量化策略---自定义股票池，红利策略创新高，收益14%，最大回撤1%，提供策略源代码_from ths.thstrader import thstrader-优快云博客

本文链接：https://blog.youkuaiyun.com/qq_50882340/article/details/138979286
内容全部的策略交易的结果，不做投资参考
链接量化策略---自定义股票池，红利策略创新高，收益14%，最大回撤1%，提供策略源代码 (qq.com)
今天量化策略创新高。2个月没有手动了，全部程序交易，程序24小时运行的效果
2个策略同时运行，最大回撤1%,严格止盈止损，趋势轮动
4个月程序运行的结果，不断升级，现在已经很完善了
这一路写下来真不容易，去年6月毕业，去bigquant实习的时候有想法写一套自己的量化交易系统，一年的努力，不知不觉一年过去了，基本的功能差不多了，后面就是完善细节，添加功能，源代码全部上传了知识星球，可以直接用
可以加我备注加群，一起研究策略，完善策略
策略全部源代码
from trader_tool.stock_data import stock_datafrom trader_tool.bond_cov_data import bond_cov_datafrom trader_tool.shape_analysis import shape_analysisfrom trader_tool.analysis_models import analysis_modelsimport pandas as pdfrom trader_tool.ths_rq import ths_rqfrom tqdm import tqdmimport numpy as npimport jsonfrom  trader_tool import jsl_datafrom qmt_trader.qmt_trader_ths import qmt_trader_thsfrom xgtrader.xgtrader import xgtraderfrom trader_tool.ths_rq import ths_rqfrom trader_tool.ths_board_concept_data import ths_board_concept_datafrom trader_tool.unification_data import unification_dataimport osimport pandas as pdfrom trader_tool.dfcf_etf_data import dfcf_etf_data#债券模型from trader_models.custom_bond_trend_rotation_strategy.custom_bond_trend_rotation_strategy import custom_bond_trend_rotation_strategyclass customize_trading_strategies:    def __init__(self,trader_tool='ths',exe='C:/同花顺软件/同花顺/xiadan.exe',tesseract_cmd='C:/Program Files/Tesseract-OCR/tesseract',                qq='1029762153@qq.com',open_set='否',qmt_path='D:/国金QMT交易端模拟/userdata_mini',                qmt_account='55009640',qmt_account_type='STOCK',name='customize_trading_strategies'):        '''        分析模型        '''        self.exe=exe        self.tesseract_cmd=tesseract_cmd        self.qq=qq        self.trader_tool=trader_tool        self.open_set=open_set        self.qmt_path=qmt_path        self.qmt_account=qmt_account        self.qmt_account_type=qmt_account_type        if trader_tool=='ths':            self.trader=xgtrader(exe=self.exe,tesseract_cmd=self.tesseract_cmd,open_set=open_set)        else:            self.trader=qmt_trader_ths(path=qmt_path,account=qmt_account,account_type=qmt_account_type)        self.stock_data=stock_data()        self.bond_cov_data=bond_cov_data()        self.ths_rq=ths_rq()        self.path=os.path.dirname(os.path.abspath(__file__))        self.ths_board_concept_data=ths_board_concept_data()        self.name=name        self.data=unification_data(trader_tool=self.trader_tool)        self.data=self.data.get_unification_data()        self.dfcf_etf_data=dfcf_etf_data()        self.trader.connect()    def save_position(self):        '''        保存持股数据        '''        with open(r'分析配置.json',encoding='utf-8') as f:            com=f.read()        text=json.loads(com)        del_df=pd.read_excel(r'{}\黑名单\黑名单.xlsx'.format(self.path),dtype='object')        del_trader_stock=text['黑名单']        if del_df.shape[0]>0:            del_df['证券代码']=del_df['证券代码'].apply(lambda x : str(x).split('.')[0])            del_df['证券代码']=del_df['证券代码'].apply(lambda x: '0'*(6-len(str(x)))+str(x))            del_stock_list=del_df['证券代码'].tolist()        else:            del_stock_list=[]        for del_stock in del_trader_stock:            del_stock_list.append(del_stock)        trader_type=text['交易品种']        def select_del_stock_list(x):            if str(x)[:6] in del_stock_list:                return '是'            else:                return '否'        df=self.trader.position()        try:            if df==False:                print('获取持股失败')        except:            if df.shape[0]>0:                if trader_type=='全部':                    df=df                else:                    df['选择']=df['证券代码'].apply(self.trader.select_data_type)                    df=df[df['选择']==trader_type]                print(df)                df=df[df['可用余额']>=10]                df['黑名单']=df['证券代码'].apply(select_del_stock_list)                df=df[df['黑名单']=='否']                print('剔除黑名单**********')                df.to_excel(r'持股数据\持股数据.xlsx')                return df            else:                