更新部署代码

database/dao/mysql_dao.py

@@ -21,8 +21,8 @@ class MySqlDao:
         self._cust_tablename = "tads_brandcul_cust_info"
         self._order_tablename = "tads_brandcul_cust_order"
         self._mock_order_tablename = "yunfu_mock_data"
-        # self._shopping_tablename = "tads_brandcul_cust_info_lbs"
-        self._shopping_tablename = "yunfu_shopping_mock_data"
+        self._shopping_tablename = "tads_brandcul_cust_info_lbs"
+        # self._shopping_tablename = "yunfu_shopping_mock_data"
         
         self._initialized = True
         
@@ -51,10 +51,6 @@ class MySqlDao:
         data.drop('stat_month', axis=1, inplace=True)
         data.drop('city_uuid', axis=1, inplace=True)
         
-        # 去除重复值和填补缺失值
-        data.drop_duplicates(inplace=True)
-        data.fillna(0, inplace=True)
-        data = data.infer_objects(copy=False)
         return data
     
     def load_mock_order_data(self):
@@ -63,11 +59,6 @@ class MySqlDao:
         
         data = self.db_helper.load_data_with_page(query, {})
         
-        # 去除重复值和填补缺失值
-        data.drop_duplicates(inplace=True)
-        data.fillna(0, inplace=True)
-        data = data.infer_objects(copy=False)
-        
         return data
     
     def load_shopping_data(self, city_uuid):

models/rank/data/preprocess.py

@@ -15,8 +15,8 @@ class DataProcess():
         print("正在加载product_info...")
         self._product_data = self._mysql_dao.load_product_data(city_uuid)
         print("正在加载order_info...")
-        # self._order_data = self._mysql_dao.load_order_data(city_uuid)
-        self._order_data = self._mysql_dao.load_mock_order_data()
+        self._order_data = self._mysql_dao.load_order_data(city_uuid)
+        # self._order_data = self._mysql_dao.load_mock_order_data()
         print("正在加载shopping_info...")
         self._shopping_data = self._mysql_dao.load_shopping_data(city_uuid)
         
@@ -119,7 +119,7 @@ class DataProcess():
     
     def _generate_pos_train_data(self):
         pos_data = self._generate_original_train_data(is_pos=True)
-        pos_data = pos_data[pos_data['YLT_TURNOVER_RATE'] != 0]
+        pos_data.dropna(subset=['YLT_TURNOVER_RATE'], inplace=True)
         return pos_data