Hi,

I have built all my indicators, analyzers, and observers, run my backtests, and now I'm ready to look at deploying a strategy live. I've been trying for the past few days now to integrate Interactive Brokers with Backtrader to just start receiving some historical data - I've tried following all the sample scripts, blog posts, medium posts, docs, everything. However, I just cannot get it to return data other than anything FX (e.g. EUR.USD-CASH-IDEALPRO). See below for the ibtest.py version I'm using, although as mentioned above, I have tried all of the different code samples.

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

import argparse
import datetime

# The above could be sent to an independent module
import backtrader as bt
from backtrader.utils import flushfile  # win32 quick stdout flushing


class TestStrategy(bt.Strategy):
    params = dict(
        smaperiod=5,
        trade=False,
        stake=10,
        exectype=bt.Order.Market,
        stopafter=0,
        valid=None,
        cancel=0,
        donotsell=False,
    )

    def __init__(self):
        # To control operation entries
        self.orderid = list()
        self.order = None

        self.counttostop = 0
        self.datastatus = 0

        # Create SMA on 2nd data
        self.sma = bt.indicators.MovAv.SMA(self.data, period=self.p.smaperiod)

        print('--------------------------------------------------')
        print('Strategy Created')
        print('--------------------------------------------------')

    def notify_data(self, data, status, *args, **kwargs):
        print('*' * 5, 'DATA NOTIF:', data._getstatusname(status), *args)
        if status == data.LIVE:
            self.counttostop = self.p.stopafter
            self.datastatus = 1

    def notify_store(self, msg, *args, **kwargs):
        print('*' * 5, 'STORE NOTIF:', msg)

    def notify_order(self, order):
        if order.status in [order.Completed, order.Cancelled, order.Rejected]:
            self.order = None

        print('-' * 50, 'ORDER BEGIN', datetime.datetime.now())
        print(order)
        print('-' * 50, 'ORDER END')

    def notify_trade(self, trade):
        print('-' * 50, 'TRADE BEGIN', datetime.datetime.now())
        print(trade)
        print('-' * 50, 'TRADE END')

    def prenext(self):
        self.next(frompre=True)

    def next(self, frompre=False):
        txt = list()
        txt.append('%04d' % len(self))
        dtfmt = '%Y-%m-%dT%H:%M:%S.%f'
        txt.append('%s' % self.data.datetime.datetime(0).strftime(dtfmt))
        txt.append('O: {:.5f}'.format(self.data.open[0]))
        txt.append('H: {:.5f}'.format(self.data.high[0]))
        txt.append('L: {:.5f}'.format(self.data.low[0]))
        txt.append('C: {:.5f}'.format(self.data.close[0]))
        # txt.append('{}'.format(self.data.volume[0]))
        # txt.append('{}'.format(self.data.openinterest[0]))
        # txt.append('{}'.format(self.sma[0]))
        print(', '.join(txt))

        if len(self.datas) > 1:
            txt = list()
            txt.append('%04d' % len(self))
            dtfmt = '%Y-%m-%dT%H:%M:%S.%f'
            txt.append('%s' % self.data1.datetime.datetime(0).strftime(dtfmt))
            txt.append('{}'.format(self.data1.open[0]))
            txt.append('{}'.format(self.data1.high[0]))
            txt.append('{}'.format(self.data1.low[0]))
            txt.append('{}'.format(self.data1.close[0]))
            txt.append('{}'.format(self.data1.volume[0]))
            txt.append('{}'.format(self.data1.openinterest[0]))
            txt.append('{}'.format(float('NaN')))
            print(', '.join(txt))

        if self.counttostop:  # stop after x live lines
            self.counttostop -= 1
            if not self.counttostop:
                self.env.runstop()
                return

        if not self.p.trade:
            return

        if self.datastatus and not self.position and len(self.orderid) < 1:
            self.order = self.buy(size=self.p.stake,
                                  exectype=self.p.exectype,
                                  price=round(self.data0.close[0] * 0.90, 2),
                                  valid=self.p.valid)