df=pd.DataFrame()                df['账号类型']=None                df['资金账号']=None                df['证券代码']=None                df['股票余额']=None                df['可用余额']=None                df['成本价']=None                df['市值']=None                df['选择']=None                df['持股天数']=None                df['交易状态']=None                df['明细']=None                df['证券名称']=None                df['冻结数量']=None                df['市价']=None                  df['盈亏']=None                df['盈亏比(%)']=None                df['当日买入']=None                  df['当日卖出']=None                df.to_excel(r'持股数据\持股数据.xlsx')                return df    def save_balance(self):        '''        保持账户数据        '''        df=self.trader.balance()        df.to_excel(r'账户数据\账户数据.xlsx')        return df    def mean_line_models(self,df):        '''        均线模型        趋势模型        5，10，20，30，60        '''        df=df        #df=self.bond_cov_data.get_cov_bond_hist_data(stock=stock,start=start_date,end=end_date,limit=1000000000)        df1=pd.DataFrame()        df1['date']=df['date']        df1['5']=df['close'].rolling(window=5).mean()        df1['10']=df['close'].rolling(window=10).mean()        df1['20']=df['close'].rolling(window=20).mean()        df1['30']=df['close'].rolling(window=30).mean()        df1['60']=df['close'].rolling(window=60).mean()        score=0        #加分的情况        mean_5=df1['5'].tolist()[-1]        mean_10=df1['10'].tolist()[-1]        mean_20=df1['20'].tolist()[-1]        mean_30=df1['30'].tolist()[-1]        mean_60=df1['60'].tolist()[-1]        #相邻2个均线进行比较        if mean_5>mean_10:            score+=25        if mean_10>mean_20:            score+=25        if mean_20>mean_30:            score+=25        if mean_30>mean_60:            score+=25        return score    def get_del_buy_sell_data(self):        '''        处理交易股票池买入股票        '''        with open(r'{}\自定义股票池策略.json'.format(self.path),encoding='utf-8') as f:            com=f.read()        text=json.loads(com)        limit=text['持股限制']        n=text['自定义交易品种跌破N日均线卖出']        max_yjl=text['ETF溢价率上限']        min_yjl=text['ETF溢价率下限']        buy_min_srore=text['买入最低分']        df=pd.read_excel(r'持股数据\持股数据.xlsx',dtype='object')        df1=df[df['股票余额']>=10]        df1['证券代码']=df1['证券代码'].astype(str)        hold_stock_list=df1['证券代码'].tolist()        trader_df=pd.read_excel(r'{}\自定义交易股票池\自定义交易股票池.xlsx'.format(self.path),dtype='object')        print('原始自定义交易股票池****************')        print(trader_df)        trader_df['证券代码']=trader_df['证券代码'].astype(str)        def select_data(stock):            if str(stock) in hold_stock_list:                return '持股超过限制'            else:                return '没有持股'        trader_df['持股检查']=trader_df['证券代码'].apply(select_data)        trader_df=trader_df[trader_df['持股检查'] !='持股超过限制']        print('处理原始自定义交易股票池****************')        print(trader_df)        #再次处理        is_buffer=text['是否开启策略缓冲区']        deviation_mean=text['偏离均线']        deviation_up_spot=text['买入时候的偏离度']        deviation_down_spot=text['跌破偏离线下穿N点卖出']        minimum_guarantee=text['买入保底均线']        n=text['自定义交易品种跌破N日均线卖出']        max_zdf=text['最大涨跌幅']        min_zdf=text['最小涨跌幅']        trader_list=trader_df['证券代码'].tolist()        zdf_list=[]        sell_list=[]        if is_buffer=='是':            print("开启策略缓冲区**************")            for stock in trader_list:                try:                    #偏离                    hist=self.data.get_hist_data_em(stock=stock)                    zdf=hist['涨跌幅'].tolist()[-1]                    zdf_list.append(zdf)                    price=hist['close'].tolist()[-1]                    hist['mean_line']=hist['close'].rolling(window=deviation_mean).mean()                    line=hist['mean_line'].tolist()[-1]                    deviation=((price-line)/line)*100                    print('{} {}价格 {}日均线{} 偏离度{}'.format(stock,price,deviation_mean,line,deviation))                    models=shape_analysis(df=hist)                    mean_line=models.get_down_mean_line_sell(n=n)                    minimum=models.get_down_mean_line_sell(n=minimum_guarantee)                    if minimum=='是':                        print('{} 跌破保底均线{} 卖出'.format(stock,minimum_guarantee))                        sell_list.append(stock)                    elif deviation>0 and deviation>=deviation_up_spot:                        print('{} 偏离{}均线并且 偏离{} 偏离向上缓冲区{}'.format(stock,n,deviation,deviation_up_spot))                        sell_list.append(stock)                    elif mean_line=='是':                        print('{} 跌破均线{} 进入缓冲区分析'.format(n,stock))                        if deviation<=0 and abs(deviation)>=deviation_down_spot:                            print('{} 跌破{}均线并且 下穿{} 跌破向下缓冲区{}'.format(stock,n,deviation,deviation_down_spot))                            sell_list.append(stock)                        else:                            print('{} 正常{}均线并且 偏离{} 偏离在正常的缓冲区{}'.format(stock,n,deviation,deviation_down_spot))                    else:                        print('{} 符合缓冲区要求'.format(stock))                except:                    print('{} 缓冲区处理有问题'.format(stock))                    zdf_list.append(None)            trader_df['涨跌幅']=zdf_list            trader_df=trader_df[trader_df['涨跌幅']>=min_zdf]            trader_df=trader_df[trader_df['涨跌幅']<=max_zdf]            trader_df['缓冲区']=trader_df['证券代码'].apply(lambda x: '是' if x in sell_list else '不是')            trader_df=trader_df[trader_df['缓冲区']=='不是']            print('处理的交易股票池********************')            print(trader_df)            trader_list=trader_df['证券代码'].tolist()            sell_list=[]            mean_score_list=[]            for stock in trader_list:                try:                    hist_df=self.data.get_hist_data_em(stock=stock)                    score=self.mean_line_models(df=hist_df)                    mean_score_list.append(score)                    models=shape_analysis(df=hist_df)                    mean_line=models.get_down_mean_line_sell(n=n)                    if mean_line=='是':                        sell_list.append('是')                    else:                        sell_list.append('不是')                except:                    print('{}有问题--处理交易股票池买入股票'.format(stock))                    mean_score_list.append(None)                    sell_list.append('是')            trader_df['均线得分']=mean_score_list             trader_df=trader_df[trader_df['均线得分']>=buy_min_srore]            fund=self.dfcf_etf_data.get_all_etf_data_1()            yjl_dict=dict(zip(fund['基金代码'].tolist(),fund['溢价率'].tolist()))            trader_df['溢价率']=trader_df['证券代码'].apply(lambda x :yjl_dict.get(str(x),0))            print('00000000000000000000000000000000000000')            trader_df=trader_df[trader_df['溢价率']<=max_yjl]            trader_df=trader_df[trader_df['溢价率']>=min_yjl]            trader_df.to_excel(r'买入股票\买入股票.xlsx')        else:            zdf_list=[]            print('不开启策略缓冲区**********************')            trader_df=pd.read_excel(r'自定义交易股票池\自定义交易股票池.xlsx',dtype='object')            trader_df['证券代码']=trader_df['证券代码'].astype(str)            df=pd.read_excel(r'持股数据\持股数据.xlsx',dtype='object')            df1=df[df['股票余额']>=10]            df1['证券代码']=df1['证券代码'].astype(str)            hold_stock_list=df1['证券代码'].tolist()            def select_data(stock):                if stock in hold_stock_list:                    return '持股超过限制'                else:                    return '没有持股'            trader_df['持股检查']=trader_df['证券代码'].apply(select_data)            trader_df=trader_df[trader_df['持股检查'] !