实盘完成

api.py

@@ -99,7 +99,7 @@ class Datum(ABC):
     '''
 
     @abstractmethod
-    def get_datums(self, type: DatumType = None, crncy=None, risk=None, datum_ids=None, ticker=None):
+    def get_datums(self, type: DatumType = None, crncy=None, risk=None, datum_ids=None, ticker=None, exclude=True):
         '''
         获取资料信息，当id和ticker都有时，取二者并集
         :param type: 资料类型
@@ -107,6 +107,7 @@ class Datum(ABC):
         :param risk: 风险等级，仅对基金资料有效
         :param datum_ids: 资料ID列表
         :param ticker: 资料ticker列表
+        :param exclude: 是否排除过滤的资料，默认为True
         :return: 资料信息数据
         '''
         pass
@@ -120,6 +121,15 @@ class Datum(ABC):
         '''
         pass
 
+    @abstractmethod
+    def update_change(self, date):
+        '''
+        在指定对日期，执行资料变更，如果有变更则返回True, 否则返回False，注意，改方法非幂等，变更后无法复原
+        :param date: 执行变更的日期
+        :return: 如果有变更则返回True，否则返回False
+        '''
+        pass
+
 
 class Navs(ABC):
     '''

asset_pool/asset_optimize.py

@@ -43,9 +43,12 @@ class SortinoAssetOptimize(AssetOptimize, ABC):
         return pct_change.columns[sortino.index[0]]
 
     def get_optimize_pool(self, day):
+        opt_pool = rop.get_one(day=day, type=AssetPoolType.OPTIMIZE)
+        if opt_pool is not None:
+            return json.loads(opt_pool['asset_ids'])
         last_one = rop.get_last_one(day=day, type=AssetPoolType.OPTIMIZE)
         start = get_quarter_start(day or dt.today())
-        if not last_one or start > last_one['date'] or self.has_incept_asset(last_one['date'] + timedelta(1), day):
+        if not last_one or start > last_one['date'] or self.has_incept_asset(last_one['date'] + timedelta(1), day) or self.has_change(day):
             pool = []
             min_dates = self.nav_min_dates
             max_incept_date = sorted([(day - relativedelta(**x)) for x in self.delta_kwargs])[0]
@@ -86,6 +89,10 @@ class SortinoAssetOptimize(AssetOptimize, ABC):
         '''
         pass
 
+    @abstractmethod
+    def has_change(self, day):
+        return False
+
 
 @component
 class FundSortinoAssetOptimize(SortinoAssetOptimize):
@@ -108,6 +115,9 @@ class FundSortinoAssetOptimize(SortinoAssetOptimize):
         end_date = sorted([(end_date - relativedelta(**x)) for x in self.delta_kwargs])[0]
         return len([x for x in self.nav_min_dates.items() if start_date <= x[1] <= end_date]) > 0
 
+    def has_change(self, day):
+        return self._datum.update_change(day)
+
     def get_groups(self):
         funds = pd.DataFrame(self._datum.get_datums(type=DatumType.FUND))
         min_dates = self._navs.get_nav_start_date()

basic/dao/robo_base_datum.py

-from py_jftech import read, where, to_tuple
+from py_jftech import read, where, to_tuple, write
 
 from api import DatumType
 
@@ -13,3 +13,8 @@ def get_base_datums(type: DatumType = None, crncy=None, risk=None, datum_ids=Non
         'v_rbd_bloomberg_ticker': to_tuple(ticker)
     }
     return f'''select rbd_id as id, rbd_datas as datas from robo_base_datum {where(**kwargs)}'''
+
+
+@write
+def update_datum(id, datas: str):
+    return f'''update robo_base_datum set rbd_datas = '{datas}' where rbd_id = {id}'''

basic/datum.py

 import json
+import os
 from datetime import datetime as dt
 from typing import List
 
 import pandas as pd
-from py_jftech import component, parse_date, get_config, to_tuple, autowired
+from py_jftech import component, parse_date, get_config, to_tuple, autowired, get_project_path, transaction
 
