no message

wangjing_projects/projects/picture_material/stock_summery/new_stock/all_connect.py

@@ -173,7 +173,7 @@ class ConnectSpider:
             try:
                 table_name = "stock_image_summary_wj"
                 # 修改查询语句以匹配你的数据表名称和列名称
-                query = f"""SELECT account_id,account_secret FROM {table_name} where id = {item_id}"""
+                query = f"""SELECT account_id,account_secret FROM {table_name} where id = {item_id} and state=1"""
                 print(query)
                 df_status = self.db_engine192.read_sql(query)
                 if len(df_status) > 0:
@@ -192,7 +192,7 @@ class ConnectSpider:
         for i in range(5):
             try:
                 table_name = "stock_image_detail_wj" # 全部下载完成之后删除这个条件
-                sql_query = f"SELECT image_id FROM {table_name} where created_time>'2025-12-12'"
+                sql_query = f"SELECT image_id FROM {table_name}"
                 df_status = self.db_engine192.read_sql(sql_query)
                 image_id = list(df_status['image_id'].astype(str))
                 return image_id
@@ -206,7 +206,7 @@ class ConnectSpider:
                 with self.db_engine192.begin() as connection:
                     table_name = "stock_image_detail_wj"
                     sql_update = f"UPDATE {table_name} SET state = 3 WHERE image_id ='{image_id}' and state = 2"
-                    print(sql_update,'234343434343434343434343434')
+                    print(sql_update,'下载完成修改状态为3 .条件为2 的')
                     connection.execute(sql_update)
                 break
             except Exception as e:
@@ -223,8 +223,8 @@ class ConnectSpider:
             result_df = self.db_engine192.read_then_update(
                 select_sql=query,
                 update_table=table_name,
-                set_values={"state": 2},  # 把库存清零
-                where_keys=["id"],  # WHERE sku = :sku
+                set_values={"state": 2},  # 修改状态下载中。状态为2
+                where_keys=["id"]
             )
             # print(result_df)
             result_list = result_df.values.tolist()