            self.orderid.append(self.order)
        elif self.position.size > 0 and not self.p.donotsell:
            if self.order is None:
                self.order = self.sell(size=self.p.stake // 2,
                                       exectype=bt.Order.Market,
                                       price=self.data0.close[0])

        elif self.order is not None and self.p.cancel:
            if self.datastatus > self.p.cancel:
                self.cancel(self.order)

        if self.datastatus:
            self.datastatus += 1

    def start(self):
        if self.data0.contractdetails is not None:
            print('Timezone from ContractDetails: {}'.format(
                  self.data0.contractdetails.m_timeZoneId))

        header = ['Datetime', 'Open', 'High', 'Low', 'Close', 'Volume',
                  'OpenInterest', 'SMA']
        print(', '.join(header))

        self.done = False


def runstrategy():
    args = parse_args([
        '--port', '7497',
        '--data0', 'TWTR',
        # '--data0', 'EUR.USD-CASH-IDEALPRO',
        '--historical',
        '--fromdate', '2018-01-02',
        # '--no-backfill_start',
        # '--no-backfill',
        '--timeframe', bt.TimeFrame.Names[bt.TimeFrame.Days],
        '--compression', '1',
        '--timezone', 'NZ',
    ])

    # Create a cerebro
    cerebro = bt.Cerebro()

    storekwargs = dict(
        host=args.host, port=args.port,
        clientId=args.clientId, timeoffset=not args.no_timeoffset,
        reconnect=args.reconnect, timeout=args.timeout,
        notifyall=args.notifyall, _debug=args.debug
    )

    if args.usestore:
        ibstore = bt.stores.IBStore(**storekwargs)

    if args.broker:
        if args.usestore:
            broker = ibstore.getbroker()
        else:
            broker = bt.brokers.IBBroker(**storekwargs)

        cerebro.setbroker(broker)

    timeframe = bt.TimeFrame.TFrame(args.timeframe)
    if args.resample or args.replay:
        datatf = bt.TimeFrame.Ticks
        datacomp = 1
    else:
        datatf = timeframe
        datacomp = args.compression

    fromdate = None
    if args.fromdate:
        dtformat = '%Y-%m-%d' + ('T%H:%M:%S' * ('T' in args.fromdate))
        fromdate = datetime.datetime.strptime(args.fromdate, dtformat)

    IBDataFactory = ibstore.getdata if args.usestore else bt.feeds.IBData

    datakwargs = dict(
        timeframe=datatf, compression=datacomp,
        historical=args.historical, fromdate=fromdate,
        rtbar=args.rtbar,
        qcheck=args.qcheck,
        what=args.what,
        backfill_start=not args.no_backfill_start,
        backfill=not args.no_backfill,
        latethrough=args.latethrough,
        tz=args.timezone
    )

    if not args.usestore and not args.broker:   # neither store nor broker
        datakwargs.update(storekwargs)  # pass the store args over the data

    data0 = IBDataFactory(dataname=args.data0, **datakwargs)

    data1 = None
    if args.data1 is not None:
        data1 = IBDataFactory(dataname=args.data1, **datakwargs)

    rekwargs = dict(
        timeframe=timeframe, compression=args.compression,
        bar2edge=not args.no_bar2edge,
        adjbartime=not args.no_adjbartime,
        rightedge=not args.no_rightedge,
        takelate=not args.no_takelate,
    )

    if args.replay:
        cerebro.replaydata(dataname=data0, **rekwargs)

        if data1 is not None:
            cerebro.replaydata(dataname=data1, **rekwargs)

    elif args.resample:
        cerebro.resampledata(dataname=data0, **rekwargs)

        if data1 is not None:
            cerebro.resampledata(dataname=data1, **rekwargs)

    else:
        cerebro.adddata(data0)
        if data1 is not None:
            cerebro.adddata(data1)

    if args.valid is None:
        valid = None
    else:
        datetime.timedelta(seconds=args.valid)
    # Add the strategy
    cerebro.addstrategy(TestStrategy,
                        smaperiod=args.smaperiod,
                        trade=args.trade,
                        exectype=bt.Order.ExecType(args.exectype),
                        stake=args.stake,
                        stopafter=args.stopafter,
                        valid=valid,
                        cancel=args.cancel,
                        donotsell=args.donotsell)