='持股超过限制']            hold_stock_list=trader_df['证券代码'].tolist()            sell_list=[]            mean_score_list=[]            for stock in hold_stock_list:                try:                    hist_df=self.data.get_hist_data_em(stock=stock)                    zdf=hist_df['涨跌幅'].tolist()[-1]                    zdf_list.append(zdf)                    score=self.mean_line_models(df=hist_df)                    mean_score_list.append(score)                    models=shape_analysis(df=hist_df)                    mean_line=models.get_down_mean_line_sell(n=n)                    if mean_line=='是':                        sell_list.append('是')                    else:                        sell_list.append('不是')                except:                    print('{}有问题--处理交易股票池买入股票'.format(stock))                    mean_score_list.append(None)                    sell_list.append('是')                    zdf_list.append(None)            trader_df['涨跌幅']=zdf_list            trader_df['跌破均线']=sell_list            trader_df['均线得分']=mean_score_list            trader_df=trader_df[trader_df['涨跌幅']>=min_zdf]            trader_df=trader_df[trader_df['涨跌幅']<=max_zdf]            trader_df=trader_df[trader_df['跌破均线']=='不是']              trader_df=trader_df[trader_df['均线得分']>=buy_min_srore]            fund=self.dfcf_etf_data.get_all_etf_data_1()            yjl_dict=dict(zip(fund['基金代码'].tolist(),fund['溢价率'].tolist()))            trader_df['溢价率']=trader_df['证券代码'].apply(lambda x :yjl_dict.get(str(x),0))            print('00000000000000000000000000000000000000')            trader_df=trader_df[trader_df['溢价率']<=max_yjl]            trader_df=trader_df[trader_df['溢价率']>=min_yjl]            print(trader_df)            is_buy=text['是否开启当日卖出买回']            if is_buy=='是':                trader_df.to_excel(r'买入股票\买入股票.xlsx')            else:                today_trades=self.trader.today_trades()                if today_trades.shape[0]>0:                    trader_list=today_trades['证券代码'].tolist()                    trader_df['今日成交']=trader_df['证券代码'].apply(lambda x: '是' if x in trader_list else '不是')                    trader_df=trader_df[trader_df['今日成交']=='不是']                    trader_df.to_excel(r'买入股票\买入股票.xlsx')                else:                    print('当日没有委托）））））））））））））））））））')            return trader_df    def get_buy_sell_stock(self):        '''        获取买卖数据        '''        with open(r'{}\自定义股票池策略.json'.format(self.path),encoding='utf-8') as f:            com=f.read()        text=json.loads(com)        buy_num=text['买入前N']        hold_limit=text['持有限制']        df=pd.read_excel(r'持股数据\持股数据.xlsx',dtype='object')        hold_min_score=text['自定义交易品种持有分数']        df1=df[df['可用余额']>=10]        hold_stock_list=df['证券代码'].tolist()        def select_stock(x):            '''            选择股票            '''            if x in hold_stock_list:                return '持股超过限制'            else:                return "持股不足"        try:            del df['Unnamed: 0']        except:            pass        trader_df=pd.read_excel(r'买入股票\买入股票.xlsx',dtype='object')        try:            del trader_df['Unnamed: 0']        except:            pass        sell_df=pd.read_excel(r'卖出股票\卖出股票.xlsx')        sell_list=[]        trader_df['选择']=trader_df['证券代码'].apply(select_stock)        trader_df=trader_df[trader_df['选择']!='持股超过限制']        if True:            if df1.shape[0]>0:                #卖出列表                #持股列表                hold_stock_list=df['证券代码'].tolist()                #对持有的可转债做均线分析                for stock in hold_stock_list:                    try:                        bond_data=self.data.get_hist_data_em(stock=stock)                        socre=self.mean_line_models(df=bond_data)                        if socre<hold_min_score:                            print('{} {}分数不符合最低{}分'.format(stock,socre,hold_min_score))                            sell_list.append(stock)                        else:                            print('{}符合最低分{}'.format(stock,hold_min_score))                    except:                        print('{}卖出数据有问题'.format(stock))                #跌破均线分析                '''                for stock in hold_stock_list:                        try:                            hist_df=self.data.get_hist_data_em(stock=stock)                            models=shape_analysis(df=hist_df)                            mean_line=models.get_down_mean_line_sell(n=n)                            if mean_line=='是':                                sell_list.append(stock)                                print('{}跌破均线'.format(stock))                            else:                                