Update R and workflow

examples/workflow_by_code.py

@@ -89,7 +89,7 @@ if __name__ == "__main__":
             "kwargs": {
                 "topk": 50,
                 "n_drop": 5,
-            }
+            },
         },
         "backtest": {
             "verbose": False,

examples/workflow_by_code_finetune.py

@@ -89,7 +89,7 @@ if __name__ == "__main__":
             "kwargs": {
                 "topk": 50,
                 "n_drop": 5,
-            }
+            },
         },
         "backtest": {
             "verbose": False,
@@ -113,7 +113,6 @@ if __name__ == "__main__":
         R.save_objects(init_model=model)
         rid = R.get_recorder().id
 
-
     # Finetune model based on previous trained model
     with R.start(experiment_name="finetune model"):
         recorder = R.get_recorder(rid, experiment_name="init models")

examples/workflow_by_config.py

@@ -1,49 +0,0 @@
-#  Copyright (c) Microsoft Corporation.
-#  Licensed under the MIT License.
-
-import sys
-from pathlib import Path
-
-import qlib
-import fire
-import yaml
-import pandas as pd
-from qlib.config import REG_CN
-from qlib.utils import exists_qlib_data, init_instance_by_config
-from qlib.workflow import R
-from qlib.workflow.record_temp import SignalRecord, PortAnaRecord
-
-# worflow handler function
-def workflow(config_path):
-    with open(config_path) as fp:
-        config = yaml.load(fp, Loader=yaml.FullLoader)
-
-    provider_uri = config.get("PROVIDER_URI")
-    if not exists_qlib_data(provider_uri):
-        print(f"Qlib data is not found in {provider_uri}")
-        sys.path.append(str(Path(__file__).resolve().parent.parent.joinpath("scripts")))
-        from get_data import GetData
-
-        GetData().qlib_data_cn(target_dir=provider_uri)
-
-    qlib.init(provider_uri=provider_uri, region=REG_CN)
-
-    # model initiaiton
-    model = init_instance_by_config(config.get("TASK")["model"])
-    dataset = init_instance_by_config(config.get("TASK")["dataset"])
-
-    # start exp
-    with R.start("workflow"):
-        model.fit(dataset)
-
-        # prediction
-        recorder = R.get_recorder()
-        sr = SignalRecord(model, dataset, recorder)
-        sr.generate()
-
-        # backtest
-        par = PortAnaRecord(recorder, config.get("PORT_ANALYSIS_CONFIG"))
-        par.generate()
-
-if __name__ == "__main__":
-    fire.Fire(workflow)

examples/workflow_config.yaml

@@ -1,13 +1,29 @@
-PROVIDER_URI: "~/.qlib/qlib_data/cn_data"
-MARKET: &market csi300
-BENCHMARK: &benchmark SH000300
-DATA_HANDLER_CONFIG: &data_handerler_config
+provider_uri: "~/.qlib/qlib_data/cn_data"
+market: &market csi300
+benchmark: &benchmark SH000300
+data_handler_config: &data_handler_config
     start_time: 2008-01-01
     end_time: 2020-08-01
     fit_start_time: 2008-01-01
     fit_end_time: 2014-12-31
     instruments: *market
-TASK:
+port_analysis_config: &port_analysis_config
+    strategy:
+        class: TopkDropoutStrategy
+        module_path: qlib.contrib.strategy.strategy
+        kwargs:
+            topk: 50
+            n_drop: 5
+    backtest:
+        verbose: False
+        limit_threshold: 0.095
+        account: 100000000
+        benchmark: *benchmark
+        deal_price: close
+        open_cost: 0.0005
+        close_cost: 0.0015
+        min_cost: 5
+task:
     model:
         class: LGBModel
         module_path: qlib.contrib.model.gbdt
@@ -28,25 +44,16 @@ TASK:
             handler:
                 class: Alpha158
                 module_path: qlib.contrib.data.handler
-                kwargs: *data_handerler_config
+                kwargs: *data_handler_config
             segments:
                 train: [2008-01-01, 2014-12-31]
                 valid: [2015-01-01, 2016-12-31]
                 test: [2017-01-01, 2020-08-01]
-    record: [SignalRecord, PortAnaRecord]
-PORT_ANALYSIS_CONFIG:
-    strategy:
-        class: TopkDropoutStrategy
-        module_path: qlib.contrib.strategy.strategy
-        kwargs:
-            topk: 50
-            n_drop: 5
-    backtest:
-        verbose: False
-        limit_threshold: 0.095
-        account: 100000000
-        benchmark: *benchmark
-        deal_price: close
-        open_cost: 0.0005
-        close_cost: 0.0015
-        min_cost: 5
+    record: 
+        - class: SignalRecord
+          module_path: qlib.workflow.record_temp
+          kwargs: {}
+        - class: PortAnaRecord
+          module_path: qlib.workflow.record_temp
+          kwargs: 
+            config: *port_analysis_config