    # Live data ... avoid long data accumulation by switching to "exactbars"
    cerebro.run(exactbars=args.exactbars)

    if args.plot and args.exactbars < 1:  # plot if possible
        cerebro.plot()


def parse_args(pargs=None):
    parser = argparse.ArgumentParser(
        formatter_class=argparse.ArgumentDefaultsHelpFormatter,
        description='Test Interactive Brokers integration')

    parser.add_argument('--exactbars', default=1, type=int,
                        required=False, action='store',
                        help='exactbars level, use 0/-1/-2 to enable plotting')

    parser.add_argument('--plot',
                        required=False, action='store_true',
                        help='Plot if possible')

    parser.add_argument('--stopafter', default=0, type=int,
                        required=False, action='store',
                        help='Stop after x lines of LIVE data')

    parser.add_argument('--usestore',
                        required=False, action='store_true',
                        help='Use the store pattern')

    parser.add_argument('--notifyall',
                        required=False, action='store_true',
                        help='Notify all messages to strategy as store notifs')

    parser.add_argument('--debug',
                        required=False, action='store_true',
                        help='Display all info received form IB')

    parser.add_argument('--host', default='127.0.0.1',
                        required=False, action='store',
                        help='Host for the Interactive Brokers TWS Connection')

    parser.add_argument('--qcheck', default=0.5, type=float,
                        required=False, action='store',
                        help=('Timeout for periodic '
                              'notification/resampling/replaying check'))

    parser.add_argument('--port', default=7496, type=int,
                        required=False, action='store',
                        help='Port for the Interactive Brokers TWS Connection')

    parser.add_argument('--clientId', default=None, type=int,
                        required=False, action='store',
                        help='Client Id to connect to TWS (default: random)')

    parser.add_argument('--no-timeoffset',
                        required=False, action='store_true',
                        help=('Do not Use TWS/System time offset for non '
                              'timestamped prices and to align resampling'))

    parser.add_argument('--reconnect', default=3, type=int,
                        required=False, action='store',
                        help='Number of recconnection attempts to TWS')

    parser.add_argument('--timeout', default=3.0, type=float,
                        required=False, action='store',
                        help='Timeout between reconnection attempts to TWS')

    parser.add_argument('--data0', default=None,
                        required=True, action='store',
                        help='data 0 into the system')

    parser.add_argument('--data1', default=None,
                        required=False, action='store',
                        help='data 1 into the system')

    parser.add_argument('--timezone', default=None,
                        required=False, action='store',
                        help='timezone to get time output into (pytz names)')

    parser.add_argument('--what', default=None,
                        required=False, action='store',
                        help='specific price type for historical requests')

    parser.add_argument('--no-backfill_start',
                        required=False, action='store_true',
                        help='Disable backfilling at the start')

    parser.add_argument('--latethrough',
                        required=False, action='store_true',
                        help=('if resampling replaying, adjusting time '
                              'and disabling time offset, let late samples '
                              'through'))

    parser.add_argument('--no-backfill',
                        required=False, action='store_true',
                        help='Disable backfilling after a disconnection')

    parser.add_argument('--rtbar', default=False,
                        required=False, action='store_true',
                        help='Use 5 seconds real time bar updates if possible')

    parser.add_argument('--historical',
                        required=False, action='store_true',
                        help='do only historical download')

    parser.add_argument('--fromdate',
                        required=False, action='store',
                        help=('Starting date for historical download '
                              'with format: YYYY-MM-DD[THH:MM:SS]'))

    parser.add_argument('--smaperiod', default=5, type=int,
                        required=False, action='store',
                        help='Period to apply to the Simple Moving Average')

    pgroup = parser.add_mutually_exclusive_group(required=False)

    pgroup.add_argument('--replay',
                        required=False, action='store_true',
                        help='replay to chosen timeframe')

    pgroup.add_argument('--resample',
                        required=False, action='store_true',
                        help='resample to chosen timeframe')

    parser.add_argument('--timeframe', default=bt.TimeFrame.Names[0],
                        choices=bt.TimeFrame.Names,
                        required=False, action='store',
                        help='TimeFrame for Resample/Replay')

    parser.add_argument('--compression', default=1, type=int,
                        required=False, action='store',
                        help='Compression for Resample/Replay')

    parser.add_argument('--no-takelate',
                        required=False, action='store_true',
                        help=('resample/replay, do not accept late samples '
                              'in new bar if the data source let them through '
                              '(latethrough)'))

    parser.add_argument('--no-bar2edge',
                        required=False, action='store_true',
                        help='no bar2edge for resample/replay')

    parser.add_argument('--no-adjbartime',
                        required=False, action='store_true',
                        help='no adjbartime for resample/replay')

    parser.add_argument('--no-rightedge',
                        required=False, action='store_true',
                        help='no rightedge for resample/replay')

    parser.add_argument('--broker',
                        required=False, action='store_true',
                        help='Use IB as broker')

    parser.add_argument('--trade',
                        required=False, action='store_true',
                        help='Do Sample Buy/Sell operations')

    parser.add_argument('--donotsell',
                        required=False, action='store_true',
                        help='Do not sell after a buy')

    parser.add_argument('--exectype', default=bt.Order.ExecTypes[0],
                        choices=bt.Order.ExecTypes,
                        required=False, action='store',
                        help='Execution to Use when opening position')

    parser.add_argument('--stake', default=10, type=int,
                        required=False, action='store',
                        help='Stake to use in buy operations')

    parser.add_argument('--valid', default=None, type=int,
                        required=False, action='store',
                        help='Seconds to keep the order alive (0 means DAY)')

    parser.add_argument('--cancel', default=0, type=int,
                        required=False, action='store',
                        help=('Cancel a buy order after n bars in operation,'
                              ' to be combined with orders like Limit'))

    if pargs is not None:
        return parser.parse_args(pargs)

    return parser.parse_args()


if __name__ == '__main__':
    runstrategy()

Running this script, and the others that have been "shown" to work, results in:

Server Version: 76
TWS Time at connection:20200205 16:02:32 NZST
--------------------------------------------------
Strategy Created
--------------------------------------------------
Timezone from ContractDetails: EST (Eastern Standard Time)
Datetime, Open, High, Low, Close, Volume, OpenInterest, SMA
***** STORE NOTIF: <error id=-1, errorCode=2104, errorMsg=Market data farm connection is OK:cashfarm>
***** STORE NOTIF: <error id=-1, errorCode=2104, errorMsg=Market data farm connection is OK:usfarm>
***** STORE NOTIF: <error id=-1, errorCode=2106, errorMsg=HMDS data farm connection is OK:cashhmds>
***** STORE NOTIF: <error id=-1, errorCode=2106, errorMsg=HMDS data farm connection is OK:hkhmds>
***** STORE NOTIF: <error id=-1, errorCode=2106, errorMsg=HMDS data farm connection is OK:ushmds>
***** STORE NOTIF: <error id=-1, errorCode=2158, errorMsg=Sec-def data farm connection is OK:secdefhk>
***** DATA NOTIF: DELAYED
***** DATA NOTIF: DISCONNECTED
***** STORE NOTIF: <error id=16777217, errorCode=162, errorMsg=Historical Market Data Service error message:No market data permissions for NYSE STK>

Process finished with exit code 0

I just cannot for the life of me figure out why I cannot get any historical data - inside TWS (and the STORE NOTIFs above), all the data connections are working. I've tried following all of the sample scripts (even uninstalling and reinstalling TWS to "perfectly" follow along with the examples), and while those are able to get the data coming through, mine never seem too.

Does anybody have any piece of information that may help me solve this issue? I really don't know what to do from here...

Many thanks in advance!

