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BuySell.py
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# encoding:gbk
import datetime, re, time, os, copy
import numpy as np
import pandas as pd
#######################################################################################################
############################# 自定义参数 ###########################################
#######################################################################################################
# 1. 根据策略文件买入；
# 2. 卖出买入仓位。
# 基本设置
ACCOUNT = '66666666' # 填写您的账号
account_type = 'STOCK'
multiples = 10 # 可转债每手十张
strategy_name = 'strat' # 策略名称
logloc = '' # 您的日志文件位置
logfile = logloc + ACCOUNT + '-' + strategy_name + '.txt'
statfile = '' + ACCOUNT + '/' + strategy_name + '.txt' # 策略状态文件位置
# 策略输入
stratfile_loc = '' # 策略文件存储位置
stratfile_name = strategy_name # 按照 strat_file_loc+日期（20240102)-strat_file_name 格式输入策略文件
buy_num = 0 # 此排名内等权买入（如果是0则按策略文件权重买入）
# 交易设置
strat_cap = 100e4 # 全部篮子标的目标市值
buy_start_time = '093000' # 开始交易时点
buy_dur_time = 300 # 最长交易时间（秒）
sell_start_time = '145000' # 开始交易时点
sell_dur_time = 300 # 最长交易时间（秒）
interval = 30 # 每隔interval秒挂单一次
wait_dur = interval*0.8 # 订单等待wait_dur秒后未成交撤单
tolerance = 0.01 # 买卖挂单超价（%）
delta_min = 3000 # 最小挂单金额
delta_max = 30000 # 最大挂单金额
max_upndown = 0.2 # 涨跌幅限制，转债20%
buy_prepare_time = datetime.datetime.strptime(buy_start_time, "%H%M%S")\
+ datetime.timedelta(seconds=-30) # 交易前30s读取篮子文件
buy_prepare_time = buy_prepare_time.strftime("%H%M%S")
buy_end_time = datetime.datetime.strptime(buy_start_time, "%H%M%S")\
+ datetime.timedelta(seconds=buy_dur_time)
buy_end_time = buy_end_time.strftime("%H%M%S")
buy_summary_time = datetime.datetime.strptime(buy_end_time, "%H%M%S")\
+ datetime.timedelta(seconds=interval) # 交易结束后interval总结交易结果
buy_summary_time = buy_summary_time.strftime("%H%M%S")
sell_prepare_time = datetime.datetime.strptime(sell_start_time, "%H%M%S")\
+ datetime.timedelta(seconds=-30) # 交易前30s读取篮子文件
sell_prepare_time = sell_prepare_time.strftime("%H%M%S")
sell_end_time = datetime.datetime.strptime(sell_start_time, "%H%M%S")\
+ datetime.timedelta(seconds=sell_dur_time)
sell_end_time = sell_end_time.strftime("%H%M%S")
sell_summary_time = datetime.datetime.strptime(sell_end_time, "%H%M%S")\
+ datetime.timedelta(seconds=interval) # 交易结束后interval总结交易结果
sell_summary_time = sell_summary_time.strftime("%H%M%S")
#######################################################################################################
############################# 常用函数模块 ###########################################
#######################################################################################################
########################################### 日常io运行 ###################################################
# log 函数
def log(*txt):
try:
f = open(logfile,'a+', encoding='gbk')
f.write('%s'%datetime.datetime.now()+' '*6) # 时间戳
if type(txt[0])==pd.Series:
f.write('name: %s\n'%txt[0].name)
for i,v in txt[0].items():
f.write(' '*32+str(i)+', '+str(v)+'\n')
elif type(txt[0])==pd.DataFrame:
f.write(' '.join([str(i) for i in txt[0].columns])+'\n')
for i,r in txt[0].iterrows():
f.write(' '*29+str(i)+': ')
f.write(', '.join([str(j) for j in r.values])+'\n')
else:
write_str = ('\n'+' '*32).join([str(i) for i in txt])
f.write('%s\n' %write_str)
f.close()
except PermissionError as e:
print(f"Error: {e}. You don't have permission to access the specified file.")
