Thanks for elaborating, this is the output;

016-03-31, Close, 1.44
2016-03-31, Close, 1.44
2016-03-31, Close, 1.44
2016-03-31, Close, 1.44
2016-03-31, Close, 1.44
2016-03-31, Close, 1.44
2016-03-31, Close, 1.44
2016-03-31, Close, 1.44
2016-04-01, Close, 1.44
Final Portfolio Value: 1000.44

I understand your point, but why is it not trading after putting the the timeframe and compression? what can be still wrong with the data?

Thanks,
The format of my data is DD/MM/YYYY, downloaded from yahoo historical prices, i didn't make any change afterwards. I actually don't need yahoo data, was just trying out...
So, my main problem is loading genericCSVdata, the data i have is 1 min time frame data, shall i download tick data (instrument/date/bid/ask format) and let backtrader resample?

This is my 1 min data

Local time	Open	High	Low	Close	Volume
29.02.2016 00:00:00.000	1.38606	1.38614	1.38591	1.38593	97.64
29.02.2016 00:01:00.000	1.38593	1.38616	1.38591	1.38598	142.93
29.02.2016 00:02:00.000	1.38599	1.38606	1.38596	1.38597	101.98

This is tick data

GBP/USD	20160601 00:00:00.133	1.44831	1.44842
GBP/USD	20160601 00:00:00.134	1.44831	1.44842
GBP/USD	20160601 00:00:00.294	1.44831	1.44842
GBP/USD	20160601 00:00:00.300	1.44831	1.44842

What changes do I need to make for it to work, please?

I got it, for the genericCSVdata i did not put timeframe, but the the data for yahooFinanceCSVData is downloaded from yahoo historical prices and it does have time frame and compression, so why am i getting the error.
Also, i just put the time frame and compression on my genericCSVdata code and run it, but the same result, no buy sell.

Hi,
I changed data to yahoo finance data

 modpath = os.path.dirname(os.path.abspath(sys.argv[0]))
    datapath = os.path.join(modpath, 'data/s&p500 daily.csv')
    
    data = btfeeds.YahooFinanceCSVData(
            
            
            dataname=datapath,
            #reversed=True,
            fromdate=datetime.datetime(2016, 5, 31),
            todate=datetime.datetime(2017, 5, 26),
            timeframe=bt.TimeFrame.Days,
            compression=1,
            name='GSPC'
            )

Got this error

 dt = date(int(dttxt[0:4]), int(dttxt[5:7]), int(dttxt[8:10]))

ValueError: invalid literal for int() with base 10: '31/0'

Thanks

Hi,
I am running this code below, with simple strategy, which should result in lots of buy/sell, but i don't see any happening and end portfolio values stays same.

from __future__ import (absolute_import, division, print_function,
                        unicode_literals)

import datetime  # For datetime objects
import os.path  # To manage paths
import sys  # To find out the script name (in argv[0])

# Import the backtrader platform
import backtrader as bt
import backtrader.feeds as btfeeds


# Create a Stratey
class TestStrategy(bt.Strategy):
    params = (
        ('maperiod', 15),
    )

    def log(self, txt, dt=None):
        ''' Logging function fot this strategy'''
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        # Keep a reference to the "close" line in the data[0] dataseries
        self.dataclose = self.datas[0].close

        # To keep track of pending orders and buy price/commission
        self.order = None
        self.buyprice = None
        self.buycomm = None

        # Add a MovingAverageSimple indicator
        self.sma = bt.indicators.SimpleMovingAverage(
            self.datas[0], period=self.params.maperiod)
        self.ADX= bt.indicators.DirectionalMovementIndex(self.data,period=12)
        self.ATR= bt.indicators.ATR(self.data,period=12)
        # Indicators for the plotting show
        bt.indicators.ExponentialMovingAverage(self.datas[0], period=25)
        '''
        bt.indicators.WeightedMovingAverage(self.datas[0], period=25,
                                            subplot=True)
        bt.indicators.StochasticSlow(self.datas[0])
        bt.indicators.MACDHisto(self.datas[0])
        rsi = bt.indicators.RSI(self.datas[0])
        bt.indicators.SmoothedMovingAverage(rsi, period=10)
        bt.indicators.ATR(self.datas[0], plot=False)
        '''

    def notify_order(self, order):
        if order.status in [order.Submitted, order.Accepted]:
            # Buy/Sell order submitted/accepted to/by broker - Nothing to do
            return

