From 68246b3b6d7037f3134ceb6e59aef869e96f1d8f Mon Sep 17 00:00:00 2001
From: bxdd <bxddream@gmail.com>
Date: Thu, 25 Mar 2021 19:58:55 +0800
Subject: [PATCH] update workflow

---
 examples/rolling_process_data/workflow.py | 87 +++++------------------
 1 file changed, 18 insertions(+), 69 deletions(-)

diff --git a/examples/rolling_process_data/workflow.py b/examples/rolling_process_data/workflow.py
index 9dd4285da..2f48662bd 100644
--- a/examples/rolling_process_data/workflow.py
+++ b/examples/rolling_process_data/workflow.py
@@ -2,6 +2,7 @@
 #  Licensed under the MIT License.
 
 import qlib
+import fire
 import pickle
 import pandas as pd
 
@@ -12,12 +13,11 @@ from qlib.contrib.data.handler import Alpha158
 from qlib.utils import exists_qlib_data, init_instance_by_config
 from qlib.tests.data import GetData
 
-
 class RollingDataWorkflow(object):
 
     MARKET = "csi300"
     start_time = "2010-01-01"
-    end_time = "2019-12-31"
+    end_time = "2019-12-31" 
     rolling_cnt = 5
 
     def _init_qlib(self):
@@ -28,7 +28,7 @@ class RollingDataWorkflow(object):
             print(f"Qlib data is not found in {provider_uri}")
             GetData().qlib_data(target_dir=provider_uri, region=REG_CN)
         qlib.init(provider_uri=provider_uri, region=REG_CN)
-
+    
     def _dump_pre_handler(self, path):
         handler_config = {
             "class": "Alpha158",
@@ -52,13 +52,13 @@ class RollingDataWorkflow(object):
         self._dump_pre_handler("pre_handler.py")
         pre_handler = self._load_pre_handler("pre_handler.py")
 
-        train_start_time = (2010, 1, 1)
-        train_end_time = (2012, 12, 31)
-        valid_start_time = (2013, 1, 1)
-        valid_end_time = (2013, 12, 31)
-        test_start_time = (2014, 1, 1)
-        test_end_time = (2014, 12, 31)
-
+        train_start_time = (2010,1,1)
+        train_end_time = (2012,12,31)
+        valid_start_time = (2013,1,1)
+        valid_end_time = (2013,12,31)
+        test_start_time = (2014,1,1)
+        test_end_time = (2014,12,31)
+        
         dataset_config = {
             "class": "DatasetH",
             "module_path": "qlib.data.dataset",
@@ -71,9 +71,9 @@ class RollingDataWorkflow(object):
                         "end_time": datetime(*test_end_time),
                         "fit_start_time": datetime(*train_start_time),
                         "fit_end_time": datetime(*train_end_time),
-                        "data_loader_kwargs": {
+                        "data_loader_kwargs":{
                             "handler_config": pre_handler,
-                        },
+                        }
                     },
                 },
                 "segments": {
@@ -95,65 +95,14 @@ class RollingDataWorkflow(object):
                         "end_time": datetime(test_end_time[0] + 1, *test_end_time[1:]),
                     },
                     segment_kwargs={
-                        "train": (
-                            datetime(train_start_time[0] + 1, *train_start_time[1:]),
-                            datetime(train_end_time[0], *train_end_time[1:]),
-                        ),
-                        "valid": (
-                            datetime(valid_start_time[0] + 1, *valid_start_time[1:]),
-                            datetime(valid_end_time[0], *valid_end_time[1:]),
-                        ),
-                        "test": (
-                            datetime(test_start_time[0] + 1, *test_start_time[1:]),
-                            datetime(test_end_time[0], *test_end_time[1:]),
-                        ),
+                        "train": (datetime(train_start_time[0] + 1, *train_start_time[1:]), datetime(train_end_time[0], *train_end_time[1:])),
+                        "valid": (datetime(valid_start_time[0] + 1, *valid_start_time[1:]), datetime(valid_end_time[0], *valid_end_time[1:])),
+                        "test": (datetime(test_start_time[0] + 1, *test_start_time[1:]), datetime(test_end_time[0], *test_end_time[1:])),
                     },
                 )
 
-            dtrain, dvalid, dtest = dataset.prepare(["train", "valid", "test"])
-
+            dtrain, dvalid, dtest  = dataset.prepare(["train", "valid", "test"])
+            
 
 if __name__ == "__main__":
-
-    # use default data
-    provider_uri = "~/.qlib/qlib_data/cn_data"  # target_dir
-    if not exists_qlib_data(provider_uri):
-        print(f"Qlib data is not found in {provider_uri}")
-        GetData().qlib_data(target_dir=provider_uri, region=REG_CN)
-
-    qlib.init(provider_uri=provider_uri, region=REG_CN)
-
-    market = "csi300"
-    benchmark = "SH000300"
-
-    ###################################
-    # train model
-    ###################################
-    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 = {
-        "dataset": {
-            "class": "DatasetH",
-            "module_path": "qlib.data.dataset",
-            "kwargs": {
-                "handler": {
-                    "class": "Alpha158",
-                    "module_path": "qlib.contrib.data.handler",
-                    "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"),
-                },
-            },
-        },
-    }
-
-    dataset = init_instance_by_config(task["dataset"])
+    fire.Fire(RollingDataWorkflow)