########################################### 行情数据 ###################################################
# 获取行情快照数据 DataFrame, index:code
SHmul = 10
SZmul = 10
def get_snapshot(C, code_list):
# 获取标的快照数据
df = C.get_full_tick(code_list)
df = pd.DataFrame.from_dict(df, dtype='float').T.reset_index().rename(columns={'index': 'code'})
# 盘口
bidPrice_columns = ['bidp1','bidp2','bidp3','bidp4','bidp5']
askPrice_columns = ['askp1','askp2','askp3','askp4','askp5']
df[bidPrice_columns] = df['bidPrice'].apply(pd.Series, index=bidPrice_columns)
df[askPrice_columns] = df['askPrice'].apply(pd.Series, index=askPrice_columns)
bidVol_columns = ['bidv1','bidv2','bidv3','bidv4','bidv5']
askVol_columns = ['askv1','askv2','askv3','askv4','askv5']
df[bidVol_columns] = df['bidVol'].apply(pd.Series, index=bidVol_columns)
df[askVol_columns] = df['askVol'].apply(pd.Series, index=askVol_columns)
# 中间价
df['mid'] = (df['bidp1'] + df['askp1'])/2
# 涨跌停则bid/askprice为0
df.loc[(df['bidp1'] == 0) | (df['askp1'] == 0),'mid'] = df['bidp1'] + df['askp1'] # 涨跌停修正
## 展示列 最新价，当日成交额、成交量(手）、最高价、最低价、开盘价
# 盘口 askp\askv*/bid* 买卖5档， 昨收
## 中间价 askp\askv*/bid* 买卖5档，需要使用券商行情
display_columns = ['code', 'lastPrice', 'amount', 'volume', 'high', 'low', 'open', 'lastClose',\
'mid', 'askp1', 'askp2', 'askp3', 'askp4', 'askp5', \
'bidp1', 'bidp2', 'bidp3', 'bidp4', 'bidp5', \
'askv1', 'askv2', 'askv3', 'askv4', 'askv5',\
'bidv1', 'bidv2', 'bidv3', 'bidv4', 'bidv5']
df = df[display_columns].rename(columns={'volume':'vol'})
df = df.set_index('code')
# 有时，沪市转债单位是手，沪市需要乘一个沪市转化因子
df['vol'] = df['vol']*df.index.map(lambda x: SHmul if 'SH' in x else SZmul if 'SZ' in x else 1)
return df
########################################### 账户状态 ###################################################
# 获取账户状态 净值，现金
def get_account():
acct_info = get_trade_detail_data(ACCOUNT, account_type, 'account')[0]
return {'net':acct_info.m_dBalance, 'cash':acct_info.m_dAvailable}
# 获取持仓数据 DataFrame index:code, cash 如果没有持仓返回空表（但是有columns）
def get_pos():
position_to_dict = lambda pos: {
'code': pos.m_strInstrumentID + '.' + pos.m_strExchangeID, # 证券代码 000001.SZ
'name': pos.m_strInstrumentName, # 证券名称
'vol': pos.m_nVolume, # 当前拥股，持仓量
'AvailableVol': pos.m_nCanUseVolume, # 可用余额，可用持仓，期货不用这个字段，股票的可用数量
'MarketValue': pos.m_dMarketValue, # 市值，合约价值
'PositionCost': pos.m_dPositionCost, # 持仓成本，
}
position_info = get_trade_detail_data(ACCOUNT, account_type, 'position')
pos = pd.DataFrame(list(map(position_to_dict, position_info)))
if pos.empty:
return pd.DataFrame(columns=['name', 'vol', 'AvailabelVol', 'MarketValue', 'PositionCost'])
pos = pos.set_index('code')
extract_names = ['新标准券', '国标准券']
pos = pos[(pos['vol']!=0)&(~pos['name'].isin(extract_names))].copy() # 已清仓不看，去掉逆回购重复输出
return pos
# 忽略逆回购订单、交割单
status_extract_codes = ['131810.SZ', '131811.SZ', '131800.SZ', '131809.SZ', '131801.SZ',\
'131802.SZ', '131803.SZ', '131805.SZ', '131806.SZ',\
'204001.SH', '204002.SH', '204003.SH', '204004.SH', '204007.SH',\
'204014.SH', '204028.SH', '204091.SH', '204182.SH']
# 获取订单状态 当日没有订单返回空表（但是有columns） 当天订单
def get_order():
order_info = get_trade_detail_data(ACCOUNT, account_type, 'ORDER')
order_to_dict = lambda o:{
'id':o.m_strOrderSysID,
'date': o.m_strInsertDate,
'code': o.m_strInstrumentID+'.'+o.m_strExchangeID,
'sub_time': o.m_strInsertTime, # 例如 str:095620
'trade_type': o.m_nOffsetFlag, # 48 买入/开仓；49 卖出/平仓
'price': o.m_dLimitPrice, # 挂单价
'sub_vol': o.m_nVolumeTotalOriginal,
'dealt_vol': o.m_nVolumeTraded,
'remain_vol': o.m_nVolumeTotal,
# 48 未报， 49 待报， 50 已报， 51 已报待撤，52 部成待撤， 53 部撤(部成撤单），
# 54 已撤， 55 部成， 56 已成， 57 废单(算法单执行完毕之后为废单）， 86 已确认， 255 未知
'status':o.m_nOrderStatus,
'frozen':o.m_dFrozenMargin+o.m_dFrozenCommission, # 冻结金额/保证金+手续费
'remark':o.m_strRemark # 订单备注
}
order = pd.DataFrame(list(map(order_to_dict, order_info)))
if order.empty:
return pd.DataFrame(columns=['id', 'date', 'code', 'sub_time', 'trade_type',\
'price', 'sub_vol', 'dealt_vol', 'remain_vol', 'status', 'frozen', 'remark'])
order = order[(order['date']==datetime.datetime.today().strftime("%Y%m%d"))&\
(~order['code'].isin(status_extract_codes))].copy()
order = order.set_index('id')
return order[['date', 'code', 'sub_time', 'trade_type', 'price',\
'sub_vol', 'dealt_vol', 'remain_vol', 'status', 'frozen', 'remark']]
# 获取成交数据
def get_deal():
deal_info = get_trade_detail_data(ACCOUNT, account_type, 'DEAL')
deal_to_dict = lambda d:{
'order_id':d.m_nRef, # 订单编号
'id':d.m_strOrderSysID, # 合同编号
'code': d.m_strInstrumentID + '.' + d.m_strExchangeID,
'date':d.m_strTradeDate,
'deal_time':d.m_strTradeTime, # 成交时间
# 48 买入/开仓 49卖出/平仓 50 强平 51 平今 52 平昨 53 强减
'trade_type':d.m_nOffsetFlag,
'price':d.m_dPrice,
'vol': d.m_nVolume,
'amount': d.m_dTradeAmount,
'remark': d.m_strRemark
}
deal = pd.DataFrame(list(map(deal_to_dict, deal_info)))
if deal.empty:
return pd.DataFrame(columns=['id', 'order_id', 'code', 'date', 'deal_time',\
'trade_type', 'price', 'vol', 'amount', 'remark'])
deal = deal[(deal['date']==datetime.datetime.today().strftime("%Y%m%d"))&\
(~deal['code'].isin(status_extract_codes))].copy()
return deal[['id', 'order_id', 'code', 'date', 'deal_time',\
'trade_type', 'price', 'vol', 'amount', 'remark']]
########################################### 买卖挂单 ###################################################
# 撤单 超过wait_dur s的订单取消
def cancel_order(C, wait_dur, stratname=None):
order = get_order()
# 全部可撤订单
order = order[order['status'].map(lambda x:(x!=53)&(x!=54)&(x!=56)&(x!=57))].copy()
if order.empty:
return
# 属于该策略
if stratname!=None:
order = order[order['remark']==stratname].copy()
if not order.empty:
# 超过等待时间撤单 insert_time 为1900年
order['sub_time'] = order['sub_time'].map(lambda x: datetime.datetime.strptime(x, "%H%M%S"))
order = order[order['sub_time'].map(lambda x: (datetime.datetime.now()-x).seconds>wait_dur)]
for orderid in order.index:
cancel(orderid, ACCOUNT, account_type, C)
# 撤单 属于策略strat的挂单价超过最新价(1+r)或低于最新价(1-r)的订单取消
def cancel_order_price(C, r, stratname=None):
order = get_order()
# 全部可撤订单
order = order[order['status'].map(lambda x:(x!=53)&(x!=54)&(x!=56)&(x!=57))].copy()
if order.empty:
return
# 属于该策略
if stratname!=None:
order = order[order['remark']==stratname].copy()
if not order.empty:
# 最新价格
codes = list(set(order['code']))
snapshot = get_snapshot(C, codes)
lastPrice = snapshot[['lastPrice', 'lastClose']].apply(lambda x: \
x['lastPrice'] if x['lastPrice']!=0 else x['lastClose'], axis=1)
lastPrice = order['code'].map(lambda x: lastPrice[x])
if not order.empty:
delta = abs((order['price']-lastPrice)/lastPrice)
delta = delta[delta>r]
for orderid in delta.index:
cancel(orderid, ACCOUNT, account_type, C)
#strategy_name = 'craft'
#multiples = 10
