from concurrent.futures import ThreadPoolExecutor from multiprocessing import Process, Queue import queue import threading from AlgoPlus.CTP.MdApi import run_tick_engine from AlgoPlus.CTP.FutureAccount import get_simulate_account from AlgoPlus.CTP.FutureAccount import FutureAccount from AlgoPlus.CTP.TraderApiBase import TraderApiBase from AlgoPlus.ta.time_bar import tick_to_bar import pandas as pd from datetime import datetime, timedelta from datetime import time as s_time import operator import time import numpy as np import os import re tickdatadict = {} quotedict = {} ofdatadict = {} trade_dfs = {} previous_volume = {} tsymbollist={} clearing_time_dict = {'sc': s_time(2,30), 'bc': s_time(1,0)} class ParamObj: symbol = None Lots = None py = None trailing_stop_percent = None fixed_stop_loss_percent = None dj_X = None delta = None sum_delta = None 失衡=None 堆积=None 周期=None cont_df = 0 pos = 0 short_trailing_stop_price = 0 long_trailing_stop_price = 0 sl_long_price = 0 sl_shor_price = 0 out_long = 0 out_short = 0 clearing_executed = False kgdata = True def __init__(self, symbol, Lots, py, trailing_stop_percent, fixed_stop_loss_percent, dj_X, delta, sum_delta,失衡,堆积,周期): self.symbol = symbol self.Lots = Lots self.py = py self.trailing_stop_percent = trailing_stop_percent self.fixed_stop_loss_percent = fixed_stop_loss_percent self.dj_X = dj_X self.delta = delta self.sum_delta = sum_delta self.失衡=失衡 self.堆积=堆积 self.周期=周期 class MyTrader(TraderApiBase): def __init__(self, broker_id, td_server, investor_id, password, app_id, auth_code, md_queue=None, page_dir='', private_resume_type=2, public_resume_type=2): self.param_dict = {} self.queue_dict = {} self.品种=' ' def tickcome(self,md_queue): global previous_volume data=md_queue instrument_id = data['InstrumentID'].decode() ActionDay = data['ActionDay'].decode() update_time = data['UpdateTime'].decode() update_millisec = str(data['UpdateMillisec']) created_at = ActionDay[:4] + '-' + ActionDay[4:6] + '-' + ActionDay[6:] + ' ' + update_time + '.' + update_millisec tick = { 'symbol': instrument_id, 'created_at':datetime.strptime(created_at, "%Y-%m-%d %H:%M:%S.%f"), 'price': float(data['LastPrice']), 'last_volume': int(data['Volume']) - previous_volume.get(instrument_id, 0) if previous_volume.get(instrument_id, 0) != 0 else 0, 'bid_p': float(data['BidPrice1']), 'bid_v': int(data['BidVolume1']), 'ask_p': float(data['AskPrice1']), 'ask_v': int(data['AskVolume1']), 'UpperLimitPrice': float(data['UpperLimitPrice']), 'LowerLimitPrice': float(data['LowerLimitPrice']), 'TradingDay': data['TradingDay'].decode(), 'cum_volume': int(data['Volume']), 'cum_amount': float(data['Turnover']), 'cum_position': int(data['OpenInterest']), } previous_volume[instrument_id] = int(data['Volume']) if tick['last_volume']>0: self.on_tick(tick) def can_time(self,hour, minute): hour = str(hour) minute = str(minute) if len(minute) == 1: minute = "0" + minute return int(hour + minute) def on_tick(self,tick): tm=self.can_time(tick['created_at'].hour,tick['created_at'].minute) if tick['last_volume']==0: return quotes = tick timetick=str(tick['created_at']).replace('+08:00', '') tsymbol=tick['symbol'] if tsymbol not in tsymbollist.keys(): tsymbollist[tsymbol]=tick bid_p=quotes['bid_p'] ask_p=quotes['ask_p'] bid_v=quotes['bid_v'] ask_v=quotes['ask_v'] else: rquotes =tsymbollist[tsymbol] bid_p=rquotes['bid_p'] ask_p=rquotes['ask_p'] bid_v=rquotes['bid_v'] ask_v=rquotes['ask_v'] tsymbollist[tsymbol]=tick