update

api.py

@@ -297,14 +297,6 @@ class PortfoliosBuilder(ABC):
         '''
         pass
 
-    @abstractmethod
-    def get_all_portfolios(self, risk: PortfoliosRisk = None):
-        """
-        查询所有优选基金
-        @param risk:
-        """
-        pass
-
 
 class Solver(ABC):
     '''

config-svrobo6.yml

@@ -82,6 +82,7 @@ portfolios: # 投组模块
     min-interval-days: 10 # 两次实际调仓最小间隔期，单位交易日
     dividend-rate: 0.09 #设定年化配息率
     dividend-date: 15 #配息日，每月15号
+    dividend-adjust-day: [1,4,7,10]  #每年的首个季度调整配息
     warehouse-frequency: 1  #每隔1个月调一次仓
     redeem-list: [ 'TEUSAAU LX Equity', 'LIGTRAA ID Equity', 'TEMFHAC LX Equity', 'LUSHUAA ID Equity' ] #从持仓中的低风险资产“直接”按序赎回
   solver: # 解算器相关
@@ -231,17 +232,17 @@ reports: # 报告模块相关
         content: "Dear All: 附件是今天生成的监测数据，請驗收，謝謝！ 注>：該郵件為自動發送，如有問題請聯繫矽谷團隊 telan_qian@chifufund.com"
 robo-executor: # 执行器相关
   use: ${ROBO_EXECUTOR:real} # 执行哪个执行器，优先取系统环境变量ROBO_EXECUTOR的值，默认backtest
-  sync-data: ${SYNC_DATA:on} # 是否开启同步资料数据
+  sync-data: ${SYNC_DATA:off} # 是否开启同步资料数据
   backtest: # 回测执行器相关
     start-date: 2022-09-30 # 回测起始日期
-    end-date: 2023-03-01 # 回测截止日期
+    end-date: 2023-07-03 # 回测截止日期
     sealing-period: 10 #调仓封闭期
     start-step: ${BACKTEST_START_STEP:3} # 回测从哪一步开始执行 1:计算资产池；2:计算最优投组：3:计算再平衡信号以及持仓投组
     end-step: ${BACKTEST_END_STEP:3} # 回测从哪一步执行完成后结束执行 1:计算资产池；2:计算最优投组：3:计算再平衡信号以及持仓投组
     clean-up: true
   real: # 实盘执行器
     export: ${EXPORT_ENABLE:on} # 是否开启报告
-    start-date: 2023-01-01 # 实盘开始时间
+    start-date: 2022-09-01 # 实盘开始时间
     include-date: []
 
 

portfolios/builder.py

@@ -4,13 +4,12 @@ from datetime import datetime as dt, timedelta
 from typing import List
 
 import pandas as pd
-from py_jftech import component, autowired, format_date, prev_workday, is_workday
+from py_jftech import component, autowired, format_date, prev_workday, is_workday, get_config
 from pymysql import IntegrityError, constants
 
 from api import PortfoliosBuilder, PortfoliosRisk, AssetPool, Navs, PortfoliosType, Datum, SolveType, SolverFactory, \
     RoboReportor, DatumType
 from portfolios.dao import robo_mpt_portfolios as rmp
-from portfolios.dao.robo_mpt_portfolios import get_list
 
 logger = logging.getLogger(__name__)
 
@@ -27,7 +26,18 @@ class MptPortfoliosBuilder(PortfoliosBuilder):
 
     def get_portfolios(self, day, risk: PortfoliosRisk, type: PortfoliosType = PortfoliosType.NORMAL):
         try:
-            portfolio = rmp.get_one(day, type, risk)
+            # 若记录为空则，将传入日期作为初始日期，进行build
+            portfolio = rmp.get_last_one(day, type, risk)
+            if portfolio:
+                frequency = get_config('portfolios')['holder']['warehouse-frequency']
+                date = pd.to_datetime(day.replace(day=1)) + pd.DateOffset(months=frequency)
+                date = date - timedelta(days=1)
+                # 指定周期末的工作日
+                date = date if is_workday(date) else prev_workday(date)
+                if date == day:
+                    portfolio = None
+                elif portfolio['date'] != day:
+                    return None
             if not portfolio:
                 result = self.build_portfolio(day, type)
                 for build_risk, datas in result.items():
@@ -87,9 +97,6 @@ class MptPortfoliosBuilder(PortfoliosBuilder):
     def clear(self, day=None, risk: PortfoliosRisk = None):
         rmp.delete(min_date=day, risk=risk)
 
-    def get_all_portfolios(self, risk: PortfoliosRisk = None):
-        return get_list(risk=risk)
-
 