#卖出
def sell(C, code, price, vol, strategyName=strategy_name, remark=strategy_name):
vol = int((vol//multiples)*multiples)
if vol==0:
print('too less vol to sub')
return
# 卖出，单标的，账号， 代码，限价单，价格，量，策略名，立即触发下单，备注
if account_type=='STOCK':
passorder(24, 1101, ACCOUNT, code, 11, price, vol, strategyName, 2, remark, C) # 下单
elif account_type=='CREDIT':
passorder(34, 1101, ACCOUNT, code, 11, price, vol, strategyName, 2, remark, C) # 下单
#买入
def buy(C, code, price, vol, strategyName=strategy_name, remark=strategy_name):
vol = int((vol//multiples)*multiples)
if vol==0:
print('too less vol to sub')
return
if account_type=='STOCK':
passorder(23, 1101, ACCOUNT, code, 11, price, vol, strategyName, 2, remark, C) # 下单
elif account_type=='CREDIT':
passorder(33, 1101, ACCOUNT, code, 11, price, vol, strategyName, 2, remark, C) # 下单
########################################### 其他 ###################################################
# 存储全局变量
class a():
pass
#######################################################################################################
############################# 策略主代码 ###########################################
#######################################################################################################
# 初始化准备
def buy_prepare(C):
strat_files = [f for f in os.listdir(stratfile_loc) \
if f.split('.')[-2].split('-')[-1]==stratfile_name]
strat_files = sorted(strat_files)
strat_file = stratfile_loc + strat_files[-1]
df = pd.read_csv(strat_file, encoding='utf-8')
log('读取策略文件', strat_file)
print('读取策略文件', strat_file)
sorted_codes = (df['代码'].astype('str')+'.'+df['市场']).values # 策略标的按打分排序
if buy_num==0:
print(df[['代码', '市场', 'name', 'weight']])
weights = pd.Series(df['weight'].values, index=sorted_codes)
else:
print(df[['代码', '市场', 'name']])
weights = pd.Series(1, index=list(sorted_codes[:buy_num]))
weights = weights/weights.sum()
buy_cap = strat_cap*weights
log('目标买入额')
log(buy_cap)
buy_cap.loc[buy_cap<delta_min] = 0
log('目标买入额小于最小变动阈值:'+','.join(list(buy_cap[buy_cap==0].index)))
buy_cap = buy_cap[buy_cap>0]
snapshot = get_snapshot(C, list(buy_cap.index))
mid_snapshot = snapshot['mid']
trade_vol = buy_cap/mid_snapshot
log('目标交易张数，金额，即时价格')
log(pd.concat([trade_vol, buy_cap, mid_snapshot], axis=1))
# trader运行所需参数
A.trade_vol = trade_vol
A.traded_vol = pd.Series(0, A.trade_vol.index) # 已成交张数
A.remain_times = int(buy_dur_time/interval-1) # 剩余挂单轮数
A.start_time = buy_start_time
A.end_time = buy_end_time
A.dur_time = buy_dur_time
A.interval = interval
A.summary_time = buy_summary_time
# 卖出
def sell_prepare(C):
with open(statfile, 'r') as f:
r = f.readlines()
bought = {i.split(',')[0]:int(i.split(',')[1][:-1]) for i in r}
bought = pd.Series(bought)
log('昨夜买入：')
log(bought)
print('昨夜买入：')
print(bought)
# trader运行所需参数
A.trade_vol = -bought
A.traded_vol = pd.Series(0, bought.index) # 已成交张数
A.remain_times = int(sell_dur_time/interval-1) # 剩余挂单轮数
A.start_time = sell_start_time
A.end_time = sell_end_time
A.dur_time = sell_dur_time
A.interval = interval
A.summary_time = sell_summary_time
# 挂单员
def trader(C):
if A.remain_times==0:
return
log('第%s/%s轮挂单'%(int(A.dur_time/A.interval)-A.remain_times+1, int(A.dur_time/A.interval)))
snapshot = get_snapshot(C, list(A.trade_vol.index))
mid_snapshot = snapshot['mid']
bidPrice_snapshot = snapshot['bidp1']
