Datastream Data For BackTrader

Aleniles
Aleniles Explorer
in Datastream

Hello, is there someone that coud help to feed Datastream data into Backtrader using the following example ?

from datetime import datetime

import backtrader as bt



# Create a subclass of Strategy to define the indicators and logic



class SmaCross(bt.Strategy):

    # list of parameters which are configurable for the strategy

    params = dict(

        pfast=10,  # period for the fast moving average

        pslow=30   # period for the slow moving average

    )



    def __init__(self):

        sma1 = bt.ind.SMA(period=self.p.pfast)  # fast moving average

        sma2 = bt.ind.SMA(period=self.p.pslow)  # slow moving average

        self.crossover = bt.ind.CrossOver(sma1, sma2)  # crossover signal



    def next(self):

        if not self.position:  # not in the market

            if self.crossover > 0:  # if fast crosses slow to the upside

                self.buy()  # enter long



        elif self.crossover < 0:  # in the market & cross to the downside



            self.close()  # close long position



# create a "Cerebro" engine instance

cerebro = bt.Cerebro()  



# Create a data feed

data = ds.get_data(tickers='@MSFT';, fields=['PO','PH','PL','P','RI','VO'], start='-5Y', end='0D', freq='D')

cerebro.adddata(data)  # Add the data feed



cerebro.addstrategy(SmaCross)  # Add the trading strategy

cerebro.run()  # run it all

cerebro.plot()  # and plot it with a single command


The cerebro.adddata(data) # Add the data feed gives an error.

Any help would be highly appreciated !

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Best Answer

  • Jirapongse
    Jirapongse ✭✭✭✭✭
    Answer ✓

    @Aleniles

    You need to use the bt.feeds.PandasData method instead.

    The code looks like this.


    datads = ds.get_data(tickers='@MSFT';, fields=['PO','PH','PL','P','VO'], start='-5Y', end='0D', freq='D')
    datads.columns = datads.columns.droplevel()
    datads.index = pd.to_datetime(datads.index, format='%Y-%m-%d')
    datads = datads.rename(columns={"PO": "Open", 
                           "PH":"High",
                           "PL":"Low",
                           "P":"Close",
                           "VO": "Volume"})


    data = bt.feeds.PandasData(dataname=datads.dropna())

    cerebro.adddata(data)


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