA busy_timeout = 30000")
+    try:
+        # substr(datetime,1,10) 比日期规避混合格式（有纯日期有带时间，同 provider 模式）
+        df = pd.read_sql(
+            "SELECT datetime, open_price, high_price, low_price, close_price, volume "
+            "FROM dbbardata WHERE symbol=? AND exchange=? AND interval='d' "
+            "AND substr(datetime,1,10)>=? AND substr(datetime,1,10)<=? ORDER BY datetime",
+            conn, params=(symbol, exchange, start_str, end_str),
+        )
+    finally:
+        conn.close()
 
-    if not bars:
+    if df.empty:
         return pd.DataFrame(columns=["date", "open", "high", "low", "close", "volume"])
 
-    df = pd.DataFrame([{
-        "date": b.datetime,
-        "open": b.open_price,
-        "high": b.high_price,
-        "low": b.low_price,
-        "close": b.close_price,
-        "volume": b.volume,
-    } for b in bars])
-    return df.sort_values("date").reset_index(drop=True)
+    df = df.rename(columns={
+        "datetime": "date", "open_price": "open", "high_price": "high",
+        "low_price": "low", "close_price": "close",
+    })
+    df["date"] = pd.to_datetime(df["date"], format="mixed")
+    return df[["date", "open", "high", "low", "close", "volume"]].reset_index(drop=True)
diff --git a/tests/data/test_index_downloader.py b/tests/data/test_index_downloader.py
index e724ffa..949196e 100644
--- a/tests/data/test_index_downloader.py
+++ b/tests/data/test_index_downloader.py
@@ -131,55 +131,73 @@ def test_download_index_clears_proxy(tmp_path):
     assert "https_proxy" not in os.environ
 
 
-def test_read_index_daily_reads_from_vnpy_db(tmp_path):
-    """read_index_daily 经 vnpy get_database.load_bar_data 读指数日线,返回 DataFrame。
+def test_read_index_daily_reads_from_dbbardata(tmp_path):
+    """read_index_daily 从 dbbardata 表读指数日线(2026-08-01 切自 vnpy DbBarData)。
 
-    注:read_index_daily 数据源是 vnpy DbBarData 表(非 parquet);D2 根治拟切 dbbardata,
-    届时 mock 数据源随之更新。当前测 vnpy 路径(与 read_db_daily 同 mock 模式)。
+    建 tmp sqlite 库 + dbbardata 表插指数行,测真实 SQL 路径(非 mock)。
+    中证指数用 sh 前缀 → exchange=SSE(点位由 sina_index_eod 灌入)。
     """
-    from types import SimpleNamespace
-    from datetime import datetime
+    import sqlite3
     from sanguo_data.datareader import read_index_daily
 
+    db = tmp_path / "q.db"
+    conn = sqlite3.connect(db)
+    conn.execute(
+        "CREATE TABLE dbbardata (symbol TEXT, exchange TEXT, datetime TEXT, interval TEXT, "
+        "volume REAL, turnover REAL, open_interest REAL, open_price REAL, "
+        "high_price REAL, low_price REAL, close_price REAL)"
+    )
+    conn.executemany(
+        "INSERT INTO dbbardata (symbol,exchange,datetime,interval,volume,turnover,"
+        "open_interest,open_price,high_price,low_price,close_price) VALUES (?,?,?,?,?,?,?,?,?,?,?)",
+        [
+            ("000300", "SSE", "2024-01-02", "d", 100000, 0, 0, 3495.0, 3505.0, 3490.0, 3500.0),
+            ("000300", "SSE", "2024-01-03", "d", 120000, 0, 0, 3505.0, 3515.0, 3500.0, 3510.0),
+            ("000300", "SSE", "2024-01-04", "d", 110000, 0, 0, 3515.0, 3525.0, 3510.0, 3520.0),
+        ],
+    )
+    conn.commit()
+    conn.close()
+
     cfg = DataConfig(
-        data_paths={"vnpy_db": str(tmp_path / "q.db")},
+        data_paths={"vnpy_db": str(db)},
         data_sources={}, validation={}, performance={},
     )
-    # vnpy load_bar_data 返回类 BarData 对象(有 datetime/open_price/... 属性)
-    bars = [
-        SimpleNamespace(datetime=datetime(2024, 1, 2), open_price=3495.0,
-                        high_price=3505.0, low_price=3490.0, close_price=3500.0, volume=100000),
-        SimpleNamespace(datetime=datetime(2024, 1, 3), open_price=3505.0,
-                        high_price=3515.0, low_price=3500.0, close_price=3510.0, volume=120000),
-        SimpleNamespace(datetime=datetime(2024, 1, 4), open_price=3515.0,
-                        high_price=3525.0, low_price=3510.0, close_price=3520.0, volume=110000),
-    ]
-    mock_db = MagicMock()
-    mock_db.load_bar_data.return_value = bars
-    # read_index_daily 内 lazy import,patch 源模块属性(同 test_datareader)
-    with patch("vnpy.trader.database.get_database", return_value=mock_db):
-        result = read_index_daily("sh000300", date(2024, 1, 1), date(2024, 12, 31), cfg)
+    result = read_index_daily("sh000300", date(2024, 1, 1), date(2024, 12, 31), cfg)
 
