fix CI

qlib/backtest/executor.py

@@ -118,7 +118,8 @@ class BaseExecutor:
     def get_report(self):
         raise NotImplementedError("get_report is not implemented!")
 
-    def get_all_executor(self):
+    def get_all_executors(self):
+        """Return all executors"""
         return [self]
 
 
@@ -247,8 +248,9 @@ class NestedExecutor(BaseExecutor):
             sub_env_report_dict.update({f"{_count}{_freq}": (_report, _positions)})
         return sub_env_report_dict
 
-    def get_all_executor(self):
-        return [self, *self.inner_executor.get_all_executor()]
+    def get_all_executors(self):
+        """Return all executors, including self and inner_executor.get_all_executors()"""
+        return [self, *self.inner_executor.get_all_executors()]
 
 
 class SimulatorExecutor(BaseExecutor):

qlib/backtest/report.py

@@ -12,6 +12,7 @@ from pandas.core.frame import DataFrame
 
 from ..utils.resam import parse_freq, resam_ts_data
 from ..data import D
+from ..tests.config import CSI300_BENCH
 
 
 class Report:
@@ -67,7 +68,7 @@ class Report:
         self.bench = self._cal_benchmark(self.benchmark_config, self.freq)
 
     def _cal_benchmark(self, benchmark_config, freq):
-        benchmark = benchmark_config.get("benchmark", "SH000300")
+        benchmark = benchmark_config.get("benchmark", CSI300_BENCH)
         if isinstance(benchmark, pd.Series):
             return benchmark
         else:

qlib/contrib/evaluate.py

@@ -29,7 +29,7 @@ def risk_analysis(r, N: int = None, freq: str = "day"):
     r : pandas.Series
         daily return series.
     N: int
-        scaler for annualizing information_ratio (day: 250, week: 50, month: 12), at least one of `N` and `freq` should exist
+        scaler for annualizing information_ratio (day: 252, week: 50, month: 12), at least one of `N` and `freq` should exist
     freq: str
         analysis frequency used for calculating the scaler, at least one of `N` and `freq` should exist
     """