Problem solved, using numpy to calculate and feed the average of account value.

class AcctValue(bt.Observer):
    lines = ('value', 'ma')
    params = dict(ma_len=100)
    plotinfo = dict(plot=True, subplot=True)

    def next(self):
        self.l.value[0] = self._owner.broker.getvalue()
        self.l.ma[0] = np.average(self.l.value.get(size=self.p.ma_len))

Thanks for your help. I have the following:

class AcctValueSMA(bt.Indicator):
    lines = ('AcctValue', 'MA')
    params = dict(ma_len=20)

    def __init__(self, type):
        self.l.AcctValue = self._owner.broker.get_value()

        if type == 'SMA':
            self.l.MA = bt.ind.MovingAverageSimple(self.l.AcctValue, period=self.p.ma_len)
        elif type == 'EMA':
            self.l.MA = bt.ind.ExponentialMovingAverage(self.l.AcctValue, period=self.p.ma_len)

But I get:
TypeError: 'float' object is not callable

Is there a specific way to store and subsequently use the value of the broker in this case?

Hi,

I'm wanting to add a MA to the Equity Curve. I have tried:

class AcctValue(bt.Observer):
    alias = ('Value',)
    lines = ('value', 'ma')

    plotinfo = {"plot": True, "subplot": True}
    plotlines = dict(ma=dict(ls='-', color='black', _plotvalue=False, _plotvaluetag=False))

    def __init__(self):
        self.l.ma = bt.indicators.MovingAverageSimple(self.l.value, period=20)

    def next(self):
        self.l.value[0] = self._owner.broker.getvalue()

That results in:

The "ma" tag shows up, but no MA.
Any ideas for how I could achieve the desired outcome?

Thanks in advance!

@backtrader
My understanding is that self.close will close the entry order. From seeing the code at the link I attached, I assumed that attached bracket orders (SL and/or TP) had to still be cancelled manually (one of them, at least).

Commenting out both the parts of code you highlighted, results in running, and accurate looking, backtest. Could you clarify whether self.close will cancel an attached child order or whether we need to do it manually? Have I set up my ordering correctly?

@run-out
Hey, thank you for that. I plan on transferring one of my factor models over soon so that will be very useful as a start/reference point!

To be honest, I think it's more trouble with opening/closing the bracket orders, and keeping track of those orders. I just want something that I can trust there is no "funny business" going on where it is entering where it shouldn't, orders/trades are being accounted for etc. The "realest" possible backtest. :)

@backtrader
Ok, I see that now. That is the same way you have shown it to be done in the link I pointed out?

Can you give me an example of how to cleanly handle ordering and orders for a multi-data, long and short strategy? Or at least point me in the direction of getting me closer to that.

Thanks in advance.

Hi there,

For a few months now I have been piecing together different parts of a framework with backtrader to handle multiple datas and be able to trade both long and short. However, I keep running into an error. Firstly, I will summarise what the code should achieve, post the code, and then post the error. Any help in helping me get this strategy off the ground would be much appreciated!

Target:
For each data (1D timeframe) in the trading universe:
-> Is it a long environment or a short environment?

If long environment and not in trade already:
Does it meet conditions to take a long?
-> If yes, order with or without tp
-> If no, do nothing

If long environment and in a trade:
Does it meet condition to close trade?
-> If yes, close trade
-> If no, leave trade open / do nothing

Exactly vice versa for the short side logic.

Here is the code I currently have to try to achieve the above:
note: BackTrader is the folder where I keep my own creations, such as indicators.

import backtrader as bt
import math
from BackTrader import indicators

class NHL(bt.Strategy):
    params = (
        ('use_tp', True),
        ('tp_percent', 12),
        ('ma_fast_len', 10),
        ('ma_slow_len', 100),
        ('ind1_period', 80)
    )