     assert len(result) == 3
-    assert "close" in result.columns
+    assert list(result.columns) == ["date", "open", "high", "low", "close", "volume"]
     assert result["close"].iloc[0] == 3500.0
 
 
-def test_read_index_daily_passes_date_range_to_vnpy(tmp_path):
-    """read_index_daily 把 start/end 传给 vnpy load_bar_data(日期过滤在 vnpy 层)。"""
-    from datetime import datetime
+def test_read_index_daily_filters_date_range(tmp_path):
+    """read_index_daily 用 substr(datetime,1,10) 比日期,正确过滤 start/end 范围。"""
+    import sqlite3
     from sanguo_data.datareader import read_index_daily
 
+    db = tmp_path / "q.db"
+    conn = sqlite3.connect(db)
+    conn.execute(
+        "CREATE TABLE dbbardata (symbol TEXT, exchange TEXT, datetime TEXT, interval TEXT, "
+        "volume REAL, turnover REAL, open_interest REAL, open_price REAL, "
+        "high_price REAL, low_price REAL, close_price REAL)"
+    )
+    conn.executemany(
+        "INSERT INTO dbbardata (symbol,exchange,datetime,interval,volume,turnover,"
+        "open_interest,open_price,high_price,low_price,close_price) VALUES (?,?,?,?,?,?,?,?,?,?,?)",
+        [
+            ("000300", "SSE", "2024-01-02", "d", 100, 0, 0, 1, 1, 1, 3500.0),
+            ("000300", "SSE", "2024-06-15", "d", 100, 0, 0, 1, 1, 1, 3600.0),
+            ("000300", "SSE", "2025-01-10", "d", 100, 0, 0, 1, 1, 1, 3700.0),  # 范围外
+        ],
+    )
+    conn.commit()
+    conn.close()
+
     cfg = DataConfig(
-        data_paths={"vnpy_db": str(tmp_path / "q.db")},
+        data_paths={"vnpy_db": str(db)},
         data_sources={}, validation={}, performance={},
     )
-    mock_db = MagicMock()
-    mock_db.load_bar_data.return_value = []
-    with patch("vnpy.trader.database.get_database", return_value=mock_db):
-        read_index_daily("sh000300", date(2024, 1, 1), date(2024, 6, 30), cfg)
-
-    # start=date→combine 00:00:00; end=date→combine datetime.max.time()(23:59:59.999999)
-    call = mock_db.load_bar_data.call_args
-    assert call.kwargs["start"] == datetime(2024, 1, 1, 0, 0, 0)
-    assert call.kwargs["end"] == datetime(2024, 6, 30, 23, 59, 59, 999999)
+    result = read_index_daily("sh000300", "2024-01-01", "2024-12-31", cfg)
+    assert len(result) == 2  # 只 2024 两行, 2025 范围外排除
+    assert result["close"].iloc[1] == 3600.0