添加数据服务脚本

app/service/data_service.py

+#!/usr/bin/python3.6
+# -*- coding: utf-8 -*-
+# @Time    : 2020/11/18 19:12
+# @Author  : Jie. Z
+# @Email   : zhaojiestudy@163.com
+# @File    : data_service.py
+# @Software: PyCharm
+
+import pandas as pd
+import numpy as np
+from sqlalchemy import and_
+from app.api.engine import tamp_user_session, tamp_product_session
+from app.model.tamp_user_models import t_customer_order, t_customer_info
+from app.model.tamp_product_models import t_fund_info
+
+
+class UserCustomerDataAdaptor:
+    fund_nav_total = pd.DataFrame()
+    user_id = ""
+    customer_id = ""
+
+    def __init__(self, user_id, customer_id):
+        self.user_id = user_id
+        self.customer_id = customer_id
+        self.user_customer_order_df = self.get_user_customer_order_data()
+
+    # 获取理财师下该用户所有订单列表
+    def get_user_customer_order_data(self):
+        # data1 = tamp_user_session.query(t_customer_order)\
+        #     .filter(user_id = self.user_id).all()
+        # data2 = tamp_user_session.query(t_customer_info).all()
+        # data3 = tamp_product_session.query(t_fund_info).all()
+
+        sql_user = """select f2.realname,f3.customer_name,fund_id,f1.order_type,f1.pay_date,f1.subscription_fee,f1.confirm_share_date,f1.confirm_share,f1.confirm_amount,f1.nav,f1.folio_name from customer_order f1, user_info f2,customer_info f3   where f2.id=f1.user_id and f3.id=f1.customer_id and f1.user_id='{}' and f1.customer_id='{}'""".format(self.user_id, self.customer_id)
+        cur = tamp_user_session.execute(sql_user)
+        data = cur.fetchall()
+        order_df = pd.DataFrame(list(data), columns=['username', 'customer_name', 'fund_id', 'order_type', 'pay_date',
+                                                     'subscription_fee', 'confirm_share_date', 'confirm_share',
+                                                     'confirm_amount', 'nav', 'folio_name'])
+
+        sql_product = "select distinct `id`, `fund_short_name`, `nav_frequency`, `substrategy` from `fund_info`"
+        cur = tamp_product_session.execute(sql_product)
+        data = cur.fetchall()
+        product_df = pd.DataFrame(list(data), columns=['fund_id', 'fund_name', 'freq', 'substrategy'])
+
+        user_customer_order_df = order_df.set_index('fund_id').join(product_df.set_index('fund_id')).reset_index()
+        return user_customer_order_df
+
+    # 获取客户持有的基金净值数据
+    def get_customer_fund_nav_data(self):
+
+        for cur_fund_id in self.user_customer_order_df["fund_id"].unique():
+            # 对应基金净值
+            sql = """select distinct `price_date`, `nav`,`cumulative_nav` from `fund_nav` where `fund_id`='{}'  order by `price_date` ASC""".format(cur_fund_id)
+            cur = tamp_product_session.execute(sql)
+            data = cur.fetchall()
+            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'])
+
+            print(cur_fund_id)
+        return
+    # 获取客户对比指数净值数据
+    def get_customer_index_nav_data(self, index_id):
+        pass
+
+    # 组合收益
+    def combine_ratio(self):
+        pass
+