From 7099e71b5cc158d8e5dd21c4a496e935451f120c Mon Sep 17 00:00:00 2001
From: workpc <liurui_test@163.com>
Date: Tue, 3 Dec 2024 14:57:47 +0800
Subject: [PATCH] =?UTF-8?q?=E6=B7=BB=E5=8A=A0=E6=95=B0=E6=8D=AE=E5=BA=93?=
 =?UTF-8?q?=E5=BC=82=E5=B8=B8=E5=88=A4=E6=96=AD?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 main_yuanyou.py | 39 +++++++++++++++++++++------------------
 1 file changed, 21 insertions(+), 18 deletions(-)

diff --git a/main_yuanyou.py b/main_yuanyou.py
index 453917d..83f9255 100644
--- a/main_yuanyou.py
+++ b/main_yuanyou.py
@@ -139,24 +139,27 @@ def predict_main():
             sqlitedb.create_table('most_model', columns="ds datetime, most_common_model TEXT")
         sqlitedb.insert_data('most_model', (datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'), most_common_model,), columns=('ds', 'most_common_model',))
 
-    if is_weekday:
-        logger.info('今天是周一，更新预测模型')
-        # 上传预警信息到数据库
-        warning_data_df = df_zhibiaoliebiao.copy()
-        warning_data_df = warning_data_df[warning_data_df['停更周期']> 3 ][['指标名称', '指标id', '频度','更新周期','指标来源','最后更新时间','停更周期']]
-        # 重命名列名
-        warning_data_df = warning_data_df.rename(columns={'指标名称': 'INDICATOR_NAME', '指标id': 'INDICATOR_ID', '频度': 'FREQUENCY', '更新周期': 'UPDATE_FREQUENCY', '指标来源': 'DATA_SOURCE', '最后更新时间': 'LAST_UPDATE_DATE', '停更周期': 'UPDATE_SUSPENSION_CYCLE'})
-        from sqlalchemy import create_engine
-        engine = create_engine(f'mysql+pymysql://{dbusername}:{password}@{host}:{port}/{dbname}')
-        warning_data_df['WARNING_DATE'] =  datetime.date.today().strftime("%Y-%m-%d")
-        # 插入数据之前查询表数据然后新增id列
-        existing_data = pd.read_sql(f"SELECT * FROM {table_name}", engine)
-        if not existing_data.empty:
-            max_id = existing_data['id'].max()
-            warning_data_df['id'] = range(max_id + 1, max_id + 1 + len(warning_data_df))
-        else:
-            warning_data_df['id'] = range(1, 1 + len(warning_data_df))
-        warning_data_df.to_sql(table_name,  con=engine, if_exists='append', index=False)
+    try:
+        if is_weekday:
+            logger.info('今天是周一，更新预测模型')
+            # 上传预警信息到数据库
+            warning_data_df = df_zhibiaoliebiao.copy()
+            warning_data_df = warning_data_df[warning_data_df['停更周期']> 3 ][['指标名称', '指标id', '频度','更新周期','指标来源','最后更新时间','停更周期']]
+            # 重命名列名
+            warning_data_df = warning_data_df.rename(columns={'指标名称': 'INDICATOR_NAME', '指标id': 'INDICATOR_ID', '频度': 'FREQUENCY', '更新周期': 'UPDATE_FREQUENCY', '指标来源': 'DATA_SOURCE', '最后更新时间': 'LAST_UPDATE_DATE', '停更周期': 'UPDATE_SUSPENSION_CYCLE'})
+            from sqlalchemy import create_engine
+            engine = create_engine(f'mysql+pymysql://{dbusername}:{password}@{host}:{port}/{dbname}')
+            warning_data_df['WARNING_DATE'] =  datetime.date.today().strftime("%Y-%m-%d")
+            # 插入数据之前查询表数据然后新增id列
+            existing_data = pd.read_sql(f"SELECT * FROM {table_name}", engine)
+            if not existing_data.empty:
+                max_id = existing_data['id'].max()
+                warning_data_df['id'] = range(max_id + 1, max_id + 1 + len(warning_data_df))
+            else:
+                warning_data_df['id'] = range(1, 1 + len(warning_data_df))
+            warning_data_df.to_sql(table_name,  con=engine, if_exists='append', index=False)
+    except:
+        logger.info('上传预警信息到数据库失败')
 
 
     if is_corr: