quartz学习笔记-core

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#核心代码
import pandas as pdimport dataApi as DAimport cPickle as pickleimport threadingimport globimport osimport timeimport lockfrom pylab import *from multiprocessing import Processclass account(object):        def __init__(self):        self.universe=[]        self.current_date=''        self.cash=0        self.secpos={}        self.valid_secpos={}        self.referencePrice={}        self.referencePortfolioValue=0        self.blotter=[]        self.days_counter=0             class StrategyBase(object):    '''    @var start:回测开始时间    @var end:回测结束时间    @int capital_base:起始资金    @var commission:手续费标准    @var slippage:滑点标准    '''    def __init__(self,start,end,hist,banchmark,universe,capital_base,commission,slippage):        self.start = start #开始时间        self.end = end #结束时间        self.hist=hist #历史数据长度        self.banchmark =banchmark #业绩基准        self.universe =universe #股票池        self.capital_base = capital_base #起始资金        self.commission = commission        self.slippage = slippage        self.account = account()        self.today_data= pd.DataFrame()        self.date_range = pd.DataFrame()        self.hist_range = pd.DataFrame()        self.last_hist =[]        self.stop_change_stock={}        self.day_hist=[] #日期记录        self.value_hist =[] #资产记录        self.return_hist =[] #回报记录        self.return_view =pd.DataFrame()        self.botter_list= [] #交易记录        self.__init__ =self.init()                    def get_cal_date(self):#获取日历        try:            res=DA.Api()            date_range=res.getTradeCal('XSHG','','','calendarDate,isOpen,prevTradeDate')            hist_range=date_range[date_range['calendarDate']<self.start]            hist_range=hist_range[hist_range['isOpen']=='1']#isOpen为字符串            hist_range=hist_range.iloc[hist_range.shape[0]-self.hist:hist_range.shape[0]]             date_range=date_range[date_range['calendarDate']>=self.start]            date_range=date_range[date_range['calendarDate']<=self.end]            self.date_range=date_range            self.hist_range=hist_range        except Exception as e:            raise e              def init(self):                self.get_cal_date()#获取日历        p1 = Process(target=chack_cache,args=(self.date_range,))        #print "start download data!"        p2 = Process(target=chack_cache,args=(self.hist_range,))        p1.start()        p2.start()        self.get_hist_day()             def get_hist_day(self):        hist_data_list=[]        for i in range(self.hist_range.shape[0]):            temp=self.read_cache(self.hist_range.iloc[i]['calendarDate'].replace('-',''))            hist_data_list.append(temp)        self.last_hist=hist_data_list               def save_hist(self):        self.last_hist.append(self.today_data)        while len(self.last_hist)>self.hist:            self.last_hist.pop(0)                def get_last_data(self):        last_data=pd.concat(self.last_hist)        return last_data            def read_cache(self,name):#读缓存函数        abs_path=os.path.abspath('..')        while glob.glob("%s\data\%s.pkl"%(abs_path,name)) == []:            time.sleep(6)        t1=time.time()        while True:            try:                f1=file('../data/%s.pkl'%name,'rb')                p1=pickle.load(f1)                f1.close()                return p1                break            except:                time.sleep(6)               def get_singal_price(self,aymbol):        rows=self.today_data[self.today_data.secID==aymbol]        self.tempdata=rows        return float(rows.iloc[0]['openPrice'])            def run(self):        #self.my_thread(self.chack_cache(self.date_range))        #self.my_thread(self.orap())        print "start strategy..."        len=self.date_range.shape[0]        self.account.cash=self.capital_base        self.initialize()        for i in range(len):            if self.date_range.iloc[i]['isOpen']=='1':                self.account.days_counter=i+1                self.account.current_date=self.date_range.iloc[i]['calendarDate'].replace('-','')                self.today_data=self.read_cache(self.account.current_date)                self.handle_data()                self.save_hist()#更新30天数据池                self.day_record()        data={'time': self.day_hist,              'return_back':self.return_hist,              'value':self.value_hist                           }        self.return_view=pd.DataFrame(data,index=data['time'])        self.return_view['return_back'].plot()        show()                    def day_record(self):        self.account.cash        value=0        for stock in self.account.secpos:            