tick_dt=pd.DataFrame({'datetime':timetick,'symbol':tick['symbol'],'mainsym':tick['symbol'].rstrip('0123456789').upper(),'lastprice':tick['price'], 'vol':tick['last_volume'], 'bid_p':bid_p,'ask_p':ask_p,'bid_v':bid_v,'ask_v':ask_v},index=[0]) sym = tick_dt['symbol'][0] self.tickdata(tick_dt,sym) def data_of(self,symbol, df): global trade_dfs trade_dfs[symbol] = pd.concat([trade_dfs[symbol], df], ignore_index=True) def process(self,bidDict, askDict, symbol): try: dic = quotedict[symbol] bidDictResult = dic['bidDictResult'] askDictResult = dic['askDictResult'] except: bidDictResult, askDictResult = {}, {} sList = sorted(set(list(bidDict.keys()) + list(askDict.keys()))) for s in sList: if s in bidDict: if s in bidDictResult: bidDictResult[s] = int(bidDict[s]) + bidDictResult[s] else: bidDictResult[s] = int(bidDict[s]) if s not in askDictResult: askDictResult[s] = 0 else: if s in askDictResult: askDictResult[s] = int(askDict[s]) + askDictResult[s] else: askDictResult[s] = int(askDict[s]) if s not in bidDictResult: bidDictResult[s] = 0 df = {'bidDictResult': bidDictResult, 'askDictResult': askDictResult} quotedict[symbol] = df return bidDictResult, askDictResult def tickdata(self,df,symbol): tickdata =pd.DataFrame({'datetime':df['datetime'],'symbol':df['symbol'],'lastprice':df['lastprice'], 'volume':df['vol'],'bid_p':df['bid_p'],'bid_v':df['bid_v'],'ask_p':df['ask_p'],'ask_v':df['ask_v']}) try: if symbol in tickdatadict.keys(): rdf=tickdatadict[symbol] rdftm=pd.to_datetime(rdf['bartime'][0]).strftime('%Y-%m-%d %H:%M:%S') now=str(tickdata['datetime'][0]) if now>rdftm: try: oo=ofdatadict[symbol] self.data_of(symbol, oo) if symbol in quotedict.keys(): quotedict.pop(symbol) if symbol in tickdatadict.keys(): tickdatadict.pop(symbol) if symbol in ofdatadict.keys(): ofdatadict.pop(symbol) except IOError as e: print('rdftm捕获到异常',e) tickdata['bartime'] = pd.to_datetime(tickdata['datetime']) tickdata['open'] = tickdata['lastprice'] tickdata['high'] = tickdata['lastprice'] tickdata['low'] = tickdata['lastprice'] tickdata['close'] = tickdata['lastprice'] tickdata['starttime'] = tickdata['datetime'] else: tickdata['bartime'] = rdf['bartime'] tickdata['open'] = rdf['open'] tickdata['high'] = max(tickdata['lastprice'].values,rdf['high'].values) tickdata['low'] = min(tickdata['lastprice'].values,rdf['low'].values) tickdata['close'] = tickdata['lastprice'] tickdata['volume']=df['vol']+rdf['volume'].values tickdata['starttime'] = rdf['starttime'] else : print('新bar的第一个tick进入') tickdata['bartime'] = pd.to_datetime(tickdata['datetime']) tickdata['open'] = tickdata['lastprice'] tickdata['high'] = tickdata['lastprice'] tickdata['low'] = tickdata['lastprice'] tickdata['close'] = tickdata['lastprice'] tickdata['starttime'] = tickdata['datetime'] except IOError as e: print('捕获到异常',e) tickdata['bartime'] = pd.to_datetime(tickdata['bartime']) param = self.param_dict[self.品种] bardata = tickdata.resample(on = 'bartime',rule = param.