Add initial workflow_by_config

examples/workflow_by_code.py

@@ -46,15 +46,6 @@ if __name__ == "__main__":
         "instruments": MARKET,
     }
 
-    TRAINER_CONFIG = {
-        "train_start_time": "2008-01-01",
-        "train_end_time": "2014-12-31",
-        "validate_start_time": "2015-01-01",
-        "validate_end_time": "2016-12-31",
-        "test_start_time": "2017-01-01",
-        "test_end_time": "2020-08-01",
-    }
-
     task = {
         "model": {
             "class": "LGBModel",
@@ -82,14 +73,8 @@ if __name__ == "__main__":
                 },
                 "segments": {
                     "train": ("2008-01-01", "2014-12-31"),
-                    "valid": (
-                        "2015-01-01",
-                        "2016-12-31",
-                    ),
-                    "test": (
-                        "2017-01-01",
-                        "2020-08-01",
-                    ),
+                    "valid": ("2015-01-01", "2016-12-31"),
+                    "test": ("2017-01-01", "2020-08-01"),
                 },
             },
         },
@@ -99,8 +84,12 @@ if __name__ == "__main__":
 
     port_analysis_config = {
         "strategy": {
-            "topk": 50,
-            "n_drop": 5,
+            "class": "TopkDropoutStrategy",
+            "module_path": "qlib.contrib.strategy.strategy",
+            "kwargs": {
+                "topk": 50,
+                "n_drop": 5,
+            }
         },
         "backtest": {
             "verbose": False,

examples/workflow_by_config.py

@@ -0,0 +1,49 @@
+#  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

@@ -0,0 +1,52 @@
+PROVIDER_URI: "~/.qlib/qlib_data/cn_data"
+MARKET: &market csi300
+BENCHMARK: &benchmark SH000300
+DATA_HANDLER_CONFIG: &data_handerler_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:
+    model:
+        class: LGBModel
+        module_path: qlib.contrib.model.gbdt
+        kwargs:
+            loss: mse
+            colsample_bytree: 0.8879
+            learning_rate: 0.0421
+            subsample: 0.8789
+            lambda_l1: 205.6999
+            lambda_l2: 580.9768
+            max_depth: 8
+            num_leaves: 210
+            num_threads: 20
+    dataset:
+        class: DatasetH
+        module_path: qlib.data.dataset
+        kwargs:
+            handler:
+                class: Alpha158
+                module_path: qlib.contrib.data.handler
+                kwargs: *data_handerler_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

setup.py

@@ -56,6 +56,7 @@ REQUIRED = [
     "lightgbm",
     "tornado",
     "joblib>=0.17.0",
+    "fire>=0.3.1",
 ]
 
 # Numpy include