-from api import DatumType, Datum, PortfoliosRisk, RoboReportor
+from api import DatumType, Datum, PortfoliosRisk, RoboReportor, RoboExecutor
 from basic.dao import robo_base_datum as rbd
 
 
@@ -17,7 +18,27 @@ class DefaultDatum(Datum):
 
     @property
     def excludes(self):
-        return self._config['excludes'] if 'excludes' in self._config else []
+        excludes = self._config['excludes'] if 'excludes' in self._config else []
+        if isinstance(excludes, dict):
+            excludes = excludes[RoboExecutor.use_name()] if RoboExecutor.use_name() in excludes else []
+        return excludes
+
+    @property
+    def change_date(self):
+        change = self._config['change'] if 'change' in self._config else {}
+        return pd.to_datetime(change['date']) if 'date' in change else None
+
+    @property
+    def change_file(self):
+        change = self._config['change'] if 'change' in self._config else {}
+        if 'file' not in change or change['file'] is None:
+            return None
+        file_path: str = change['file']
+        if file_path.startswith('.'):
+            return os.path.abspath(os.path.join(os.path.dirname(__file__), file_path))
+        elif file_path.startswith('/'):
+            return os.path.abspath(file_path)
+        return os.path.abspath(os.path.join(get_project_path(), file_path))
 
     def format_datum(self, datum):
         if DatumType(datum['type']) is DatumType.FUND:
@@ -27,14 +48,14 @@ class DefaultDatum(Datum):
             }
         return datum
 
-    def get_datums(self, type: DatumType = None, crncy=None, risk=None, datum_ids=None, ticker=None):
+    def get_datums(self, type: DatumType = None, crncy=None, risk=None, datum_ids=None, ticker=None, exclude=True):
         datum_ids = to_tuple(datum_ids)
         if ticker:
             datums = rbd.get_base_datums(type=type, ticker=ticker)
             datum_ids = tuple(set(datum_ids or []) | {x['id'] for x in datums})
         result = rbd.get_base_datums(type=type, crncy=crncy, risk=risk, datum_ids=datum_ids)
         result = [{**json.loads(x['datas']), 'id': x['id']} for x in result]
-        return [self.format_datum(x) for x in result if DatumType(x['type']) is not DatumType.FUND or x['bloombergTicker'] not in self.excludes]
+        return [self.format_datum(x) for x in result if not exclude or x['bloombergTicker'] not in self.excludes]
 
     def get_high_risk_datums(self, risk: PortfoliosRisk):
         risk3 = self.get_datums(type=DatumType.FUND, risk=3)
@@ -47,6 +68,19 @@ class DefaultDatum(Datum):
             return risk3 + self.get_datums(type=DatumType.FUND, risk=(4, 5))
         return None
 
+    @transaction
+    def update_change(self, date):
+        if self.change_date is not None and self.change_date == pd.to_datetime(date):
+            if self.change_file is not None:
+                for fund in pd.read_excel(self.change_file).to_dict('records'):
+                    db_data = rbd.get_base_datums(ticker=fund['bloombergTicker'])
+                    rbd.update_datum(db_data['id'], json.dumps({
+                        **json.loads(db_data['datas']),
+                        **fund
+                    }))
+            return True
+        return False
+
 
 @component(bean_name='funds-report')
 class FundReportor(RoboReportor):
@@ -62,5 +96,6 @@ class FundReportor(RoboReportor):
     def load_report(self, max_date=dt.today(), min_date=None) -> List[dict]:
         datums = self._datum.get_datums(type=DatumType.FUND)
         datums = pd.DataFrame(datums)
-        datums = datums[['id', 'ftTicker', 'bloombergTicker', 'chineseName', 'englishName', 'lipperKey', 'isin', 'currency', 'risk', 'inceptDate', 'category', 'assetType']]
+        datums = datums[
+            ['id', 'ftTicker', 'bloombergTicker', 'chineseName', 'englishName', 'lipperKey', 'isin', 'currency', 'risk', 'inceptDate', 'category', 'assetType']]
         return datums.to_dict('records')

