black format

examples/high_freq/highfreq_handler.py

@@ -50,7 +50,6 @@ class HighFreqHandler(DataHandlerLP):
             drop_raw=drop_raw,
         )
 
-
     def get_feature_config(self):
         fields = []
         names = []
@@ -98,7 +97,7 @@ class HighFreqHandler(DataHandlerLP):
             )
         ]
         names += ["$open", "$high", "$low", "$close", "$vwap"]
-        
+
         fields += [
             "Ref({0}, 240)/Ref(DayLast({1}), 240)".format(
                 template_if.format(
@@ -205,7 +204,9 @@ class HighFreqBacktestHandler(DataHandler):
         template_paused = "Select(Eq($paused, 0.0), {0})"
         template_fillnan = "FFillNan({0})"
 
-        fields += [template_fillnan.format(template_paused.format("$close")),]
+        fields += [
+            template_fillnan.format(template_paused.format("$close")),
+        ]
         names += ["$close0"]
         fields += [
             "If(Eq({1}, np.nan), 0, If(Or(Gt({2}, Mul(1.001, {4})), Lt({2}, Mul(0.999, {3}))), 0, {1}))".format(

examples/high_freq/highfreq_ops.py

@@ -9,7 +9,7 @@ from qlib.data.data import Cal
 class DayFirst(ElemOperator):
     def __init__(self, feature):
         super(DayFirst, self).__init__(feature, "day_first")
-    
+
     def _load_internal(self, instrument, start_index, end_index, freq):
         _calendar = Cal.get_calender_day(freq=freq)[0]
         series = self.feature.load(instrument, start_index, end_index, freq)
@@ -44,6 +44,7 @@ class Date(ElemOperator):
         series = self.feature.load(instrument, start_index, end_index, freq)
         return pd.Series(_calendar[series.index], index=series.index)
 
+
 class Select(PairOperator):
     def __init__(self, condition, feature):
         super(Select, self).__init__(condition, feature, "select")
@@ -53,10 +54,11 @@ class Select(PairOperator):
         series_feature = self.feature_right.load(instrument, start_index, end_index, freq)
         return series_feature.loc[series_condition]
 
+
 class IsNull(ElemOperator):
     def __init__(self, feature):
         super(IsNull, self).__init__(feature, "isnull")
 
     def _load_internal(self, instrument, start_index, end_index, freq):
         series = self.feature.load(instrument, start_index, end_index, freq)
-        return series.isnull()
+        return series.isnull()

examples/high_freq/highfreq_processor.py

@@ -62,9 +62,9 @@ class HighFreqNorm(Processor):
         feat_1 = df_values[:, [5, 6, 7, 8, 9, 11]].reshape(-1, 6 * 240)
 
         df_new_features = pd.DataFrame(
-           data=np.concatenate((feat, feat_1), axis=1),
-           index=idx,
-           columns=["FEATURE_%d" % i for i in range(12 * 240)],
+            data=np.concatenate((feat, feat_1), axis=1),
+            index=idx,
+            columns=["FEATURE_%d" % i for i in range(12 * 240)],
         ).sort_index()
 
-        return df_new_features
+        return df_new_features

examples/high_freq/workflow.py

@@ -24,6 +24,7 @@ from qlib.data.data import Cal
 
 from highfreq_ops import DayFirst, DayLast, FFillNan, Date, Select, IsNull
 
+
 def save_dataset(dataset, path: [Path, str]):
     """
     save dataset to path
@@ -35,6 +36,7 @@ def save_dataset(dataset, path: [Path, str]):
     """
     dataset.to_pickle(path=path)
 
+
 def load_dataset(path: [Path, str], init_type=DataHandlerLP.IT_LS):
     """
     load dataset from path
@@ -48,7 +50,7 @@ def load_dataset(path: [Path, str], init_type=DataHandlerLP.IT_LS):
         - if `init_type` == DataHandlerLP.IT_FIT_SEQ:
 
             the input of `DataHandlerLP.fit` will be the output of the previous processor
-        
+
         - if `init_type` == DataHandlerLP.IT_FIT_IND:
 
             the input of `DataHandlerLP.fit` will be the original df
@@ -57,17 +59,24 @@ def load_dataset(path: [Path, str], init_type=DataHandlerLP.IT_LS):
 
             The state of the object has been load by pickle
     """
-    fd = open(path, 'rb')
+    fd = open(path, "rb")
     dataset = pickle.load(fd)
     dataset.init(init_type=init_type)
     fd.close()
     return dataset
 
+
 if __name__ == "__main__":
 
     # use default data
     provider_uri = "/mnt/v-xiabi/data/qlib/high_freq"  # target_dir
-    qlib.init(provider_uri=provider_uri, custom_ops=[DayFirst, DayLast, FFillNan, Date, Select, IsNull], redis_port=233, region=REG_CN, auto_mount=False)
+    qlib.init(
+        provider_uri=provider_uri,
+        custom_ops=[DayFirst, DayLast, FFillNan, Date, Select, IsNull],
+        redis_port=233,
+        region=REG_CN,
+        auto_mount=False,
+    )
 
     MARKET = "csi300"
     BENCHMARK = "SH000300"
@@ -134,4 +143,3 @@ if __name__ == "__main__":
     Cal.get_calender_day(freq="1min")  # TO FIX: load the calendar day for cache
     dataset = init_instance_by_config(task["dataset"])
     dataset_backtest = init_instance_by_config(task["dataset_backtest"])
-