Some Optimization of online code (#784)

* Some Optimization of online code

* more flexible updater and load_object & fix p*_uri

* make recorder more friendly

* remove unused import

qlib/model/ens/ensemble.py

@@ -122,6 +122,8 @@ class AverageEnsemble(Ensemble):
         # need to flatten the nested dict
         ensemble_dict = flatten_dict(ensemble_dict, sep=FLATTEN_TUPLE)
         values = list(ensemble_dict.values())
+        # NOTE: this may change the style underlying data!!!!
+        # from pd.DataFrame to pd.Series
         results = pd.concat(values, axis=1)
         results = results.groupby("datetime").apply(lambda df: (df - df.mean()) / df.std())
         results = results.mean(axis=1)

qlib/model/ens/group.py

@@ -3,9 +3,9 @@
 
 """
 Group can group a set of objects based on `group_func` and change them to a dict.
-After group, we provide a method to reduce them. 
+After group, we provide a method to reduce them.
 
-For example: 
+For example:
 
 group: {(A,B,C1): object, (A,B,C2): object} -> {(A,B): {C1: object, C2: object}}
 reduce: {(A,B): {C1: object, C2: object}} -> {(A,B): object}
@@ -109,5 +109,5 @@ class RollingGroup(Group):
                 grouped_dict.setdefault(key[:-1], {})[key[-1]] = values
         return grouped_dict
 
-    def __init__(self):
-        super().__init__(ens=RollingEnsemble())
+    def __init__(self, ens=RollingEnsemble()):
+        super().__init__(ens=ens)

qlib/model/trainer.py

@@ -26,6 +26,7 @@ from qlib.workflow.record_temp import SignalRecord
 from qlib.workflow.recorder import Recorder
 from qlib.workflow.task.manage import TaskManager, run_task
 
+
 # from qlib.data.dataset.weight import Reweighter