pass                        except:                            pass                '''                #再次处理                is_buffer=text['是否开启策略缓冲区']                deviation_mean=text['偏离均线']                deviation_up_spot=text['向上偏离N点卖出']                deviation_down_spot=text['跌破偏离线下穿N点卖出']                minimum_guarantee=text['偏离保底均线N卖出']                n=text['自定义交易品种跌破N日均线卖出']                if is_buffer=='是':                    print("开启策略缓冲区**************")                    for stock in hold_stock_list:                        try:                            #偏离                            hist=self.data.get_hist_data_em(stock=stock)                            price=hist['close'].tolist()[-1]                            hist['mean_line']=hist['close'].rolling(window=deviation_mean).mean()                            line=hist['mean_line'].tolist()[-1]                            deviation=((price-line)/line)*100                            print('{} {}价格 {}日均线{} 偏离度{}'.format(stock,price,deviation_mean,line,deviation))                            models=shape_analysis(df=hist)                            mean_line=models.get_down_mean_line_sell(n=n)                            minimum=models.get_down_mean_line_sell(n=minimum_guarantee)                            if minimum=='是':                                print('{} 跌破保底均线{} 卖出'.format(stock,minimum_guarantee))                                sell_list.append(stock)                            elif deviation>0 and deviation>=deviation_up_spot:                                print('{} 偏离{}均线并且 偏离{} 偏离向上缓冲区{}'.format(stock,n,deviation,deviation_up_spot))                                sell_list.append(stock)                            elif mean_line=='是':                                print('{} 跌破均线{} 进入缓冲区分析'.format(n,stock))                                if deviation<=0 and abs(deviation)>=deviation_down_spot:                                    print('{} 跌破{}均线并且 下穿{} 跌破向下缓冲区{}'.format(stock,n,deviation,deviation_down_spot))                                    sell_list.append(stock)                                else:                                    print('{} 正常{}均线并且 偏离{} 偏离在正常的缓冲区{}'.format(stock,n,deviation,deviation_down_spot))                            else:                                print('{} 符合缓冲区要求'.format(stock))                        except:                            print('{} 缓冲区处理有问题'.format(stock))                else:                    print('不开启策略缓冲区**********************')                    for stock in hold_stock_list:                        try:                            hist_df=self.data.get_hist_data_em(stock=stock)                            models=shape_analysis(df=hist_df)                            mean_line=models.get_down_mean_line_sell(n=n)                            if mean_line=='是':                                sell_list.append(stock)                                print('{}跌破均线'.format(stock))                            else:                                pass                        except:                            print('不开启策略缓冲区{}有问题'.format(stock))                #溢价率自动平仓                fund=self.dfcf_etf_data.get_all_etf_data_1()                yjl_dict=dict(zip(fund['基金代码'].tolist(),fund['溢价率'].tolist()))                is_yjl=text['是否开启溢价率平仓']                max_yjl=text['平仓溢价率']                if is_yjl=='是':                    print('********************溢价率自动平仓')                    for stock in hold_stock_list:                        try:                            yjl=yjl_dict.get(stock,0)                            if yjl>=max_yjl:                                print('{} 溢价率{} 符合最大溢价率{} 自动平仓'.format(stock,yjl,max_yjl))                                sell_list.append(stock)                            else:                                print('{} 溢价率{} 不符合最大溢价率{} 不自动平仓'.format(stock,yjl,max_yjl))                        except:                            print('{} 溢价率平仓有问题'.format(stock))                #是否开启大涨卖出                is_max_up=text['是否开启大涨卖出']                max_up=text['大涨']                