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Interactive brokers never finishes the script, even there is no error
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I 0ma using IB data feed in my strategy. Strategy works till end, when it hangs and doesn't show anything. Before, when I was using one asset the strategy IB feed works, but know, with 2 asset, it doesn't. It doesn't return any error, just hangs and I have to stop the process in my command line.
I had similar problem before: https://community.backtrader.com/topic/3021/interactive-brokers-hang-and-plot/3, but I solved it by removing
cerebro.plot(I used quantstats instead).Here is the cerebro part of my code (I don't thing the problem is in strategy):
def run(args=None): # parse args args = parse_args(args) # Create a cerebro entity cerebro = bt.Cerebro(stdstats=False, live=False, preload=False) # Definetrade option """ You have 3 options: - backtest (IS_BACKTEST=True, IS_LIVE=False) - paper trade (IS_BACKTEST=False, IS_LIVE=False) - live trade (IS_BACKTEST=False, IS_LIVE=True) """ broker = args.broker IS_BACKTEST = args.isbacktest IS_LIVE = args.islive if broker == 'alpaca': symbol = "SPY" elif broker == 'ib': symbol = "SPY-STK-SMART-USD" # Add a strategy cerebro.addstrategy(ExuberStrategy) # Data API store if broker == 'alpaca': store = alpaca_backtrader_api.AlpacaStore( key_id=ALPACA_API_KEY, secret_key=ALPACA_SECRET_KEY, paper=IS_LIVE, usePolygon=USE_POLYGON ) DataFactory = store.getdata # or use alpaca_backtrader_api.AlpacaData elif broker == 'ib': # IB store store=bt.stores.IBStore(host="127.0.0.1", port=7496, clientId=14) # Data feed args from_date = args.fromdate from_date = datetime.datetime.strptime(from_date, '%Y-%m-%d') to_date = args.todate to_date = datetime.datetime.strptime(to_date, '%Y-%m-%d') timeframe = bt.TimeFrame.TFrame(args.timeframedata) compression = args.compression compression_resamaple = args.cpresample timezone = pytz.timezone("America/New_York") # Data feed if IS_BACKTEST: stockkwargs = dict( timeframe=bt.TimeFrame.Minutes, historical=True, fromdate=from_date, todate=to_date, compression=compression, tz=timezone ) if broker == 'alpaca': data0 = DataFactory(dataname=symbol, **stockkwargs) elif broker == 'ib': data0 = store.getdata(dataname=symbol, **stockkwargs) data1 = store.getdata(dataname='VIX-IND-CBOE-USD', **stockkwargs) cerebro.resampledata(data1, timeframe=bt.TimeFrame.Minutes, compression=compression_resamaple) cerebro.resampledata(data0, timeframe=bt.TimeFrame.Minutes, compression=compression_resamaple) else: stockkwargs = dict( timeframe=bt.TimeFrame.Seconds, historical=False, # only historical download qcheck=2.0, # timeout in seconds (float) to check for events # fromdate=from_date, # get data from.. # todate=datetime.datetime(2020, 9, 22), # get data from.. # latethrough=False, # let late samples through # tradename=None # use a different asset as order target ) data0 = store.getdata(dataname=symbol, **stockkwargs) cerebro.resampledata(data0, timeframe=timeframe, compression=compression_resamaple) # or just alpaca_backtrader_api.AlpacaBroker() if IS_LIVE: broker = store.getbroker() cerebro.setbroker(broker) # set cash if backtest if IS_BACKTEST: # backtrader broker set initial simulated cash cerebro.broker.setcash(50000.0) # Set sizer cerebro.addsizer(bt.sizers.AllInSizer) # Set the commission cerebro.broker.setcommission(commission=0.01, leverage=2, commtype=bt.commissions.CommInfoBase.COMM_FIXED) # Analyzer cerebro.addanalyzer(bt.analyzers.PyFolio, _name='PyFolio') # check returns and banchmarks # if args.timereturn: # cerebro.addobserver(bt.observers.TimeReturn, # timeframe=TIMEFRAMES[args.timeframe]) # else: # benchdata = data0 # if args.benchdata1: # data1 = DataFactory(dataname='SPY', historical=True, # fromdate=from_date, # timeframe=bt.TimeFrame.Minutes, compression=60) # cerebro.adddata(data1, name='Data1') # benchdata = data1 # cerebro.addobserver(bt.observers.Benchmark, # data=benchdata, # timeframe=TIMEFRAMES[args.timeframe]) # save data file_name = f'single_{symbol}_{from_date.strftime("%Y-%m-%d")}_{datetime.datetime.now().strftime("%Y-%m-%d-%H-%M-%S")}' # cerebro.addwriter(bt.WriterFile, csv=True, out='log_' + file_name + '.csv') # Run over everything cerebro.run() print('Krsj') #strat = results[0] # ---- Format the values from results ---- #portfolio_stats = strat.analyzers.getbyname('PyFolio') #returns, positions, transactions, gross_lev = portfolio_stats.get_pf_items() #returns.index = returns.index.tz_convert(None) # ---------------------------------------- # Benchmark # raw data # dtime = [bt.utils.date.num2date(x) for x in strat.data_datetime.array] # dtime = pd.to_datetime(dtime) # close = pd.Series(strat.data_close.array.tolist(), index=dtime) # close = close.resample('D').last().dropna() # # returns_benchmark = close.pct_change().dropna() # returns_bm = quantstats.utils.to_returns(close) # Quantstats report #quantstats.reports.html( # returns, benchmark='SPY', # output='stats_' + file_name + '.html', # title='BackCUSUM Volatility strategy for ' + symbol) def parse_args(pargs=None): parser = argparse.ArgumentParser( formatter_class=argparse.ArgumentDefaultsHelpFormatter, description=( 'Backtrader exuber' ) ) # Defaults for dates parser.add_argument('--broker', default='ib', choices=['ib', 'alpaca'], required=True, action='store', help='Broker to use: alpaca or IB' ) parser.add_argument('--compression', default=1, type=int, required=False, action='store', help='Compression') parser.add_argument('--timeframedata', default='Minutes', choices=bt.TimeFrame.Names, required=False, action='store', help='TimeFrame for Resample/Replay') parser.add_argument('--cpresample', default=5, type=int, required=False, action='store', help='Compression for Resample/Replay') parser.add_argument('--isbacktest', required=False, action='store_true', help='Do only historical download') parser.add_argument('--islive', required=False, action='store_true', help='Do only historical download') # parser.add_argument('--historical', # required=False, action='store_true', # help='Do only historical download') parser.add_argument('--fromdate', required=False, default='2020-05-01', help='Date[time] in YYYY-MM-DD[THH:MM:SS] format') parser.add_argument('--todate', required=False, default='2020-11-30', help='Date[time] in YYYY-MM-DD[THH:MM:SS] format') parser.add_argument('--benchdata1', required=False, action='store_true', help=('Benchmark against data1')) parser.add_argument('--timereturn', required=False, action='store_true', default=None, help=('Use TimeReturn observer instead of Benchmark')) parser.add_argument('--timeframe', required=False, action='store', default=None, choices=TIMEFRAMES.keys(), help=('TimeFrame to apply to the Observer')) return parser.parse_args(pargs) if __name__ == '__main__': run()I commented many parts because I tried to figure out where is the problem, but I can't find it.
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The problem was in time zone. When I removed timezone from store it worked.
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I was wrong!!!
The problem is not in timezone. I solved the problem by using
oldsync=Truein cerebro!But if I use this option, new problems arise I will explain in next topic.
