新增基金的数据联动接口3

app/controller/update_report.py

@@ -14,12 +14,7 @@ import uuid
 import oss2
 from flask_restful import Resource, reqparse
 from flask import request, render_template, g
-from flask import make_response
-
-from app.api.engine import config
 from app.service.folio_comment_service import recalculation_fund_comment
-from app.service.report_service import get_report_list, delete_report, get_one_report, edit_report, make_report, edit_report_name
-from app.service.template_manage_service import get_make_report_data
 from app.utils.auth import login_require
 from app.utils.format_transfer import npEncoder
 
@@ -40,7 +35,13 @@ class UpdateReportHandlers(Resource):
         args = self.parser.parse_args()
         args['ifa_id'] = g.ifa_id
         data = recalculation_fund_comment(args)
-        # data = make_report(args)
+        if data is False:
+            resq = {
+                "statusCode": "8888",
+                "message": "内部错误",
+                "attributes": data
+            }
+            return resq
         resp = {
             "statusCode": "0000",
             "message": "成功",

app/service/folio_comment_service.py

 from app.service.portfolio_diagnose import PortfolioDiagnose
 from app.service.result_service_v2 import UserCustomerResultAdaptor
 import datetime
-
+import json
 from app.utils.draw import draw_combination_chart
+from app.utils.format_transfer import npEncoder
 
 
 def recalculation_fund_comment(args):
-    ifa_id = args.get("ifa_id")
-    customer_id = args.get("customer_id")
-    folio = args.get("folio")
-    suggest_result = args.get("suggest_data")
-
-    suggest_fund_dict = {}
-    suggest_fund_list = []
-    suggest_amount_list = []
-    for key, value_list in suggest_result.items():
-        for value in value_list:
-            if value["after_optimization"] <= 0:
-                continue
-            suggest_fund_dict[value["fund_id"]] = value["fund_type"]
-            suggest_fund_list.append(value["fund_id"])
-            suggest_amount_list.append(value["after_optimization"])
-    sum_amount = sum(suggest_amount_list)
-    suggest_weight_list = [round(amount / sum_amount, 4) for amount in suggest_amount_list]
-
-    user_customer = UserCustomerResultAdaptor(ifa_id, customer_id, end_date=datetime.datetime.now().strftime("%Y-%m-%d"))
-    group_result = user_customer.calculate_group_result_data()
-    cur_folio_result = group_result[folio]
-
-    portfolio_diagnose = PortfolioDiagnose(client_type=1, portfolio=user_customer.all_fund_type_dict,
-                                           invest_amount=float(cur_folio_result["total_cost"]),
-                                           start_date=user_customer.start_date)
-
-    portfolio_diagnose.proposal_customize(suggest_fund_list, suggest_weight_list, suggest_fund_dict)
-
-    abandon_fund = list(set(cur_folio_result["fund_id_list"]) - set(suggest_fund_list))
-    portfolio_diagnose.abandon_fund_score = abandon_fund
-
-    finall_reslut = {}
-    finall_reslut["suggestions_result"], finall_reslut["suggestions_result_asset"], \
-    finall_reslut["return_compare_data"], \
-    finall_reslut["indicator_compare"], finall_reslut["new_group_evaluation"] = \
-        portfolio_diagnose.new_evaluation(folio, group_result, user_customer, suggest_fund_dict)
-
-    finall_reslut["return_compare_pic"] = draw_combination_chart(
-        finall_reslut["return_compare_data"]["xlabels"],
-        finall_reslut["return_compare_data"]["new_combination"],
-        finall_reslut["return_compare_data"]["origin_combination"],
-        finall_reslut["return_compare_data"]["index"])
-
-    return finall_reslut
+    try:
+        ifa_id = args.get("ifa_id")
+        customer_id = args.get("customer_id")
+        folio = args.get("folio")
+        suggest_result = json.loads(args.get("suggest_data"))
+
+        suggest_fund_dict = {}
+        suggest_fund_list = []
+        suggest_amount_list = []
+        for key, value_list in suggest_result.items():
+            for value in value_list:
+                if value["after_optimization"] <= 0:
+                    continue
+                suggest_fund_dict[value["fund_id"]] = value["fund_type"]
+                suggest_fund_list.append(value["fund_id"])
+                suggest_amount_list.append(value["after_optimization"])
+        sum_amount = sum(suggest_amount_list)
+        suggest_weight_list = [round(amount / sum_amount, 4) for amount in suggest_amount_list]
+
+        user_customer = UserCustomerResultAdaptor(ifa_id, customer_id, end_date=datetime.datetime.now().strftime("%Y-%m-%d"))
+        group_result = user_customer.calculate_group_result_data()
+        cur_folio_result = group_result[folio]
+
+        portfolio_diagnose = PortfolioDiagnose(client_type=1, portfolio=user_customer.all_fund_type_dict,
+                                               invest_amount=float(cur_folio_result["total_cost"]),
+                                               start_date=user_customer.start_date)
+
+        portfolio_diagnose.proposal_customize(suggest_fund_list, suggest_weight_list, suggest_fund_dict)
+
+        abandon_fund = list(set(cur_folio_result["fund_id_list"]) - set(suggest_fund_list))
+        portfolio_diagnose.abandon_fund_score = abandon_fund
+
+        finall_reslut = {}
+        finall_reslut["suggestions_result"], finall_reslut["suggestions_result_asset"], \
+        finall_reslut["return_compare_data"], \
+        finall_reslut["indicator_compare"], finall_reslut["new_group_evaluation"] = \
+            portfolio_diagnose.new_evaluation(folio, group_result, user_customer, suggest_fund_dict)
+
+        finall_reslut["return_compare_pic"] = draw_combination_chart(
+            finall_reslut["return_compare_data"]["xlabels"],
+            finall_reslut["return_compare_data"]["new_combination"],
+            finall_reslut["return_compare_data"]["origin_combination"],
+            finall_reslut["return_compare_data"]["index"])
+    except Exception as e:
\ No newline at end of file
+        return False
+
+    return json.dumps(finall_reslut, cls=npEncoder, ensure_ascii=False)