 @component(bean_name='poem')
 class PoemPortfoliosBuilder(MptPortfoliosBuilder):
@@ -146,45 +153,6 @@ class SignalReportor(RoboReportor):
         return result
 
 
-@component(bean_name='daily-hold-report')
-class DailyHoldReportor(RoboReportor):
-
-    @autowired
-    def __init__(self, datum: Datum = None):
-        self._datum = datum
-
-    @property
-    def report_name(self) -> str:
-        return '每日持仓信息'
-
-    def load_report(self, max_date=prev_workday(dt.today()), min_date=None) -> List[dict]:
-        # 月初调仓，实际相当于调仓信号在上月月末
-        first_day = max_date.replace(day=1)
-        prev_month = first_day - timedelta(days=1)
-        prev_month.replace(day=prev_month.day)
-        prev_month = prev_month if is_workday(prev_month) else prev_workday(prev_month)
-        portfolio = rmp.get_one(prev_month, type=PortfoliosType.NORMAL, risk=PortfoliosRisk.FT3)
-        result = {}
-        if portfolio:
-            datum_ids = list(json.loads(portfolio['portfolio']).keys())
-            datums = pd.DataFrame(self._datum.get_datums(type=DatumType.FUND, datum_ids=datum_ids))
-            datums.set_index('id', inplace=True)
-
-            result['risk'] = [portfolio['risk'] for i in datum_ids]
-            result['rebalance_type'] = [portfolio['type'] for i in datum_ids]
-
-            result['weight'] = [format(i, '.0%') for i in json.loads(portfolio['portfolio']).values()]
-            result['asset_ids'] = [datums.loc[int(i)]['ftTicker'] for i in datum_ids]
-            result['name'] = [datums.loc[int(i)]['chineseName'] for i in datum_ids]
-            result['lipper_id'] = [datums.loc[int(i)]['lipperKey'] for i in datum_ids]
-            result['date'] = [max_date for i in datum_ids]
-            result['rebalance_date'] = [portfolio['date'] for i in datum_ids]
-            result = pd.DataFrame(result)
-            result = result[
-                ['lipper_id', 'asset_ids', 'name', 'weight', 'risk', 'date', 'rebalance_type', 'rebalance_date']]
-            return result.to_dict('records')
-
-        return []
 
 
 @component(bean_name='daily-signal-report')

portfolios/dao/robo_hold_portfolios.py

@@ -14,6 +14,7 @@ __COLUMNS__ = {
     'rhp_nav': 'nav',
     'rhp_fund_av': 'fund_av',
     'rhp_fund_div': 'fund_div',
+    'rhp_div_forecast': 'div_forecast',
     'rhp_asset_nav': 'asset_nav',
     'rhp_port_div': 'port_div',
     'v_nav_div_acc': 'acc_av',
@@ -40,7 +41,7 @@ def get_one(day, risk: PortfoliosRisk):
 
 @read(one=True)
 def get_last_one(risk: PortfoliosRisk = None, max_date=None, rebalance: bool = None, signal_id=None):
-    sql = "rhp_date <= '{format_date(max_date)}'" if max_date else None
+    sql = f"rhp_date <= '{format_date(max_date)}'" if max_date else None
     return f'''
     select {','.join([f'{x[0]} as {x[1]}' for x in __COLUMNS__.items()])} from robo_hold_portfolios
     {where(sql, rhp_risk=risk, rhp_rrs_id=signal_id, rhp_rebalance=rebalance)}

portfolios/dao/robo_mpt_portfolios.py

@@ -51,3 +51,14 @@ def get_list(max_date=None, min_date=None, type: PortfoliosType = None, risk: Po
     {where(*sqls, rmp_risk=risk, rmp_type=type)}
     order by rmp_date
     '''
+
+@read(one=True)
+def get_last_one(date=None, type: PortfoliosType = None, risk: PortfoliosRisk = None):
+    sqls = []
+    if date:
+        sqls.append(f"rmp_date <= '{format_date(date)}'")
+    return f'''
+    select {','.join([f"{x[0]} as {x[1]}" for x in __COLUMNS__.items()])} from robo_mpt_portfolios
+    {where(*sqls, rmp_risk=risk, rmp_type=type)}
+    order by rmp_date desc limit 1
+    '''
\ No newline at end of file

requirements.txt

@@ -20,3 +20,5 @@ requests==2.28.1
 scipy==1.9.3
 six==1.16.0
 urllib3==1.26.12
+fastapi==0.100.0
+uvicorn==0.23.1
\ No newline at end of file

robo_executor.py

 import logging
 import sys
 from concurrent.futures import wait
-from datetime import datetime as dt, timedelta
+from datetime import datetime as dt
 from typing import List
 
 import pandas as pd
@@ -34,19 +34,17 @@ class BacktestExecutor(RoboExecutor):
         self._config = get_config(__name__)['backtest']
 