basic/test_case.py

@@ -2,7 +2,6 @@ import logging
 import unittest
 from typing import List
 
-import pandas as pd
 from py_jftech import autowired, parse_date, to_str
 
 from api import Navs, Datum, PortfoliosRisk, DataSync, RoboReportor

config.yml

@@ -35,6 +35,12 @@ py-jftech:
     user: ${MYSQL_USER:root}
     password: ${MYSQL_PWD:123456}
     dbname: ${MYSQL_DBNAME:jftech_robo}
+  database-2:
+    host: 106.14.56.221
+    port: 3306
+    user: robo_user
+    password: robo2.1@20220521
+    dbname: robo_ft_fund_real
   injectable:
     types:
       api.PortfoliosBuilder: portfolios.builder.PoemPortfoliosBuilder
@@ -48,15 +54,34 @@ basic: # 基础信息模块
   sync:
     start-date: 2007-01-01 # 同步数据开始日期
   datum: # 资料模块
+    change:
+      date: ${DATUM_CHANGE_DATE}
+      file: ${DATUM_CHANGE_FILE}
     excludes: # 排除的资料彭博ticker
-      - 'FKUQX US Equity'
-      - 'FTAAUSH LX Equity'
-      - 'FTJAPAU LX Equity'
-      - 'TEGAUH1 LX Equity'
-      - 'TMEEAAU LX Equity'
-      - 'TEUSAAU LX Equity'
-      - 'FTEAUH1 LX Equity'
-      - 'TFIAAUS LX Equity'
+      backtest:
+        - 'FKUQX US Equity'
+        - 'FTAAUSH LX Equity'
+        - 'FTJAPAU LX Equity'
+        - 'TEGAUH1 LX Equity'
+        - 'TMEEAAU LX Equity'
+        - 'TEUSAAU LX Equity'
+        - 'FTEAUH1 LX Equity'
+        - 'TFIAAUS LX Equity'
+      real:
+        - 'FGFSACU LX Equity'
+        - 'TMEEAAU LX Equity'
+        - 'FTEAMUH LX Equity'
+        - 'FKUTX US Equity'
+        - 'TEMUSGI LX Equity'
+        - 'TEMFIAI LX Equity'
+        - 'TEMGROA LX Equity'
+        - 'TEMFMEA LX Equity'
+        - 'TEMDGAA LX Equity'
+        - 'TEMJAAU LX Equity'
+        - 'TEMFHAC LX Equity'
+        - 'TEMLATA LX Equity'
+        - 'LEPEUAA ID Equity'
+        - 'LGBOAAU ID Equity'
   navs: # 净值模块
     exrate: # 汇率，如果不开启，整个这块注释掉
       - from: EUR # 需要转换的货币类型
@@ -139,7 +164,7 @@ rebalance: # 再平衡模块
   signals: # 信号相关
     crisis-signal: # 危机信号相关
       exp-years: 3 # 预警期时长，单位自然年，点到点计算
-      exp-init: 2008-01-01 # 设置起始危机预警开始时间，如果关闭初始预警起，注释到这一条即可
+      exp-init: 2022-03-04 # 设置起始危机预警开始时间，如果关闭初始预警起，注释到这一条即可
       inversion-years: 1 # 利率倒挂计算时长，单位自然年，点到点取值
       inversion-threshold: 0.3 # 利率倒挂触发阀值
       crisis-1: # 危机1相关
@@ -211,7 +236,7 @@ reports: # 报告模块相关
   backtest: # 回测导出曹策略
     exist-build: on # 如果报告文件存在，是否重新构建文件
     save-path: ${EXPORT_PATH:excels} # 导出报告文件存放路径，如果以./或者../开头，则会以执行python文件为根目录，如果以/开头，则为系统绝对路径，否则，以项目目录为根目录
-    file-name: ${EXPORT_FILENAME:1323}
+    file-name: ${EXPORT_FILENAME:real}
     include-report: # 需要导出的报告类型列表，下面的顺序，也代表了excel中sheet的顺序
 #      - funds-report # 基金资料
 #      - navs-report # 净值报告
@@ -224,16 +249,16 @@ reports: # 报告模块相关
       - fixed-range-report # 固定区间收益报告
       - relative-range-report # 相对区间收益报告
 robo-executor: # 执行器相关
-  use: ${ROBO_EXECUTOR:backtest} # 执行哪个执行器，优先取系统环境变量ROBO_EXECUTOR的值，默认backtest
+  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:off} # 是否开启同步资料数据
   backtest: # 回测执行器相关
-    start-date: 2008-01-02 # 回测起始日期
-    end-date: 2022-11-01 # 回测截止日期
+    start-date: 2022-09-01 # 回测起始日期
+    end-date: 2023-02-20 # 回测截止日期
     start-step: ${BACKTEST_START_STEP:4} # 回测从哪一步开始执行 1:计算资产ewma；2:计算资产池；3:计算最优投组：4:计算再平衡信号以及持仓投组
     end-step: ${BACKTEST_END_STEP:4} # 回测从哪一步执行完成后结束执行 1:计算资产ewma；2:计算资产池；3:计算最优投组：4:计算再平衡信号以及持仓投组
-    clean-up: on
+    clean-up: off
   real: # 实盘执行器
-    start-date: 2022-11-01 # 实盘开始时间
+    start-date: 2022-09-01 # 实盘开始时间
     include-date:
       - 2023-02-18
       - 2023-03-25