stock_data=self.today_data[self.today_data['secID']==stock]            price=float(stock_data.iloc[0]['closePrice'])            if price == 0 :                if stock in self.stop_change_stock:                    price=float(self.stop_change_stock[stock])#查询是否属于停牌股票，获得停牌前价格                else:                    price=float(stock_data.iloc[0]['preclosePrice']) #首次停牌股票，获得停牌前价格                    self.stop_change_stock[stock]=price            else:                if stock in self.stop_change_stock:                    self.stop_change_stock.pop(stock)                else:                    pass            value+=(int(self.account.secpos[stock])*price)                        self.account.referencePortfolioValue=value+self.account.cash        value_return=float(self.account.referencePortfolioValue-self.capital_base)/self.capital_base        self.return_hist.append(value_return)        self.value_hist.append(self.account.referencePortfolioValue)        self.day_hist.append(self.account.current_date)                        def initialize(self):        pass        def handle_data(self):        pass            def order(self,aymbol,amount):                price=self.get_singal_price(aymbol)        if amount>0 and price>0:            #买入            volum=int(amount/100)*100            order_money=(price*volum)*(1+float(self.commission[0]))            if order_money<=self.account.cash:                self.account.cash-=order_money                if aymbol in  self.account.secpos:                    self.account.secpos[aymbol]+=volum                else:                    self.account.secpos[aymbol]=volum                self.botter=[aymbol,self.tempdata.iloc[0]['secShortName'],'buy',self.account.current_date,price,volum,order_money]                self.botter_list.append(self.botter)                return self.botter            else :                print "botter_error:no enough cash!"                return 0        elif amount<0 and price>0:            #卖出            volum=int(abs(amount)/100)*100            order_money=(price*volum)*(1-float(self.commission[1]))            if aymbol in  self.account.secpos and self.account.secpos[aymbol]>=volum :                self.account.cash+=order_money                self.account.secpos[aymbol]-=volum                self.botter=[aymbol,self.tempdata.iloc[0]['secShortName'],'sell',self.account.current_date,price,volum,order_money]                self.botter_list.append(self.botter)                return self.botter            else:                print "botter_error:no enough stock!"                return 0        else:            pass                 def get_botter_list(self):        botter_list=pd.DataFrame(self.botter_list,columns=[u'证券代码',u'证券名称',u'买/卖',u'时间',u'成交价格',u'交易数量',u'交易金额'])        return botter_list        def order_to(self,symbol,amount):        pass        def max_buy(self,aymbol,cash):        pass  def chack_cache(date_range):#检查数据缓存    try:        date_range=date_range[date_range['isOpen']=='1']        abs_path=os.path.abspath('..')        for i in range(date_range.shape[0]):            day=date_range.iloc[i]['calendarDate'].replace('-','')            have_file=glob.glob("%s\data\%s.pkl"%(abs_path,day))            if have_file == []:                write_cache(day)                print "download data: %s done!"%day            else:                size=os.path.getsize("%s\data\%s.pkl"%(abs_path,day))                if size < 10:                    write_cache(day)                    except Exception as e:        print edef write_cache(name):#写入数据缓存        f1=file('../data/%s.pkl'%name,'wb')    p1=get_all_market_data(name)    if p1 is not None:        pickle.dump(p1,f1,True)    f1.close()        def get_all_market_data(current_data):        res=DA.Api()        data=res.getMktEqud('','',current_data,'','')                #print data        return dataif __name__ == '__main__':    pass    #data=pd.read_csv('../data/600006.csv')    #new_obj=take_back('2006-01-09','2007-01-09',data,cash=100000)    #new_obj.handle()        #res=DA.Api()    #print res.getTradeCal('XSHG','','','calendarDate,isOpen,prevTradeDate')    #mystrategy=StrategyBase(start='2012-01-01',end='2014-01-01',banchmark='HS300',universe='A',capital_base=10000000,commission=0.01,slippage=0)    #date_range=mystrategy.get_cal_date()    #date_range=date_range[date_range['isOpen']=='1']    #for i in range(date_range.shape[0]):        #name=date_range.iloc[i]['calendarDate'].replace('-','')        #print name        #mystrategy.write_cache(name)                      #print mystrategy.get_all_market_data('20150902')
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