update

config-mdis_prr3.yml

@@ -215,6 +215,7 @@ reports: # 报告模块相关
       include-report:
 #        - daily-hold-report
         - daily-signal-report
+        - daily-mpt-report
       email:
         receives:
           - brody_wu@chifufund.com

portfolios/holder.py

@@ -11,7 +11,7 @@ from py_jftech import (
 )
 
 from api import PortfoliosHolder, PortfoliosRisk, Navs, RoboExecutor, PortfoliosType, PortfoliosBuilder, RoboReportor, \
-    DatumType, Datum, RebalanceSignal
+    DatumType, Datum, RebalanceSignal, SignalType
 from portfolios.dao import robo_hold_portfolios as rhp
 from portfolios.utils import format_weight
 
@@ -282,7 +282,8 @@ class InvTrustPortfoliosHolder(DividendPortfoliosHolder):
             nav_cals = fund_div_tuple[2]
             share_nav = share
             # 不考虑配息
-            share_nodiv_nav = {x: (1 - funds_subscription_rate[x]) * (fund_av * w) / nav_cals[x] for x, w in weight.items()}
+            share_nodiv_nav = {x: (1 - funds_subscription_rate[x]) * (fund_av * w) / nav_cals[x] for x, w in
+                               weight.items()}
             #  初始买入扣手续费
             fee = sum(funds_subscription_rate[x] * (fund_av * w) for x, w in weight.items())
             fund_av = fund_av - fee
@@ -445,3 +446,38 @@ class DailyHoldReportor(RoboReportor):
                 ['lipper_id', 'asset_ids', 'name', 'weight', 'risk', 'date', 'rebalance_type', 'rebalance_date']]
             return holds.to_dict('records')
         return []
+
+
+@component(bean_name='daily-mpt-report')
+class DailyMptReportor(RoboReportor):
+
+    @autowired
+    def __init__(self, hold: PortfoliosHolder = None, datum: Datum = None):
+        self._hold = hold
+        self._datum = datum
+
+    @property
+    def report_name(self) -> str:
+        return '每日mpt'
+
+    def load_report(self, max_date=prev_workday(dt.today()), min_date=None) -> List[dict]:
+        from portfolios.dao import robo_mpt_portfolios as rmp
+        signals = pd.DataFrame([rmp.get_last_one(type=PortfoliosType.NORMAL,risk=PortfoliosRisk.FT3)])
+        if not signals.empty:
+            datum_ids = reduce(lambda x, y: x | y, signals['portfolio'].apply(lambda x: set(json.loads(x).keys())))
+            datums = pd.DataFrame(self._datum.get_datums(type=DatumType.FUND, datum_ids=datum_ids))
+            datums.set_index('id', inplace=True)
+
+            signals['risk'] = signals.apply(lambda row: PortfoliosRisk(row['risk']).name, axis=1)
+            signals['portfolio'] = signals.apply(lambda row: [x for x in json.loads(row['portfolio']).items()], axis=1)
+            signals = signals.explode('portfolio', ignore_index=True)
+
+            signals['weight'] = signals.apply(lambda row: format(row['portfolio'][1], '.0%'), axis=1)
+            signals['asset_ids'] = signals.apply(lambda row: datums.loc[int(row['portfolio'][0])]['ftTicker'], axis=1)
+            signals['name'] = signals.apply(lambda row: datums.loc[int(row['portfolio'][0])]['chineseName'], axis=1)
+            signals['lipper_id'] = signals.apply(lambda row: datums.loc[int(row['portfolio'][0])]['lipperKey'], axis=1)
+
+            signals = signals[['lipper_id', 'asset_ids', 'name', 'weight', 'risk', 'date']]
+            return signals.to_dict('records')
+
+        return []

rebalance/base_signal.py

@@ -6,7 +6,7 @@ from functools import reduce
 from typing import List
 
 import pandas as pd
-from py_jftech import component, autowired, get_config, prev_workday, workday_range
+from py_jftech import component, autowired, get_config, prev_workday
 from py_jftech import is_workday
 
 from api import PortfoliosBuilder