        # Check if an order has been completed
        # Attention: broker could reject order if not enougth cash
        if order.status in [order.Completed]:
            if order.isbuy():
                self.log(
                    'BUY EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
                    (order.executed.price,
                     order.executed.value,
                     order.executed.comm))

                self.buyprice = order.executed.price
                self.buycomm = order.executed.comm
            else:  # Sell
                self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
                         (order.executed.price,
                          order.executed.value,
                          order.executed.comm))

            self.bar_executed = len(self)

        elif order.status in [order.Canceled, order.Margin, order.Rejected]:
            self.log('Order Canceled/Margin/Rejected')

        # Write down: no pending order
        self.order = None

    def notify_trade(self, trade):
        if not trade.isclosed:
            return

        self.log('OPERATION PROFIT, GROSS %.2f, NET %.2f' %
                 (trade.pnl, trade.pnlcomm))

    def next(self):
        # Simply log the closing price of the series from the reference
        self.log('Close, %.2f' % self.dataclose[0])

        # Check if an order is pending ... if yes, we cannot send a 2nd one
        if self.order:
            return

        # Check if we are in the market
        if not self.position:
            

            # Not yet ... we MIGHT BUY if ...
          if (self.ADX[-1] > 35  
                  and self.ADX.DIplus[-1]>25 ):
              self.log('BUY CREATE, %.2f' % self.dataclose[0])
              self.order = self.buy()


              
                 
               
        else:
            
             if (self.ADX[-1] > 35 
                  and self.ADX.DIminus[-1]>25 ):
                 self.log('SELL CREATE, %.2f' % self.dataclose[0])
                 self.order = self.sell()
                 

            
                


if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()

    # Add a strategy
    cerebro.addstrategy(TestStrategy)

    # Datas are in a subfolder of the samples. Need to find where the script is
    # because it could have been called from anywhere
    modpath = os.path.dirname(os.path.abspath(sys.argv[0]))
    datapath = os.path.join(modpath, 'data/gbpusd 1min data.csv')
     # Create a Data Feed
    data = btfeeds.GenericCSVData(
    dataname= datapath,

    fromdate=datetime.datetime(2016, 3, 1),
    todate=datetime.datetime(2016,4 , 1),

    nullvalue=0.0,

    dtformat=('%d.%m.%Y %H:%M:%S.%f'),

    datetime=0,
    open=1,
    high=2,
    low=3,
    close=4,
    volume=5,
    openinterest=-1)

    # Add the Data Feed to Cerebro
    cerebro.adddata(data)

    # Set our desired cash start
    cerebro.broker.setcash(1000.0)

    # Add a FixedSize sizer according to the stake
    cerebro.addsizer(bt.sizers.FixedSize, stake=10)

    # Set the commission
    cerebro.broker.setcommission(commission=0.0)

    # Print out the starting conditions
    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())

    # Run over everything
    cerebro.run()

    # Print out the final result
    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())

    # Plot the result
    cerebro.plot()

Is something wrong with my strategy?
Thanks

Hi,
Is it possible to backtest/trade multiple instruments from one script? Any example?
Thanks

Hi,
Could you please elaborate, how to print data values from prenext in the strategy.
Thanks

Thanks,
I tried running the same script with commenting out indicator line, works fine, no error code.
Also, having same issue with my saved data in hard drive and data loading using btfeeds.GenericCSVData, some thing wrong with indicators?

from __future__ import (absolute_import, division, print_function,
                        unicode_literals)

import datetime  # For datetime objects
import os.path  # To manage paths
import sys  # To find out the script name (in argv[0])

# Import the backtrader platform
import backtrader as bt
import backtrader.feeds as btfeeds


# Create a Stratey
class TestStrategy(bt.Strategy):
   # params = (
    #    ('maperiod', 15),
    #)

    def log(self, txt, dt=None):
        ''' Logging function fot this strategy'''
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        # Keep a reference to the "close" line in the data[0] dataseries
        self.dataclose = self.datas[0].close