if is_max_up=='是':                    print('开启大涨卖出')                    for stock in hold_stock_list:                        try:                            hist=self.data.get_hist_data_em(stock=stock)                            zdf=hist['涨跌幅'].tolist()[-1]                            if zdf>=max_up:                                print('{} 今日涨跌幅{} 大于最大涨跌幅{} 卖出'.format(stock,zdf,max_up))                                sell_list.append(stock)                            else:                                print('{} 今日涨跌幅{} 小于最大涨跌幅{} 不操作'.format(stock,zdf,max_up))                        except:                            print('{} 开启大涨卖出有问题'.format(stock))                else:                    print('不开启大涨卖出')                sell_df=pd.DataFrame()                sell_list=list(set(sell_list))                print('************************')                print(sell_list)                is_sell=text['是否开启大跌不卖']                sell_spot=text['大跌']                if is_sell=='是':                    print("开启大跌不卖****************")                    for stock in sell_list:                        try:                            hist=self.data.get_hist_data_em(stock=stock)                            zdf=hist['涨跌幅'].tolist()[-1]                            if zdf>=sell_spot:                                print('大跌不卖{} 今日涨跌幅{} 大于大跌涨跌幅{} 符合模型'.format(stock,zdf,sell_spot))                            else:                                print('大跌不卖{} 今日涨跌幅{} 小于大跌涨跌幅{} 不卖出'.format(stock,zdf,sell_spot))                                sell_list.remove(stock)                        except:                            print('大跌不卖{} 开启大写不卖出有问题'.format(stock))                else:                    print('不开启大跌不卖00000000000000000000000000000000000000000')                sell_df['证券代码']=sell_list                sell_df['交易状态']='未卖'                if sell_df.shape[0]>0:                    print('卖出*****************')                    print(sell_df)                    sell_df=sell_df[['证券代码','交易状态']]                    sell_df.to_excel(r'卖出股票\卖出股票.xlsx')                else:                    print('没有卖出的可转债')                    sell_df['证券代码']=[None]                    sell_df['交易状态']=[None]                    sell_df['策略名称']=self.name                    sell_df=sell_df[['证券代码','交易状态']]                    sell_df.to_excel(r'卖出股票\卖出股票.xlsx')                hold_num=df1.shape[0]                if hold_num>0:                    av_buy_num=hold_limit-hold_num                    av_buy_num=av_buy_num+sell_df.shape[0]                    if av_buy_num>=hold_limit:                        av_buy_num=hold_limit                    else:                        av_buy_num=av_buy_num                    buy_df=trader_df[:av_buy_num]                    if buy_df.shape[0]>0:                        pass                    else:                        buy_df=pd.DataFrame()                        buy_df['证券代码']=[None]                        buy_df['交易状态']=[None]                else:                    buy_df=trader_df[:buy_num]                    if buy_df.shape[0]>0:                        pass                    else:                        buy_df=pd.DataFrame()                        buy_df['证券代码']=[None]                        buy_df['交易状态']=[None]                buy_df['交易状态']='未买'                print('买入*****************')                print(buy_df)                buy_df=buy_df[['证券代码','交易状态']]                buy_df.to_excel(r'买入股票\买入股票.xlsx')                return buy_df            else:                buy_df=trader_df[:hold_limit]                buy_df['交易状态']='未买'                print('买入*****************')                print(buy_df)                buy_df=buy_df[['证券代码','交易状态']]                buy_df.to_excel(r'买入股票\买入股票.xlsx')                return buy_df        else:            print('买入股票文件没有数据')    def get_del_not_trader_stock(self):        '''        剔除黑名单        '''        print('剔除黑名单______________*************************_______________________')        with open(r'分析配置.json',encoding='utf-8') as f:            com=f.read()        text=json.loads(com)        del_df=pd.read_excel(r'{}\黑名单\黑名单.xlsx'.format(self.path),dtype='object')        del_trader_stock=text['黑名单']        if del_df.shape[0]>0:            del_df['证券代码']=del_df['证券代码'].apply(lambda x : str(x).split('.')