Fix pylint (#888)

* add_pylint_to_workflow

* fix-pylint

* fix_pylinterror

* fix-issue

qlib/model/base.py

@@ -13,7 +13,6 @@ class BaseModel(Serializable, metaclass=abc.ABCMeta):
     @abc.abstractmethod
     def predict(self, *args, **kwargs) -> object:
         """Make predictions after modeling things"""
-        pass
 
     def __call__(self, *args, **kwargs) -> object:
         """leverage Python syntactic sugar to make the models' behaviors like functions"""

qlib/model/ens/group.py

@@ -13,7 +13,7 @@ reduce: {(A,B): {C1: object, C2: object}} -> {(A,B): object}
 """
 
 from qlib.model.ens.ensemble import Ensemble, RollingEnsemble
-from typing import Callable, Union
+from typing import Callable
 from joblib import Parallel, delayed
 
 

qlib/model/interpret/base.py

@@ -27,6 +27,9 @@ class FeatureInt:
 class LightGBMFInt(FeatureInt):
     """LightGBM (F)eature (Int)erpreter"""
 
+    def __init__(self):
+        self.model = None
+
     def get_feature_importance(self, *args, **kwargs) -> pd.Series:
         """get feature importance
 
@@ -35,6 +38,8 @@ class LightGBMFInt(FeatureInt):
             parameters reference:
             https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.Booster.html?highlight=feature_importance#lightgbm.Booster.feature_importance
         """
-        return pd.Series(self.model.feature_importance(*args, **kwargs), index=self.model.feature_name()).sort_values(
+        return pd.Series(
+            self.model.feature_importance(*args, **kwargs), index=self.model.feature_name()
+        ).sort_values(  # pylint: disable=E1101
             ascending=False
         )

qlib/model/meta/dataset.py

@@ -4,8 +4,6 @@
 import abc
 from qlib.model.meta.task import MetaTask
 from typing import Dict, Union, List, Tuple, Text
-from ...workflow.task.gen import RollingGen, task_generator
-from ...data.dataset.handler import DataHandler
 from ...utils.serial import Serializable
 
 
@@ -73,4 +71,3 @@ class MetaTaskDataset(Serializable, metaclass=abc.ABCMeta):
         seg : Text
             the name of the segment
         """
-        pass

qlib/model/meta/model.py

@@ -2,10 +2,8 @@
 # Licensed under the MIT License.
 
 import abc
-from qlib.contrib.meta.data_selection.dataset import MetaDatasetDS
-from typing import Union, List, Tuple
+from typing import List
 
-from qlib.model.meta.task import MetaTask
 from .dataset import MetaTaskDataset
 
 
@@ -23,7 +21,6 @@ class MetaModel(metaclass=abc.ABCMeta):
         """
         The training process of the meta-model.
         """
-        pass
 
     @abc.abstractmethod
     def inference(self, *args, **kwargs) -> object:
@@ -35,7 +32,6 @@ class MetaModel(metaclass=abc.ABCMeta):
         object:
             Some information to guide the model learning
         """
-        pass
 
 
 class MetaTaskModel(MetaModel):

qlib/model/meta/task.py

@@ -1,9 +1,6 @@
 # Copyright (c) Microsoft Corporation.
 # Licensed under the MIT License.
 
-import abc
-from typing import Union, List, Tuple
-
 from qlib.data.dataset import Dataset
 from ...utils import init_instance_by_config
 

qlib/model/riskmodel/base.py

@@ -91,7 +91,7 @@ class RiskModel(BaseModel):
                 "return_decomposed_components" in inspect.getfullargspec(self._predict).args
             ), "This risk model does not support return decomposed components of the covariance matrix "
 
-            F, cov_b, var_u = self._predict(X, return_decomposed_components=True)
+            F, cov_b, var_u = self._predict(X, return_decomposed_components=True)  # pylint: disable=E1123
             return F, cov_b, var_u
 
         # estimate covariance

qlib/model/trainer.py

@@ -12,17 +12,13 @@ In ``DelayTrainer``, the first step is only to save some necessary info to model
 """
 
 import socket
-import time
-import re
 from typing import Callable, List
 
 from tqdm.auto import tqdm
 from qlib.data.dataset import Dataset
-from qlib.log import get_module_logger
 from qlib.model.base import Model
-from qlib.utils import flatten_dict, get_callable_kwargs, init_instance_by_config, auto_filter_kwargs, fill_placeholder
+from qlib.utils import flatten_dict, init_instance_by_config, auto_filter_kwargs, fill_placeholder
 from qlib.workflow import R
-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