        # To keep track of pending orders and buy price/commission
        self.order = None
        self.buyprice = None
        self.buycomm = None

        # Add a MovingAverageSimple indicator
        self.sma = bt.indicators.SimpleMovingAverage(
            self.data, period=36)

        ''' 
       # Indicators for the plotting show
        bt.indicators.ExponentialMovingAverage(self.datas[0], period=25)
        bt.indicators.WeightedMovingAverage(self.datas[0], period=25,
                                            subplot=True)
        bt.indicators.StochasticSlow(self.datas[0])
        bt.indicators.MACDHisto(self.datas[0])
        rsi = bt.indicators.RSI(self.datas[0])
        bt.indicators.SmoothedMovingAverage(rsi, period=10)
        bt.indicators.ATR(self.datas[0], plot=False)
        '''

    def notify_order(self, order):
        if order.status in [order.Submitted, order.Accepted]:
            # Buy/Sell order submitted/accepted to/by broker - Nothing to do
            return

        # Check if an order has been completed
        # Attention: broker could reject order if not enougth cash
        if order.status in [order.Completed]:
            if order.isbuy():
                self.log(
                    'BUY EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
                    (order.executed.price,
                     order.executed.value,
                     order.executed.comm))

                self.buyprice = order.executed.price
                self.buycomm = order.executed.comm
            else:  # Sell
                self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
                         (order.executed.price,
                          order.executed.value,
                          order.executed.comm))

            self.bar_executed = len(self)

        elif order.status in [order.Canceled, order.Margin, order.Rejected]:
            self.log('Order Canceled/Margin/Rejected')

        # Write down: no pending order
        self.order = None

    def notify_trade(self, trade):
        if not trade.isclosed:
            return

        self.log('OPERATION PROFIT, GROSS %.2f, NET %.2f' %
                 (trade.pnl, trade.pnlcomm))

    def next(self):
        # Simply log the closing price of the series from the reference
        self.log('Close, %.2f' % self.dataclose[0])

        # Check if an order is pending ... if yes, we cannot send a 2nd one
        if self.order:
            return

        # Check if we are in the market
        if not self.position:

            # Not yet ... we MIGHT BUY if ...
            if self.dataclose[0] > self.sma[0]:

                # BUY, BUY, BUY!!! (with all possible default parameters)
                self.log('BUY CREATE, %.2f' % self.dataclose[0])

                # Keep track of the created order to avoid a 2nd order
                self.order = self.buy()

        else:

            if self.dataclose[0] < self.sma[0]:
                # SELL, SELL, SELL!!! (with all possible default parameters)
                self.log('SELL CREATE, %.2f' % self.dataclose[0])

                # Keep track of the created order to avoid a 2nd order
                self.order = self.sell()


if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()

    # Add a strategy
    cerebro.addstrategy(TestStrategy)

    # Datas are in a subfolder of the samples. Need to find where the script is
    # because it could have been called from anywhere
    modpath = os.path.dirname(os.path.abspath(sys.argv[0]))
    datapath = os.path.join(modpath, 'data/msft dt.csv')
    
    data = btfeeds.YahooFinanceCSVData(
            
            
            dataname=datapath,
            reversed=True,
            fromdate=datetime.datetime(2016, 4, 1),
            todate=datetime.datetime(2016, 12, 30),
            timeframe=bt.TimeFrame.Days,
            compression=1,
            name='msft'
            )

  
    

    # Add the Data Feed to Cerebro
    cerebro.adddata(data)

    # Set our desired cash start
    cerebro.broker.setcash(1000.0)

    # Add a FixedSize sizer according to the stake
    cerebro.addsizer(bt.sizers.FixedSize, stake=10)

    # Set the commission
    cerebro.broker.setcommission(commission=0.0)

    # Print out the starting conditions
    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())

    # Run over everything
    cerebro.run()

    # Print out the final result
    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())

    # Plot the result
    #cerebro.plot()

Getting this error msg:

dst[i] = math.fsum(src[i - period + 1:i + 1]) / period

IndexError: array assignment index out of range

Please help!