fix(backtest): benchmark全链路透传(API→runner→engine) + metrics分支用_dcfg修cfg=None导致relative_metrics空

sanguo_backtest/cta_engine.py

@@ -47,7 +47,7 @@ def guess_exchange(symbol: str) -> Exchange:
     return Exchange("SSE")
 
 
-def run_cta_backtest(strategy_class, symbol: str, params: dict, start: str, end: str, cfg, db_path: str) -> BacktestResult:
+def run_cta_backtest(strategy_class, symbol: str, params: dict, start: str, end: str, cfg, db_path: str, benchmark: str = "hs300") -> BacktestResult:
     """
     Run CTA strategy backtest using vnpy_ctastrategy BacktestingEngine.
 
@@ -98,6 +98,9 @@ def run_cta_backtest(strategy_class, symbol: str, params: dict, start: str, end:
 
         # Configure vnpy DB → A-share quant_trading.db. Worker process (spawn)
         # doesn't inherit main-process SETTINGS, so set before engine.load_data.
+        # _dcfg is also reused by the metrics branch (benchmark data_paths) since the
+        # cfg param can be None when called via the API.
+        _dcfg = None
         try:
             from vnpy.trader.setting import SETTINGS
             from sanguo_data.config import load_config, find_config_path
@@ -129,16 +132,17 @@ def run_cta_backtest(strategy_class, symbol: str, params: dict, start: str, end:
             if not isinstance(daily_df.index, pd.DatetimeIndex):
                 daily_df.index = pd.to_datetime(daily_df.index)
 
-            # Get benchmark config (default hs300)
-            benchmark_key = getattr(cfg, "benchmark", "hs300") if hasattr(cfg, "benchmark") else "hs300"
-            benchmark_code = BENCHMARK_SYMBOL.get(benchmark_key, "sh000300")
+            # Get benchmark code (default hs300) + a cfg that has data_paths.
+            # _dcfg is the loaded config; fall back to the passed cfg if loading failed.
+            benchmark_code = BENCHMARK_SYMBOL.get(benchmark, "sh000300")
+            bench_cfg = _dcfg if (_dcfg is not None and hasattr(_dcfg, "data_paths")) else cfg
 
             # Load benchmark data
             start_date = start_dt if isinstance(start_dt, datetime) else datetime.strptime(start, "%Y-%m-%d")
             end_date = end_dt if isinstance(end_dt, datetime) else datetime.strptime(end, "%Y-%m-%d")
 
             try:
-                bench_df = read_index_daily(benchmark_code, start_date, end_date, cfg)
+                bench_df = read_index_daily(benchmark_code, start_date, end_date, bench_cfg)
                 if bench_df is not None and not bench_df.empty and "close" in bench_df.columns:
                     # Calculate benchmark daily returns
                     bench_df["date"] = pd.to_datetime(bench_df["date"])