feat:修改日志

XGB/vov_xgboost_train.py

@@ -114,7 +114,7 @@ def fetch_feature_data_dt(dt: str, index):
     :return:
     """
 
-    logger.info(f"开始处理 videoid_vov_base_data -- {dt} 的数据")
+    logger.info(f"fetch_feature_data_dt.dt -- {dt} 的数据")
 
     df = get_partition_df("videoid_vov_base_data", dt).fillna(0)
 
@@ -164,23 +164,34 @@ def fetch_feature_data(t_1_datetime: datetime):
     :return:
     """
 
-    logger.info(f"fetch_feature_data.label_datetime: {t_1_datetime.strftime('%Y%m%d')}")
-
     with concurrent.futures.ThreadPoolExecutor(5) as executor:
         t_1_feature_task = executor.submit(
             fetch_feature_data_dt, t_1_datetime.strftime("%Y%m%d"), 1
         )
+        t_2_datetime = t_1_datetime - timedelta(days=1)
         t_2_feature_task = executor.submit(
-            fetch_feature_data_dt, (t_1_datetime - timedelta(days=1)).strftime("%Y%m%d"), 2
+            fetch_feature_data_dt, t_2_datetime.strftime("%Y%m%d"), 2
         )
+        t_3_datetime = t_1_datetime - timedelta(days=2)
         t_3_feature_task = executor.submit(
-            fetch_feature_data_dt, (t_1_datetime - timedelta(days=2)).strftime("%Y%m%d"), 3
+            fetch_feature_data_dt, t_3_datetime.strftime("%Y%m%d"), 3
         )
+        t_4_datetime = t_1_datetime - timedelta(days=3)
         t_4_feature_task = executor.submit(
-            fetch_feature_data_dt, (t_1_datetime - timedelta(days=3)).strftime("%Y%m%d"), 4
+            fetch_feature_data_dt, t_4_datetime.strftime("%Y%m%d"), 4
         )
+        t_5_datetime = t_1_datetime - timedelta(days=4)
         t_5_feature_task = executor.submit(
-            fetch_feature_data_dt, (t_1_datetime - timedelta(days=4)).strftime("%Y%m%d"), 5
+            fetch_feature_data_dt, t_5_datetime.strftime("%Y%m%d"), 5
+        )
+
+        logger.info(
+            f"fetch_feature_data:"
+            f"\n\t t_1_feature_task.datetime: {t_1_datetime.strftime('%Y%m%d')}"
+            f"\n\t t_2_feature_task.datetime: {t_2_datetime.strftime('%Y%m%d')}"
+            f"\n\t t_3_feature_task.datetime: {t_3_datetime.strftime('%Y%m%d')}"
+            f"\n\t t_4_feature_task.datetime: {t_4_datetime.strftime('%Y%m%d')}"
+            f"\n\t t_5_feature_task.datetime: {t_5_datetime.strftime('%Y%m%d')}"
         )
 
         t_1_feature = t_1_feature_task.result()
@@ -239,9 +250,9 @@ def xgb_train_multi_dt_data(t_1_label_dt: datetime):
         t_1_feature_dt = t_1_label_dt - timedelta(1)
         logger.info(
             f"VOV模型特征数据处理 --- t_1_label_future:"
-            f"label_datetime: {t_1_label_dt.strftime('%Y%m%d')}"
-            f"feature_datetime: {t_1_feature_dt.strftime('%Y%m%d')}"
-            f"view_rate_datetime: {t_1_label_dt.strftime('%Y%m%d')}"
+            f"\n\t label_datetime: {t_1_label_dt.strftime('%Y%m%d')}  "
+            f"\n\t feature_datetime: {t_1_feature_dt.strftime('%Y%m%d')}  "
+            f"\n\t view_rate_datetime: {t_1_label_dt.strftime('%Y%m%d')}  "
         )
         t_1_label_future = executor.submit(fetch_data, t_1_label_dt, t_1_feature_dt, t_1_label_dt)
 
@@ -249,9 +260,9 @@ def xgb_train_multi_dt_data(t_1_label_dt: datetime):
         t_2_feature_dt = t_2_label_dt - timedelta(1)
         logger.info(
             f"VOV模型特征数据处理 --- t_2_label_future:"
-            f"label_datetime: {t_2_label_dt.strftime('%Y%m%d')}"
-            f"feature_datetime: {t_2_feature_dt.strftime('%Y%m%d')}"
-            f"view_rate_datetime: {t_2_label_dt.strftime('%Y%m%d')}"
+            f"\n\t label_datetime: {t_2_label_dt.strftime('%Y%m%d')}  "
+            f"\n\t feature_datetime: {t_2_feature_dt.strftime('%Y%m%d')}  "
+            f"\n\t view_rate_datetime: {t_2_label_dt.strftime('%Y%m%d')}  "
         )
         t_2_label_future = executor.submit(fetch_data, t_2_label_dt, t_2_feature_dt, t_2_label_dt)
 
@@ -259,9 +270,9 @@ def xgb_train_multi_dt_data(t_1_label_dt: datetime):
         t_3_feature_dt = t_3_label_dt - timedelta(1)
         logger.info(
             f"VOV模型特征数据处理 --- t_3_label_future:"
-            f"label_datetime: {t_3_label_dt.strftime('%Y%m%d')}"
-            f"feature_datetime: {t_3_feature_dt.strftime('%Y%m%d')}"
-            f"view_rate_datetime: {t_3_label_dt.strftime('%Y%m%d')}"
+            f"\n\t label_datetime: {t_3_label_dt.strftime('%Y%m%d')}  "
+            f"\n\t feature_datetime: {t_3_feature_dt.strftime('%Y%m%d')}  "
+            f"\n\t view_rate_datetime: {t_3_label_dt.strftime('%Y%m%d')}  "
         )
         t_3_label_future = executor.submit(fetch_data, t_3_label_dt, t_3_feature_dt, t_3_label_dt)
 
@@ -281,9 +292,9 @@ def xgb_predict_dt_data(label_datetime: datetime):
     feature_start_datetime = label_datetime
     logger.info(
         f"VOV模型预测数据处理 --- predict_df: "
-        f"label_datetime: {label_datetime.strftime('%Y%m%d')}"
-        f"feature_datetime: {feature_start_datetime.strftime('%Y%m%d')}"
-        f"view_rate_datetime: {label_datetime.strftime('%Y%m%d')}"
+        f"label_datetime: {label_datetime.strftime('%Y%m%d')}  "
+        f"feature_datetime: {feature_start_datetime.strftime('%Y%m%d')}  "
+        f"view_rate_datetime: {label_datetime.strftime('%Y%m%d')}  "
     )
     return fetch_data(label_datetime, feature_start_datetime, label_datetime)