[0])            del_df['证券代码']=del_df['证券代码'].apply(lambda x: '0'*(6-len(str(x)))+str(x))            del_stock_list=del_df['证券代码'].tolist()        else:            del_stock_list=[]        for del_stock in del_trader_stock:            del_stock_list.append(del_stock)        def select_del_stock_list(x):            if str(x)[:6] in del_stock_list:                return '是'            else:                return '否'        buy_df=pd.read_excel(r'买入股票\买入股票.xlsx',dtype='object')        if buy_df.shape[0]>0:            buy_df['证券代码']=buy_df['证券代码'].apply(lambda x: '0'*(6-len(str(x)))+str(x))            try:                del buy_df['Unnamed: 0']            except:                pass            buy_df['黑名单']=buy_df['证券代码'].apply(select_del_stock_list)            buy_df=buy_df[buy_df['黑名单']=='否']            #隔离策略            buy_df['证券代码']=buy_df['证券代码'].apply(lambda x: '0'*(6-len(str(x)))+str(x))            buy_df['品种']=buy_df['证券代码'].apply(lambda x: self.trader.select_data_type(x))            buy_df.to_excel(r'买入股票\买入股票.xlsx')            print(buy_df)        else:            buy_df=pd.DataFrame()            buy_df.to_excel(r'买入股票\买入股票.xlsx')        #卖出        sell_df=pd.read_excel(r'卖出股票\卖出股票.xlsx',dtype='object')        if sell_df.shape[0]>0:            sell_df['证券代码']=sell_df['证券代码'].apply(lambda x: '0'*(6-len(str(x)))+str(x))            try:                del sell_df['Unnamed: 0']            except:                pass            sell_df['黑名单']=sell_df['证券代码'].apply(select_del_stock_list)            sell_df=sell_df[sell_df['黑名单']=='否']            #隔离策略            sell_df['证券代码']=sell_df['证券代码'].apply(lambda x: '0'*(6-len(str(x)))+str(x))            sell_df['品种']=sell_df['证券代码'].apply(lambda x: self.trader.select_data_type(x))            sell_df.to_excel(r'卖出股票\卖出股票.xlsx')            print(sell_df)        else:            sell_df=pd.DataFrame()            sell_df.to_excel(r'卖出股票\卖出股票.xlsx')        return buy_df,sell_df    def update_all_data(self):        '''        更新策略数据        '''        with open(r'{}\自定义股票池策略.json'.format(self.path),encoding='utf-8') as f:            com=f.read()        user_def_text=json.loads(com)        is_bond_models=user_def_text['是否开启债券模型']        account_av_buy_amount=user_def_text['账户大概可以买入的股票数量']        with open(r'分析配置.json',encoding='utf-8') as f:            com=f.read()        main_text=json.loads(com)        special_stock_list=main_text['特殊标的']        special_cash=main_text['特殊固定交易资金']        fix_cash=main_text['固定交易资金']        trader_ratio=int(special_cash/fix_cash)        print('债券模型交易资金比例{}'.format(trader_ratio))        if is_bond_models=='是':            print('开启债券模型************************')            print(self.save_position())            print(self.save_balance())            self.get_del_buy_sell_data()            self.get_buy_sell_stock()            buy_df,sell_df=self.get_del_not_trader_stock()            hold_stock=pd.read_excel(r'持股数据\持股数据.xlsx',dtype='object')            if hold_stock.shape[0]>0:                hold_stock['证券代码']=hold_stock['证券代码'].apply(lambda x: '0'*(6-len(str(x)))+str(x))                hold_amount=hold_stock.shape[0]                hold_stock['国债']=hold_stock['证券代码'].apply(lambda x: '是' if (x) in special_stock_list else '不是')                bond_hold_stock=hold_stock[hold_stock['国债']=='是']            else:                hold_amount=0                bond_hold_stock=pd.DataFrame()            #债券模型            buy_stock_list=[]            sell_stock_list=[]            bond_models=custom_bond_trend_rotation_strategy(trader_tool=self.trader_tool,exe=self.exe,tesseract_cmd=self.tesseract_cmd,                                open_set=self.open_set,qmt_path=self.qmt_path,qmt_account=self.qmt_account,                                qmt_account_type=self.qmt_account_type)            