askPrice_snapshot = snapshot['askp1']
lastClose_snapshot = snapshot['lastClose']
# 该trader已成交数量（备注为strategy_name, sub_time从start_time到end_time）
trader_orders = get_order().reset_index()
trader_orders = trader_orders[(trader_orders['remark']==strategy_name)&\
(trader_orders['sub_time']>A.start_time)&(trader_orders['sub_time']<A.end_time)]
undeal = trader_orders['sub_vol']*trader_orders['sub_time'].map(lambda x: 1 if x>'145700' else 0)*\
trader_orders['code'].map(lambda x: 1 if 'SZ' in x else 0)
trader_orders['dealt_vol'] = trader_orders['dealt_vol']+undeal # SZ 交易所，1457之后未成交全部归为成交
trader_orders['dealt_vol'] = trader_orders['dealt_vol']*trader_orders['trade_type'].map(lambda x: 1 if x==48 else -1)
A.traded_vol = (trader_orders.groupby('code')['dealt_vol'].sum()).reindex(A.traded_vol.index).fillna(0)
log('策略已成交:')
log(A.traded_vol)
# 涨停不卖出、不排板
limitup_codes = askPrice_snapshot[askPrice_snapshot.isna()|(askPrice_snapshot==0)]
limitdown_codes = bidPrice_snapshot[bidPrice_snapshot.isna()|(bidPrice_snapshot==0)]
should_trade_vol = (A.trade_vol - A.traded_vol).sort_values() # 先卖再买
for code, delta_vol in should_trade_vol.items():
log('处理 %s %s'%(code, delta_vol))
if code in limitup_codes.index:
print('涨停不卖出，不排版')
log('涨停不卖出，不排板')
continue
mean_vol = abs(delta_vol)/A.remain_times # 平均每次需要交易张数绝对值
price = mid_snapshot.loc[code]
if (abs(delta_vol*price)<delta_min)&(delta_vol>0):
log('买入与目标市值差距小于挂单金额，不交易')
continue
else:
if mean_vol*price<delta_min:
log('单笔成交金额小于最小值，已按最小值和需要成交张数低者挂单。')
vol = min(delta_min/price, abs(delta_vol))
elif mean_vol*price<delta_max:
vol = mean_vol
else:
log('单笔成交金额超过最大值，已按最大值挂单。')
vol = delta_max/price
if delta_vol>0:
# 跌停不买入
if code in limitdown_codes.index:
print('跌停不买入', code)
log('跌停不买入', code)
else:
# 不能超过涨停价
price = min(lastClose_snapshot[code]*(1+max_upndown), bidPrice_snapshot[code]*(tolerance+1))
buy(C, code, price, vol)
log('buy %s %s %s'%(code, price, vol))
#print('buy', code, price, vol)
else:
price = min(lastClose_snapshot[code]*(1-max_upndown), askPrice_snapshot[code]*(1-tolerance))
sell(C, code, price, vol)
log('sell %s %s %s'%(code, price, vol))
#print('sell', code, price, vol)
A.remain_times = A.remain_times-1
# 交易情况总结
def summary(C):
trader_orders = get_order().reset_index()
trader_orders = trader_orders[(trader_orders['remark']==strategy_name)&\
(trader_orders['sub_time']>A.start_time)&(trader_orders['sub_time']<A.summary_time)]
trader_orders['dealt_vol'] = trader_orders['dealt_vol']*trader_orders['trade_type'].map(lambda x: 1 if x==48 else -1)
traded_vol = trader_orders.groupby('code')['dealt_vol'].sum()
traded_vol = traded_vol.loc[traded_vol.sort_values(ascending=False).index]
log('成交')
log(traded_vol)
print(traded_vol)
with open(statfile, 'w') as f:
for i,v in traded_vol.items():
f.write(str(i)+','+str(v))
f.write('\n')
# 大概率不成交的单子进行撤单
def order_canceler(C):
cancel_order(C, wait_dur, strategy_name)
cancel_order_price(C, 0.01, strategy_name)
# 初始化函数 主程序
def init(C):
# 存储全局变量
global A
A = a()
# buy_start_time之前准备买，sell_start_time之前准备卖
if buy_start_time<sell_start_time:
if datetime.datetime.now().strftime("%H%M%S")<buy_start_time:
buy_prepare(C)
elif (datetime.datetime.now().strftime("%H%M%S")>buy_end_time)&\
(datetime.datetime.now().strftime("%H%M%S")<sell_start_time):
A.start_time = buy_start_time
A.summary_time = buy_summary_time