portfolios/test_case.py

@@ -29,7 +29,7 @@ class PortfoliosTest(unittest.TestCase):
 
     @autowired(names={'hold': 'next-re'})
     def test_build_hold(self, hold: PortfoliosHolder = None):
-        hold.build_hold_portfolio(parse_date('2022-11-01'), PortfoliosRisk.FT9)
+        hold.build_hold_portfolio(parse_date('2023-02-23'), PortfoliosRisk.FT9)
 
     @autowired(names={'reportor': 'hold-report'})
     def test_hold_report(self, reportor: RoboReportor = None):

rebalance/test_case.py

 import logging
 import unittest
-from dateutil.relativedelta import relativedelta
 
+from dateutil.relativedelta import relativedelta
 from py_jftech import autowired, parse_date, to_str, next_workday
 
 from api import RebalanceSignal, PortfoliosRisk, RebalanceRuler, RoboReportor

robo_executor.py

@@ -174,18 +174,17 @@ class RealExecutor(RoboExecutor):
             for sync in self._syncs:
                 sync.do_sync()
         date = self.curt_date
-        for date in pd.date_range(start='2008-01-17', end='2008-01-20'):
-            if is_workday(date) or date in self.include_date:
-                date = prev_workday(date)
-                for risk in PortfoliosRisk:
-                    logger.info(f"start to build risk[{risk.name}] real for date[{format_date(date)}]".center(50, '-'))
-                    now = dt.now()
-                    # 因为每天都必须有NORMAL最优投组，不管用不用
-                    self._builder.get_portfolios(date, risk)
-                    self._hold.build_hold_portfolio(date, risk)
-                    self._ruler.take_next_signal(date, risk)
-                    # 如果当前持仓为风控投组，则还要计算风控投组，不管用不用
-                    p_type = self._hold.get_portfolio_type(date, risk)
-                    if p_type is not PortfoliosType.NORMAL:
-                        self._builder.get_portfolios(date, risk, type=p_type)
-                    logger.info(f"build risk[{risk.name}] real for date[{format_date(date)}] success, use[{(dt.now() - now).seconds}s]")
+        if is_workday(date) or date in self.include_date:
+            date = prev_workday(date)
+            for risk in PortfoliosRisk:
+                logger.info(f"start to build risk[{risk.name}] real for date[{format_date(date)}]".center(50, '-'))
+                now = dt.now()
+                # 因为每天都必须有NORMAL最优投组，不管用不用
+                self._builder.get_portfolios(date, risk)
+                self._hold.build_hold_portfolio(date, risk)
+                self._ruler.take_next_signal(date, risk)
+                # 如果当前持仓为风控投组，则还要计算风控投组，不管用不用
+                p_type = self._hold.get_portfolio_type(date, risk)
+                if p_type is not PortfoliosType.NORMAL:
+                    self._builder.get_portfolios(date, risk, type=p_type)
+                logger.info(f"build risk[{risk.name}] real for date[{format_date(date)}] success, use[{(dt.now() - now).seconds}s]")