bond_buy_df,bond_sell_df=bond_models.update_all_data()            if buy_df.shape[0]>0:                stock_list=buy_df['证券代码'].tolist()                for stock in stock_list:                    buy_stock_list.append(stock)            if bond_buy_df.shape[0]>0:                stock_list=bond_buy_df['证券代码'].tolist()                for stock in stock_list:                    buy_stock_list.append(stock)            if sell_df.shape[0]>0:                stock_list=sell_df['证券代码'].tolist()                for stock in stock_list:                    sell_stock_list.append(stock)            if bond_sell_df.shape[0]>0:                stock_list=bond_sell_df['证券代码'].tolist()                for stock in stock_list:                    sell_stock_list.append(stock)            buy_stock_list=list(set(buy_stock_list))            sell_stock_list=list(set(sell_stock_list))            buy_amount=len(buy_stock_list)            sell_amount=len(sell_stock_list)            #账户数量            account_amount=hold_amount+buy_amount-sell_amount            if account_amount<account_av_buy_amount:                print('账户资金充足不用释放资金*************')                buy_df=pd.DataFrame()                buy_df['证券代码']=buy_stock_list                buy_df['交易状态']='未买'                buy_df.to_excel(r'买入股票\买入股票.xlsx')                print('买入股票***************')                print(buy_df)                sell_df=pd.DataFrame()                sell_df['证券代码']=sell_stock_list                sell_df['交易状态']="未卖"                sell_df.to_excel(r'卖出股票\卖出股票.xlsx')                print('卖出股票***************')                print(sell_df)                self.get_del_not_trader_stock()            else:                print('账户资金不充足释放资金*************')                #释放数量                release_amount=account_av_buy_amount-account_amount                release_amount=abs(release_amount)                print('释放数量{}********************'.format(release_amount))                if bond_hold_stock.shape[0]>0:                    bond_hold_stock['卖出']=bond_hold_stock['证券代码'].apply(lambda x: '是' if str(x) in sell_stock_list else '不是')                    bond_hold_stock=bond_hold_stock[bond_hold_stock['卖出']=='不是']                    bond_hold_stock=bond_hold_stock[:int(release_amount/trader_ratio)]                    bond_stock_list=bond_hold_stock['证券代码'].tolist()                    print('释放的股票池***************')                    print(bond_hold_stock)                    for stock in bond_stock_list:                        sell_stock_list.append(stock)                    sell_stock_list=list(set(sell_stock_list))                    buy_df=pd.DataFrame()                    buy_df['证券代码']=buy_stock_list                    buy_df['交易状态']='未买'                    buy_df.to_excel(r'买入股票\买入股票.xlsx')                    print('买入股票***************')                    print(buy_df)                    sell_df=pd.DataFrame()                    sell_df['证券代码']=sell_stock_list                    sell_df['交易状态']="未卖"                    sell_df.to_excel(r'卖出股票\卖出股票.xlsx')                    print('卖出股票***************')                    print(sell_df)                    self.get_del_not_trader_stock()                else:                    print('债券没有持股释放不了资金')                    buy_df=pd.DataFrame()                    buy_df['证券代码']=buy_stock_list                    buy_df['交易状态']='未买'                    buy_df.to_excel(r'买入股票\买入股票.xlsx')                    print('买入股票***************')                    print(buy_df)                    sell_df=pd.DataFrame()                    sell_df['证券代码']=sell_stock_list                    sell_df['交易状态']="未卖"                    sell_df.to_excel(r'卖出股票\卖出股票.xlsx')                    print('卖出股票***************')                    print(sell_df)                    self.get_del_not_trader_stock()        else:            print('不开启债券模型************************')            print(self.save_position())            print(self.save_balance())            self.get_del_buy_sell_data()            self.get_buy_sell_stock()            buy_df,sell_df=self.get_del_not_trader_stock()