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

    def __init__(self):
        self.name = 'Multi_Long_Short'

        self.inds = dict()
        self.trades = dict()
        self.orders = dict()

        self.cash = self.broker.get_value()
        self.risk = 0.01
        self.onePlot = False

        for i, d in enumerate(self.datas):
            plot_ind1 = True
            plot_vstop1 = True
            plot_vstop2 = False

            self.inds[d] = dict()
            self.inds[d]['ind1'] = indicators.Ind1(d, plot=plot_ind1, n=self.p.ind1_period)
            self.inds[d]['vstop1'] = indicators.Vol_Stop(d, mult=1, plot=plot_vstop1)
            self.inds[d]['vstop2'] = indicators.Vol_Stop(d, mult=2, plot=plot_vstop2)

            use_sma = False
            if use_sma:
                self.inds[d]['fast_ma'] = bt.indicators.SMA(d, period=self.p.ma_fast_len)
                self.inds[d]['slow_ma'] = bt.indicators.SMA(d, period=self.p.ma_slow_len)
            else:
                self.inds[d]['fast_ma'] = bt.indicators.ExponentialMovingAverage(d, period=self.p.ma_fast_len)
                self.inds[d]['slow_ma'] = bt.indicators.ExponentialMovingAverage(d, period=self.p.ma_slow_len)

            if i > 0:
                if self.onePlot:
                    d.plotinfo.plotmaster = self.datas[0]

    def notify_order(self, order):
        order_name = order.info.name
        d = order.data
        data_name = d._name
        order_price = order.executed.price

        if order.status in [order.Submitted, order.Accepted]:
            return

        if order.status in [order.Completed]:
            self.log('%s, %s, %s, Price: %.5f' % (data_name, self.name, order_name, order_price))

        elif order.status in [order.Canceled]:
            # if not order.info.name in ['Long SL', 'Short SL', 'Long Entry', 'Short Entry', 'Long TP', 'Short TP']:
                self.log('Order Canceled')
        elif order.status in [order.Margin, order.Rejected]:
            self.log('Order Margin/Rejected')

        if not order.alive():
            orders = self.orders[d]
            idx = orders.index(order)
            orders[idx] = None
            if all(x is None for x in orders):
                orders[:] = []

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

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

    def next(self):
        for i, d in enumerate(self.datas):
            name = d._name
            close = d.close[0]
            close1 = d.close[-1]
            high = d.high[0]
            low = d.low[0]
            self.log('{}: {}'.format(name, close))

            ind1_1 = self.inds[d]['ind1'].lines.ind1_1[0]
            ind1_2 = self.inds[d]['ind1'].lines.ind1_2[0]
            ma_fast = self.inds[d]['fast_ma'][0]
            ma_slow = self.inds[d]['slow_ma'][0]
            vstop1 = self.inds[d]['vstop1'][0]
            vstop2 = self.inds[d]['vstop2'][0]

            long_environment = ma_fast > ma_slow
            short_environment = ma_fast < ma_slow
            go_long = close >= ind1_1
            go_short = close <= ind1_2
            close_long = close < ma_fast
            close_short = close > ma_fast

            position = self.getposition(d).size
            r_percent = self.p.tp_percent / 100

            if not position and not self.orders.get(d, None):
                if long_environment and go_long:
                    sl = vstop2 if (close > vstop2) else (low - (close*0.01))
                    qty = math.floor(self.cash * self.risk / abs(close - sl))
                    qty = qty if (qty > 0) else 1 # Just in case
                    tp = close + (close*r_percent)

                    if self.p.use_tp:
                        # Open Long with TP
                        o1 = self.buy(data=d, price=close, size=qty, exectype=bt.Order.Limit, transmit=False)
                        o2 = self.sell(data=d, price=sl, size=o1.size, exectype=bt.Order.Stop, parent=o1, transmit=False)
                        o3 = self.sell(data=d, price=tp, size=o1.size, exectype=bt.Order.Limit, parent=o1, transmit=True)
                        o1.addinfo(name='Long Entry')
                        o2.addinfo(name='Long SL')
                        o3.addinfo(name='Long TP')
                        self.orders[d] = [o1, o2, o3]
                    else:
                        # Open Long without TP
                        o1 = self.buy(data=d, price=close, size=qty, exectype=bt.Order.Limit, transmit=False)
                        o2 = self.sell(data=d, price=sl, size=o1.size, exectype=bt.Order.Stop, parent=o1, transmit=True)
                        o1.addinfo(name='Long Entry')
                        o2.addinfo(name='Long SL')
                        self.orders[d] = [o1, o2]