summary(C)
sell_prepare(C)
elif datetime.datetime.now().strftime("%H%M%S")>sell_end_time:
A.start_time = sell_start_time
A.summary_time = sell_summary_time
summary(C)
else:
if datetime.datetime.now().strftime("%H%M%S")<sell_start_time:
sell_prepare(C)
elif (datetime.datetime.now().strftime("%H%M%S")>sell_end_time)&\
(datetime.datetime.now().strftime("%H%M%S")<buy_start_time):
A.start_time = sell_start_time
A.summary_time = sell_summary_time
summary(C)
buy_prepare(C)
elif datetime.datetime.now().strftime("%H%M%S")>buy_end_time:
A.start_time = buy_start_time
A.summary_time = buy_summary_time
summary(C)
# 交易时间运行装饰器 交易日start到start+dur
def buy_trader_time(func):
def wrapper(*args, **kwargs):
today = datetime.datetime.now().date().strftime("%Y%m%d")
now = datetime.datetime.now().time()
if C.get_trading_dates('SH', today, today, 1, '1d'):
if (datetime.time(int(buy_start_time[:2]), int(buy_start_time[2:4]), int(buy_start_time[4:6])) \
<= now <= datetime.time(int(buy_end_time[:2]), int(buy_end_time[2:4]), int(buy_end_time[4:6]))):
return func(*args, **kwargs)
else:
pass
else:
pass
return wrapper
def sell_trader_time(func):
def wrapper(*args, **kwargs):
today = datetime.datetime.now().date().strftime("%Y%m%d")
now = datetime.datetime.now().time()
if C.get_trading_dates('SH', today, today, 1, '1d'):
if (datetime.time(int(sell_start_time[:2]), int(sell_start_time[2:4]), int(sell_start_time[4:6])) \
<= now <= datetime.time(int(sell_end_time[:2]), int(sell_end_time[2:4]), int(sell_end_time[4:6]))):
return func(*args, **kwargs)
else:
pass
else:
pass
return wrapper
def trade_time(func):
def wrapper(*args, **kwargs):
today = datetime.datetime.now().date().strftime("%Y%m%d")
now = datetime.datetime.now().time()
if C.get_trading_dates('SH', today, today, 1, '1d'):
if (datetime.time(9, 30) <= now <= datetime.time(11, 30)) or \
(datetime.time(13, 00) <= now <= datetime.time(15, 0, 0)):
return func(*args, **kwargs)
else:
pass
#print('非交易时间，不运行')
else:
pass
#print('非交易日，不运行')
return wrapper
def trade_date(func):
def wrapper(*args, **kwargs):
today = datetime.datetime.now().date().strftime("%Y%m%d")
now = datetime.datetime.now().time()
if C.get_trading_dates('SH', today, today, 1, '1d'):
return func(*args, **kwargs)
else:
pass
return wrapper
# 挂载定时函数
global f0, f1, f2, f_summary
f0 = trade_time(order_canceler) # 定时、按条件撤单程序
C.run_time('f0', "1nSecond", "2022-08-01 09:15:00", "SH") # 每秒检查撤单
C.run_time('buy_prepare', "1d", "2022-08-01 %s:%s:%s"%(buy_prepare_time[:2], buy_prepare_time[2:4], buy_prepare_time[4:6]),\
"SH") # 买入初始化函数
f1 = buy_trader_time(trader)
C.run_time('f1', "%snSecond"%interval, "2022-08-01 09:15:00", "SH") # 交易员
f_summary = trade_date(summary)
C.run_time('f_summary', "1d", "2022-08-01 %s:%s:%s"%(buy_summary_time[:2], buy_summary_time[2:4], buy_summary_time[4:6]),\
"SH") # 记录买入数量
C.run_time('sell_prepare', "1d", "2022-08-01 %s:%s:%s"%(sell_prepare_time[:2], sell_prepare_time[2:4], sell_prepare_time[4:6]),\
"SH") # 买入初始化函数
f2 = sell_trader_time(trader)
C.run_time('f2', "%snSecond"%interval, "2022-08-01 09:15:00", "SH") # 交易员
C.run_time('f_summary', "1d", "2022-08-01 %s:%s:%s"%(sell_summary_time[:2], sell_summary_time[2:4], sell_summary_time[4:6]),\
"SH") # 记录卖出数量
# 读取图形界面传入的ACCOUNT
global ACCOUNT
ACCOUNT = account if 'account' in globals() else ACCOUNT