分组数据结果配置成json

app/service/data_service.py

@@ -94,21 +94,21 @@ class UserCustomerDataAdaptor:
             cur_fund_nav_df = pd.DataFrame(list(data), columns=['price_date', 'nav', 'cnav'])
 
             # # 对应基金分红
-            # sql = """select distinct `distribute_date`, `distribution` from `fund_distribution` where `fund_id`='{}' and `distribute_type`='1' order by `distribute_date` ASC""".format(
-            #     cur_fund_id)
-            # cur = tamp_product_session.execute(sql)
-            # data = cur.fetchall()
-            # cur_fund_distribution_df = pd.DataFrame(list(data), columns=['price_date', 'distribution'])
-            # self.all_fund_distribution[cur_fund_id] = cur_fund_distribution_df
-            #
-            # # 对应基金performance数据
-            # sql = """select distinct `price_date`, `ret_cum_1w`, `ret__cum_1m`, `ret_cum_6m`, `ret_cum_1y`, `ret_cum_ytd`, `ret_cum_incep` from `fund_performance` where `fund_id`='{}' order by `price_date` ASC""".format(
-            #     cur_fund_id)
-            # cur = tamp_product_session.execute(sql)
-            # data = cur.fetchall()
-            # cur_fund_performance_df = pd.DataFrame(list(data),
-            # columns=['price_date', 'ret_cum_1w', 'ret__cum_1m', 'ret_cum_6m', 'ret_cum_1y', 'ret_cum_ytd', 'ret_cum_incep'])
-            # self.all_fund_performance[cur_fund_id] = cur_fund_performance_df
+            sql = """select distinct `distribute_date`, `distribution` from `fund_distribution` where `fund_id`='{}' and `distribute_type`='1' order by `distribute_date` ASC""".format(
+                cur_fund_id)
+            cur = tamp_product_session.execute(sql)
+            data = cur.fetchall()
+            cur_fund_distribution_df = pd.DataFrame(list(data), columns=['price_date', 'distribution'])
+            self.all_fund_distribution[cur_fund_id] = cur_fund_distribution_df
+
+            # 对应基金performance数据
+            sql = """select distinct `price_date`, `ret_1w`, `ret_cum_1m`, `ret_cum_6m`, `ret_cum_1y`, `ret_cum_ytd`, `ret_cum_incep` from `fund_performance` where `fund_id`='{}' order by `price_date` ASC""".format(
+                cur_fund_id)
+            cur = tamp_product_session.execute(sql)
+            data = cur.fetchall()
+            cur_fund_performance_df = pd.DataFrame(list(data),
+            columns=['price_date', 'ret_1w', 'ret_cum_1m', 'ret_cum_6m', 'ret_cum_1y', 'ret_cum_ytd', 'ret_cum_incep'])
+            self.all_fund_performance[cur_fund_id] = cur_fund_performance_df
 
             cur_fund_nav_df["price_date"] = pd.to_datetime(cur_fund_nav_df["price_date"])
             cur_fund_nav_df.set_index("price_date", inplace=True)