def run_policy():
p = live_policy_runner.LivePolicySwitch()
s = boll_pramid.Strategy_Boll_Pre(data_interface.TdxData())
if agl.is_function(s.setParams):
s.setParams()
p.Regist(s)
while 1:
agl.tic()
p.Run()
agl.toc()
time.sleep(3)
if stock.IsShouPan():
break
def main(args):
agl.tic()
BackTestPolicy.Test()
agl.toc()
print("end")
#测试策略， 为了并行计算， 需要使用这种格式的函数定义
def Run(codes='', task_id=0):
from pypublish import publish
#设置策略参数
def setParams(s):
if 0: s = Strategy_Boll
s.setParams(trade_num = 300,
pl=publish.Publish()
)
if codes == '':
codes = ['300033']
#现在的5分钟线在2017-5-15之后才有
backtest_policy.test_strategy(codes, BollFenCangKline, setParams, day_num=20, mode=myenum.hisdat_mode,
start_day='2016-10-20', end_day='2017-10-1'
)
def calcYinKui(price, chengben):
return (price - chengben)/chengben
if __name__ == "__main__":
is_multi = 0
#is_multi = 1
if not is_multi:
Run()
else:
codes = stock.DataSources.getCodes()
cpu_num = 5
#codes = stock.get_codes(myenum.randn, cpu_num*1)
backtest_policy.MultiProcessRun(cpu_num, codes, Run, __file__)
agl.toc()