from zipline.api import (add_history, 
     history, 
     order_target_percent,
     record, 
     symbol)
import talib 
def initialize(context):
   context.secs = [ symbol('SPY') ]
   context.history_depth  = 30
   context.iwarmup       = 0 
   add_history(30, '1d', 'price')
   context.BBANDS_timeperiod = 16
   context.BBANDS_nbdevup    = 1.819
   context.BBANDS_nbdevdn    = 1.470
   UseParams = False
   try:
      Nparams=len(context.algo_params)
      if Nparams ==  3 :
         UseParams = True
      else:
         print 'len context.algo_params is',Nparams,' expecting 3'
   except Exception as e:
      print 'context.algo_params not passed'
   if UseParams:
      print 'Setting Algo parameters via passed algo_params'
      context.BBANDS_timeperiod = context.algo_params['timeperiod']
      context.BBANDS_nbdevup    = context.algo_params['nbdevup']
      context.BBANDS_nbdevdn    = context.algo_params['nbdevdn']
def handle_data(context, data):
   context.iwarmup = context.iwarmup + 1
   if context.iwarmup <= ( context.history_depth + 1 ) :
      return
   dfHistD = history(30, '1d', 'price')
   S=context.secs[0]
   CurP=data[S].price
   BolU,BolM,BolL = talib.BBANDS(
      dfHistD[S].values,
      timeperiod=context.BBANDS_timeperiod,
      nbdevup=context.BBANDS_nbdevup,
      nbdevdn=context.BBANDS_nbdevdn,
      matype=0)
   record(CurP=CurP,BolU=BolU[-1],BolM=BolM[-1],BolL=BolL[-1])
   if CurP < BolL[-1] :
      order_target_percent(S,+0.97)
   else:
      if CurP > BolU[-1] :
         order_target_percent(S,-0.97)
   return