The right way to access multiple timeframes data?

Quỳnh H Nguyễn

Hi all,

I got a simple issue when using multiple timeframes data:

data1 = bt.feeds.PandasData(dataname=data_df, timeframe=bt.TimeFrame.Minutes, compression=1)

cerebro.adddata(data1, name='M1')
cerebro.resampledata(data1, name='M5', timeframe=bt.TimeFrame.Minutes, compression=5)

But in next(self) function of strategy I could not access the second data. It print if I used only one data. When add 2 data, the next function is missed (no print at all).

def next(self):
    print(self.datas[0].close[0])
    print(self.datas[1].close[0])

So what is the right way to access multiple timeframes data in strategy class? I tried many search result here, but no way to access them.

run-out

@quỳnh-h-nguyễn From the information you have given, that should be working. Please try to add your entire code next time to assist us in answering your question.

Here is a sample of code to show you how to add data and print.

import backtrader as bt

class Strategy(bt.Strategy):

    def log(self, txt, dt=None):
        """ Logging function fot this strategy"""
        dt = dt or self.data.datetime[0]
        if isinstance(dt, float):
            dt = bt.num2date(dt)
        print("%s, %s" % (dt, txt))

    def print_signal(self, dline=0):
        self.log(
            f"{self.datas[dline]._name}, "
            f"o {self.datas[dline].open[0]:7.2f} "
            f"h {self.datas[dline].high[0]:7.2f} "
            f"l {self.datas[dline].low[0]:7.2f} "
            f"c {self.datas[dline].close[0]:7.2f} "
            f"v {self.datas[dline].volume[0]:7.0f} "
        )


    def next(self):
        self.print_signal(dline=0)
        self.print_signal(dline=1)

if __name__ == "__main__":

    cerebro = bt.Cerebro()

    data = bt.feeds.GenericCSVData(
        dataname="data/dev.csv",
        dtformat=("%Y-%m-%d %H:%M:%S"),
        timeframe=bt.TimeFrame.Minutes,
        compression=1,
        date=0,
        high=1,
        low=2,
        open=3,
        close=4,
        volume=6,
    )

    cerebro.adddata(data, name='m1')
    cerebro.resampledata(data, timeframe=bt.TimeFrame.Minutes, compression=15, name="m15")

    cerebro.addstrategy(Strategy)

    # Execute
    cerebro.run()

Quỳnh H Nguyễn

Wow, thanks so much @run-out !

I found the problem in data sample. Because the sample is not big enough for a indicator parameter. I used a indicator HullMovingAverage with a big period, so with the small timeframe it is normal, but in the large timeframe it need a bigger size of input data.

That's why cerebro plots running result, but not print log.

P/S: I will add entire code next question. Thanks for your advice!