周期,label = 'right',closed = 'right').agg({'starttime':'first','symbol':'last','open':'first','high':'max','low':'min','close':'last','volume':'sum'}).reset_index(drop = False) bardata =bardata.dropna().reset_index(drop = True) bardata['bartime'] = pd.to_datetime(bardata['bartime'][0]).strftime('%Y-%m-%d %H:%M:%S') tickdatadict[symbol]=bardata tickdata['volume']=df['vol'].values self.orderflow_df_new(tickdata,bardata,symbol) def orderflow_df_new(self,df_tick,df_min,symbol): startArray = pd.to_datetime(df_min['starttime']).values voluememin= df_min['volume'].values highs=df_min['high'].values lows=df_min['low'].values opens=df_min['open'].values closes=df_min['close'].values endArray = df_min['bartime'].values deltaArray = np.zeros((len(endArray),)) tTickArray = pd.to_datetime(df_tick['datetime']).values bp1TickArray = df_tick['bid_p'].values ap1TickArray = df_tick['ask_p'].values lastTickArray = df_tick['lastprice'].values volumeTickArray = df_tick['volume'].values symbolarray = df_tick['symbol'].values indexFinal = 0 for index,tEnd in enumerate(endArray): dt=endArray[index] start = startArray[index] bidDict = {} askDict = {} bar_vol=voluememin[index] bar_close=closes[index] bar_open=opens[index] bar_low=lows[index] bar_high=highs[index] bar_symbol=symbolarray[index] Bp = round(bp1TickArray[0],4) Ap = round(ap1TickArray[0],4) LastPrice = round(lastTickArray[0],4) Volume = volumeTickArray[0] if LastPrice >= Ap: if str(LastPrice) in askDict.keys(): askDict[str(LastPrice)] += Volume else: askDict[str(LastPrice)] = Volume if LastPrice <= Bp: if str(LastPrice) in bidDict.keys(): bidDict[str(LastPrice)] += Volume else: bidDict[str(LastPrice)] = Volume bidDictResult,askDictResult = self.process(bidDict,askDict,symbol) bidDictResult=dict(sorted(bidDictResult.items(),key=operator.itemgetter(0))) askDictResult=dict(sorted(askDictResult.items(),key=operator.itemgetter(0))) prinslist=list(bidDictResult.keys()) asklist=list(askDictResult.values()) bidlist=list(bidDictResult.values()) delta=(sum(askDictResult.values()) - sum(bidDictResult.values())) df=pd.DataFrame({'price':pd.Series([prinslist]),'Ask':pd.Series([asklist]),'Bid':pd.Series([bidlist])}) df['symbol']=bar_symbol df['datetime']=dt df['delta']=str(delta) df['close']=bar_close df['open']=bar_open df['high']=bar_high df['low']=bar_low df['volume']=bar_vol df['dj'] = self.GetOrderFlow_dj(df) ofdatadict[symbol]=df def GetOrderFlow_dj(self,kData): param = self.param_dict[self.品种] Config = { 'Value1': param.失衡, 'Value2': param.堆积, 'Value4': True, } aryData = kData djcout = 0 for index, row in aryData.iterrows(): kItem = aryData.iloc[index] high = kItem['high'] low = kItem['low'] close = kItem['close'] open = kItem['open'] dtime = kItem['datetime'] price_s = kItem['price'] Ask_s = kItem['Ask'] Bid_s = kItem['Bid'] delta = kItem['delta'] price_s = price_s Ask_s = Ask_s Bid_s = Bid_s gj = 0 xq = 0 gxx = 0 xxx = 0 for i in np.arange(0, len(price_s), 1): duiji = { 'price': 0, 'time': 0, 'longshort': 0, } if i == 0: delta = delta order= { "Price":price_s[i], "Bid":{ "Value":Bid_s[i]}, "Ask":{ "Value":Ask_s[i]} } if i >= 0 and i < len(price_s) - 1: if (order["Bid"]["Value"] > Ask_s[i + 1] * int(Config['Value1'])): gxx += 1 gj += 1 if gj >= int(Config['Value2']) and Config['Value4'] == True: duiji['price'] = price_s[i] duiji['time'] = dtime duiji['longshort'] = -1 if float(duiji['price']) > 0: djcout += -1 else: gj = 0 if i >= 1 and i < len(price_s) - 1: if (order["Ask"]["Value"] > Bid_s[i - 1] * int(Config['Value1'])): xq += 1 xxx += 1 if xq >= int(Config['Value2']) and Config['Value4'] == True: duiji['price'] = price_s[i] duiji['time'] = dtime duiji['longshort'] = 1 if float(duiji['price']) > 0: djcout += 1 else: xq = 0 return djcout def read_to_csv(self,symbol): param = self.param_dict[symbol] folder_path = "traderdata" file_path = os.path.join(folder_path, f"{str(symbol)}_traderdata.csv") if not os.path.exists(folder_path): os.makedirs(folder_path) if os.path.exists(file_path): df = pd.read_csv(file_path) if not df.empty and param.kgdata==True: row = df.iloc[-1] param.pos = int(row['pos']) param.short_trailing_stop_price = float(row['short_trailing_stop_price']) param.long_trailing_stop_price = float(row['long_trailing_stop_price']) param.sl_long_price = float(row['sl_long_price']) param.sl_shor_price = float(row['sl_shor_price']) print("找到历史交易数据文件,已经更新持仓，止损止盈数据", df.iloc[-1]) param.kgdata=False else: pass pass def save_to_csv(self,symbol): param = self.param_dict[symbol] data = { 'datetime': [trade_dfs[symbol]['datetime'].iloc[-1]], 'pos': [param.pos], 'short_trailing_stop_price': [param.short_trailing_stop_price], 'long_trailing_stop_price': [param.long_trailing_stop_price], 'sl_long_price': [param.sl_long_price], 'sl_shor_price': [param.sl_shor_price], } df = pd.DataFrame(data) df.to_csv(f"traderdata/{str(symbol)}_traderdata.csv", index=False) def day_data_reset(self, symbol): param = self.param_dict[symbol] sec = ''.join(re.findall('[a-zA-Z]', str(symbol))) current_time = datetime.now().time() clearing_time1_start = s_time(15,00) clearing_time1_end = s_time(15,15) param.clearing_executed = False if clearing_time1_start <= current_time <= clearing_time1_end and not param.clearing_executed : param.clearing_executed = True trade_dfs[symbol].drop(trade_dfs[symbol].index,inplace=True) elif sec in clearing_time_dict.keys(): clearing_time2_start = clearing_time_dict[sec] clearing_time2_end = s_time(clearing_time2_start.hour, clearing_time2_start.minute+15) if clearing_time2_start <= current_time <= clearing_time2_end and not param.clearing_executed : param.clearing_executed = True trade_dfs[symbol].drop(trade_dfs[symbol].index,inplace=True) else: param.clearing_executed = False pass return param.clearing_executed def OnRtnTrade(self, pTrade): print("||成交回报||", pTrade) def OnRspOrderInsert(self, pInputOrder, pRspInfo, nRequestID, bIsLast): print("||OnRspOrderInsert||", pInputOrder, pRspInfo, nRequestID, bIsLast) def OnRtnOrder(self, pOrder): print("||订单回报||", pOrder) def cal_sig(self, symbol_queue): while True: try: data = symbol_queue.get(block=True, timeout=5) instrument_id = data['InstrumentID'].decode() size = symbol_queue.qsize() if size > 1: print(f'当前{instrument_id}共享队列长度为{size}, 有点阻塞！！！！！') self.read_to_csv(instrument_id) self.day_data_reset(instrument_id) param = self.param_dict[instrument_id] self.品种=instrument_id self.tickcome(data) trade_df = trade_dfs[instrument_id] self.read_to_csv(instrument_id) if len(trade_df)>param.cont_df: csv_file_path = f"traderdata/{instrument_id}_ofdata.csv" if os.path.exists(csv_file_path): trade_df.tail(1).to_csv(csv_file_path, mode='a', header=False, index=False) else: trade_df.to_csv(csv_file_path, index=False) if param.long_trailing_stop_price >0 and param.pos>0: param.long_trailing_stop_price = trade_df['low'].iloc[-1] if param.long_trailing_stop_price0 and param.pos<0: param.short_trailing_stop_price = trade_df['high'].iloc[-1] if trade_df['high'].iloc[-1] 0: print('datetime+sig: ',trade_df['datetime'].iloc[-1],'预设——多头止盈——','TR',param.out_long,'low', trade_df['low'].iloc[-1]) if trade_df['low'].iloc[-1] < param.out_long and param.pos>0 and param.sl_long_price>0 and trade_df['low'].iloc[-1]>param.sl_long_price: print('datetime+sig: ',trade_df['datetime'].iloc[-1],'多头止盈','TR',param.out_long,'low', trade_df['low'].iloc[-1]) self.insert_order(data['ExchangeID'], data['InstrumentID'], data['BidPrice1']-param.py,param.Lots,b'1',b'1') self.insert_order(data['ExchangeID'], data['InstrumentID'], data['BidPrice1']-param.py,param.Lots,b'1',b'3') param.long_trailing_stop_price = 0 param.out_long=0 param.sl_long_price=0 param.pos = 0 self.save_to_csv(instrument_id) if param.out_short>0: print('datetime+sig: ',trade_df['datetime'].iloc[-1],'预设——空头止盈——: ','TR',param.out_short,'high', trade_df['high'].iloc[-1]) if trade_df['high'].iloc[-1] > param.out_short and param.pos<0 and param.sl_shor_price>0 and trade_df['high'].iloc[-1]0: print('datetime+sig: ', trade_df['datetime'].iloc[-1], '预设——多头止损', 'SL', fixed_stop_loss_L, 'close', trade_df['close'].iloc[-1]) if param.sl_long_price>0 and fixed_stop_loss_L>0 and param.pos > 0 and trade_df['close'].iloc[-1] < fixed_stop_loss_L: print('datetime+sig: ', trade_df['datetime'].iloc[-1], '多头止损', 'SL', fixed_stop_loss_L, 'close', trade_df['close'].iloc[-1]) self.insert_order(data['ExchangeID'], data['InstrumentID'], data['BidPrice1']-param.py,param.Lots,b'1',b'1') self.insert_order(data['ExchangeID'], data['InstrumentID'], data['BidPrice1']-param.py,param.Lots,b'1',b'3') param.long_trailing_stop_price = 0 param.sl_long_price=0 param.out_long = 0 param.pos = 0 self.save_to_csv(instrument_id) fixed_stop_loss_S = param.sl_shor_price * (1 + param.fixed_stop_loss_percent) if param.pos<0: print('datetime+sig: ', trade_df['datetime'].iloc[-1], '预设——空头止损', 'SL', fixed_stop_loss_S, 'close', trade_df['close'].iloc[-1]) if param.sl_shor_price>0 and fixed_stop_loss_S>0 and param.pos < 0 and trade_df['close'].iloc[-1] > fixed_stop_loss_S: print('datetime+sig: ', trade_df['datetime'].iloc[-1], '空头止损', 'SL', fixed_stop_loss_S, 'close', trade_df['close'].iloc[-1]) self.insert_order(data['ExchangeID'], data['InstrumentID'], data['AskPrice1']+param.py,param.Lots,b'0',b'1') self.insert_order(data['ExchangeID'], data['InstrumentID'], data['AskPrice1']+param.py,param.Lots,b'0',b'3') param.short_trailing_stop_price = 0 param.sl_shor_price=0 param.out_short = 0 param.pos = 0 self.save_to_csv(instrument_id) trade_df['dayma']=trade_df['close'].mean() trade_df['delta'] = trade_df['delta'].astype(float) trade_df['delta累计'] = trade_df['delta'].cumsum() 开多1=trade_df['dayma'].iloc[-1] > 0 and trade_df['close'].iloc[-1] > trade_df['dayma'].iloc[-1] 开多4=trade_df['delta累计'].iloc[-1] > param.sum_delta and trade_df['delta'].iloc[-1] > param.delta 开空1=trade_df['dayma'].iloc[-1]>0 and trade_df['close'].iloc[-1] < trade_df['dayma'].iloc[-1] 开空4=trade_df['delta累计'].iloc[-1] < -param.sum_delta and trade_df['delta'].iloc[-1] < -param.delta 开多组合= 开多1 and 开多4 and trade_df['dj'].iloc[-1]>param.dj_X 开空条件= 开空1 and 开空4 and trade_df['dj'].iloc[-1]<-param.dj_X 平多条件=trade_df['dj'].iloc[-1]<-param.dj_X 平空条件=trade_df['dj'].iloc[-1]>param.dj_X if param.pos<0 and 平空条件 : print('平空： ','ExchangeID: ',data['ExchangeID'],'InstrumentID',data['InstrumentID'],'AskPrice1',data['AskPrice1']+param.py) self.insert_order(data['ExchangeID'], data['InstrumentID'], data['AskPrice1']+param.py,param.Lots,b'0',b'1') self.insert_order(data['ExchangeID'], data['InstrumentID'], data['AskPrice1']+param.py,param.Lots,b'0',b'3') param.pos=0 param.sl_shor_price=0 param.short_trailing_stop_price=0 print('datetime+sig: ', trade_df['datetime'].iloc[-1], '反手平空：', '平仓价格：', data['AskPrice1']+param.py,'堆积数：', trade_df['dj'].iloc[-1]) self.save_to_csv(instrument_id) if param.pos==0 and 开多组合: print('开多： ','ExchangeID: ',data['ExchangeID'],'InstrumentID',data['InstrumentID'],'AskPrice1',data['AskPrice1']+param.py) self.insert_order(data['ExchangeID'], data['InstrumentID'], data['AskPrice1']+param.py,param.Lots,b'0',b'0') print('datetime+sig: ', trade_df['datetime'].iloc[-1], '多头开仓', '开仓价格：', data['AskPrice1']+param.py,'堆积数：', trade_df['dj'].iloc[-1]) param.pos=1 param.long_trailing_stop_price=data['AskPrice1'] param.sl_long_price=data['AskPrice1'] self.save_to_csv(instrument_id) if param.pos>0 and 平多条件 : print('平多： ','ExchangeID: ',data['ExchangeID'],'InstrumentID',data['InstrumentID'],'BidPrice1',data['BidPrice1']-param.py) self.insert_order(data['ExchangeID'], data['InstrumentID'], data['BidPrice1']-param.py,param.Lots,b'1',b'1') self.insert_order(data['ExchangeID'], data['InstrumentID'], data['BidPrice1']-param.py,param.Lots,b'1',b'3') param.pos=0 param.long_trailing_stop_price=0 param.sl_long_price=0 print('datetime+sig: ', trade_df['datetime'].iloc[-1], '反手平多', '平仓价格：', data['BidPrice1']-param.py,'堆积数：', trade_df['dj'].iloc[-1]) self.save_to_csv(instrument_id) if param.pos==0 and 开空条件 : print('开空： ','ExchangeID: ',data['ExchangeID'],'InstrumentID',data['InstrumentID'],'BidPrice1',data['BidPrice1']) self.insert_order(data['ExchangeID'], data['InstrumentID'], data['BidPrice1']-param.py,param.Lots,b'1',b'0') print('datetime+sig: ', trade_df['datetime'].iloc[-1], '空头开仓', '开仓价格：', data['BidPrice1']-param.py,'堆积数：', trade_df['dj'].iloc[-1]) param.pos=-1 param.short_trailing_stop_price=data['BidPrice1'] param.sl_shor_price=data['BidPrice1'] self.save_to_csv(instrument_id) print(trade_df) param.cont_df=len(trade_df) except queue.Empty: pass def distribute_tick(self): while True: if self.status == 0: data = None while not self.md_queue.empty(): data = self.md_queue.get(block=False) instrument_id = data['InstrumentID'].decode() try: self.queue_dict[instrument_id].put(data, block=False) except queue.Full: print(f"{instrument_id}合约信号计算阻塞导致对应队列已满，请检查对应代码逻辑后重启。") else: time.sleep(1) def start(self, param_dict): threads = [] self.param_dict = param_dict for symbol in param_dict.keys(): trade_dfs[symbol] = pd.DataFrame({}) self.queue_dict[symbol] = queue.Queue(20) t = threading.Thread(target=self.cal_sig, args=(self.queue_dict[symbol],)) threads.append(t) t.start() self.distribute_tick() for t in threads: t.join() def run_trader(param_dict, broker_id, td_server, investor_id, password, app_id, auth_code, md_queue=None, page_dir='', private_resume_type=2, public_resume_type=2): my_trader = MyTrader(broker_id, td_server, investor_id, password, app_id, auth_code, md_queue, page_dir, private_resume_type, public_resume_type) my_trader.start(param_dict) if __name__ == '__main__': param_dict = {} param_dict['rb2410'] = ParamObj(symbol='rb2410', Lots=1, py=5, trailing_stop_percent=0.02, fixed_stop_loss_percent=0.01,dj_X=1,delta=1500,sum_delta=2000,失衡=3,堆积=3,周期='1T') future_account = get_simulate_account( investor_id='***', password='***', server_name='***', subscribe_list=list(param_dict.keys()) ) print('开始',len(future_account.subscribe_list)) share_queue = Queue(maxsize=200) md_process = Process(target=run_tick_engine, args=(future_account, [share_queue])) trader_process = Process(target=run_trader, args=( param_dict, future_account.broker_id, future_account.server_dict['TDServer'], future_account.investor_id, future_account.password, future_account.app_id, future_account.auth_code, share_queue, future_account.td_flow_path )) md_process.start() trader_process.start() md_process.join() trader_process.join()