     @staticmethod
-    def get_first_business_day(start_date, end_date):
+    def get_last_business_day(start_date, end_date):
         # 生成日期范围并转换为DataFrame
         dates = pd.date_range(start_date, end_date, freq='MS')
-        dates = dates.insert(0, start_date)
         df = pd.DataFrame({'dates': dates})
-        # 提取每个月的第一个工作日
-        df['first_business_day'] = df['dates'].apply(
-            lambda x: pd.date_range(start=x, end=x + pd.offsets.MonthEnd(0), freq='B')[0]
+        df['last_business_day'] = df['dates'].map(
+            lambda date: pd.date_range(start=date, periods=1, freq='BM')[-1]
         )
         # 每隔n个月提取第一个工作日
         result = []
         for i in range(0, len(df), get_config('portfolios')['holder']['warehouse-frequency']):
-            result.append(df.iloc[i]['first_business_day'])
+            result.append(df.iloc[i]['last_business_day'])
         delta = workday_range(result[0], result[1])
         period = get_config(__name__)['backtest']['sealing-period']
         if len(delta) <= period:
@@ -98,7 +96,7 @@ class BacktestExecutor(RoboExecutor):
         if self.start_step.within(BacktestStep.ASSET_POOL) and self.end_step.without(BacktestStep.ASSET_POOL):
             logger.info("start to build asset pool".center(50, '-'))
             now = dt.now()
-            workdays = self.get_first_business_day(self.start_date, self.end_date)
+            workdays = self.get_last_business_day(self.start_date, self.end_date)
             for date in workdays:
                 self._pool.get_pool(date)
                 logger.info(f"build asset pool success, use[{(dt.now() - now).seconds}s]")
@@ -107,7 +105,7 @@ class BacktestExecutor(RoboExecutor):
             logger.info("start to build normal portfolios".center(50, '-'))
             now = dt.now()
             wait([self.async_build_portfolios(day, risk) for risk in PortfoliosRisk for day in
-                  self.get_first_business_day(self.start_date, self.end_date)])
+                  self.get_last_business_day(self.start_date, self.end_date)])
             logger.info(f"build normal portfolios success, use[{(dt.now() - now).seconds}s]")
         if self.start_step.within(BacktestStep.HOLD_PORTFOLIO) and self.end_step.without(BacktestStep.HOLD_PORTFOLIO):
             logger.info("start to build hold portfolios".center(50, '-'))
@@ -181,18 +179,8 @@ class RealExecutor(RoboExecutor):
             for risk in PortfoliosRisk:
                 logger.info(f"start to build risk[{risk.name}] real for date[{format_date(date)}]".center(50, '-'))
                 now = dt.now()
-                first_day = date.replace(day=1)
-                prev_month = first_day - timedelta(days=1)
-                prev_month.replace(day=prev_month.day)
-                prev_month = prev_month if is_workday(prev_month) else prev_workday(prev_month)
-                self._pool.get_pool(prev_month)
-                self._builder.get_portfolios(prev_month, risk)
-                next_month = date.replace(day=28) + timedelta(days=4)
-                prev_month = next_month.replace(day=1) - timedelta(days=1)
-                prev_month = prev_month if is_workday(prev_month) else prev_workday(prev_month)
-                if date.day == prev_month.day:
-                    self._pool.get_pool(date)
-                    self._builder.get_portfolios(date, risk)
+                # 更新持仓
+                self._hold.build_hold_portfolio(date, risk)
                 logger.info(
                     f"build risk[{risk.name}] real for date[{format_date(date)}] success, use[{(dt.now() - now).seconds}s]")
             if self.export:

web/robo_controller.py

+import uvicorn
+from fastapi import FastAPI
+
+app = FastAPI()
+
+REC_GID = 'E3886FBA-123B-7890-123E-123456BEEED'
+
+
+@app.get("/recommend")
+async def root():
+    rec_list = []
+    portfolios = {'recomm_guid': REC_GID}
+    data = {'recomm_guid': REC_GID}
+    data['data_date'] = '2019-09-20'
+    data['funds'] = [
+        {'weight': '5', 'fund_id': '0152'}
+    ]
+    portfolios['data'] = data
+    rec_list.append(portfolios)
+    return rec_list
+
+
+if __name__ == "__main__":
+    uvicorn.run("robo_controller:app", reload=True, port=8080)