                elif short_environment and go_short:
                    sl = vstop2 if (close < vstop2) else high + (close*0.01)
                    qty = math.floor(self.cash * self.risk / abs(close - sl))
                    qty = qty if (qty > 0) else 1 # Just in case
                    tp = close - (close*r_percent)

                    if self.p.use_tp:
                        # Open Short with TP
                        o1 = self.sell(data=d, price=close, size=qty, exectype=bt.Order.Limit, transmit=False)
                        o2 = self.buy(data=d, price=sl, size=o1.size, exectype=bt.Order.Stop, parent=o1, transmit=False)
                        o3 = self.buy(data=d, price=tp, size=o1.size, exectype=bt.Order.Limit, parent=o1, transmit=True)
                        o1.addinfo(name='Short Entry')
                        o2.addinfo(name='Short SL')
                        o3.addinfo(name='Short TP')
                        self.orders[d] = [o1, o2, o3]
                    else:
                        # Open Short without TP
                        o1 = self.sell(data=d, price=close, size=qty, exectype=bt.Order.Limit, transmit=False)
                        o2 = self.buy(data=d, price=sl, size=o1.size, exectype=bt.Order.Stop, parent=o1, transmit=True)
                        o1.addinfo(name='Short Entry')
                        o2.addinfo(name='Short SL')
                        self.orders[d] = [o1, o2]

            elif position:
                if (position > 0) and close_long:
                    # Close Long
                    long_close = self.close(data=d)
                    if long_close:
                        long_close.addinfo(name='Close Long')
                        self.orders[d].append(long_close)
                        self.cancel(self.orders[d][1])

                elif (position < 0) and close_short:
                    # Close Short
                    short_close = self.close(data=d)
                    if short_close:
                        short_close.addinfo(name='Close Short')
                        self.orders[d].append(short_close)
                        self.cancel(self.orders[d][1])

The above has been pieced together mainly through docs, examples, forum posts, etc.

Here is an example of the error that I am hitting at the moment:

Traceback (most recent call last):
  File "/Users/.../Desktop/Python Projects/AlgoTrading/.../backtester.py", line 170, in <module>
    run_strat()
  File "/Users/.../Desktop/Python Projects/AlgoTrading/.../backtester.py", line 88, in run_strat
    run = cerebro.run(stdstats=False, tradehistory=True)
  File "/anaconda3/lib/python3.7/site-packages/backtrader/cerebro.py", line 1127, in run
    runstrat = self.runstrategies(iterstrat)
  File "/anaconda3/lib/python3.7/site-packages/backtrader/cerebro.py", line 1293, in runstrategies
    self._runonce(runstrats)
  File "/anaconda3/lib/python3.7/site-packages/backtrader/cerebro.py", line 1695, in _runonce
    strat._oncepost(dt0)
  File "/anaconda3/lib/python3.7/site-packages/backtrader/strategy.py", line 309, in _oncepost
    self.next()
  File "/Users/.../Desktop/Python Projects/AlgoTrading/.../LT_2.py", line 120, in next
    self.cancel(self.orders[d][1])
IndexError: list index out of range

I am struggling to see where it is going wrong in achieving what I have in mind, the ordering and "orderbook" are implemented almost identically to:
https://www.backtrader.com/blog/posts/2017-04-09-multi-example/multi-example/

I believe what I have is very close to being fully functional for my purposes - can anyone help me get past this error and/or achieve what I would like in-full?

Please let me know if I need to provide more code.

Thanks in advance!

@backtrader
Sorry to bring up an old thread, but I'm still having issues with one aspect of the above.

I would like to access the returns information of each data within the strategy. I don't think this is currently possible - could you help me with this?

Thanks in advance!

@run-out
Thanks for your input! Unfortunately, I don't know ahead of time which assets I would like to plot.

I would like to access something rank-able, such as returns of each asset, and make plotting decisions based on that (top-performing, mean, bottom-performing - for example).

Any ideas or tips on achieving that?