@backtrader So obvious (when you know how) got it. Removed the globals and try except and got it to work! Thank you sir!

Many thanks! got it working now - great work.

Hi,

thanks for the hard work here.

when installing I get the error:

byte-compiling build\bdist.win-amd64\egg\backtrader_plotting\bokeh\bokeh.py to bokeh.cpython-35.pyc
  File "build\bdist.win-amd64\egg\backtrader_plotting\bokeh\bokeh.py", line 41
    self.figures: List[Figure] = []
                ^
SyntaxError: invalid syntax

Any ideas what I am doing wrong pls?

Hi,

after posting "Create orders from CSV file" and getting quick and helpful feedabck. I have started using backtrader again and thanks to the great documentation I have now gotten to the stage where I can push in my own orders. I am now trying to:

Optimize against stop order entry price and trailing stop distance.

I have :

1. declared parameters to be optimized
2. referenced them under self.params.x
3. added the “Strategy” hook stop method
4. called the cerebro.optstategy function

However I keep getting the same value back from the broker for all variances of the optimization parameters.

Here is my code:

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 btfeed
import pandas as pd

class PlotScheme(object):
    def __init__(self):

        # Default plotstyle for the OHLC bars which (line -> line on close)
        # Other options: 'bar' and 'candle'
        self.style = 'line'


class dataFeed(btfeed.GenericCSVData):
    params = (
        ('dtformat', '%Y-%m-%d %H:%M:%S'),
        ('datetime', 0),
        ('open', 1),
        ('high', 2),
        ('low', 3),
        ('close', 4),
        ('volume', 5),
        ('openinterest', -1)
    )

# Create a Stratey
class TestStrategy(bt.Strategy):
    params = (
        ('trail', 10),
        ('distance', 3),)

    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.dataopen = self.datas[0].open
        self.datahigh = self.datas[0].high
        self.datalow = self.datas[0].low
        self.dataclose = self.datas[0].close
        self.datavolume = self.datas[0].volume

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

    def notify_order(self, order):
        if order.status in [order.Submitted, order.Accepted]:
            # Buy/Sell order submitted/accepted to/by broker - Nothing to do
            # print('Submitted/Accepted: ', str(self.data.datetime.time(0)))

            return

        # Check if an order has been completed
        # Attention: broker could reject order if not enough 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))
                print(str(self.data.datetime.time(0)))

                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))
                print(str(self.data.datetime.time(0)))

            self.bar_executed = len(self)

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

        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):
        global i,dt

        # Get datetime
        dt = self.datas[0].datetime.datetime()

        # Check if we are in the market
        try:
            # if not self.position:
            if orders['DATE'][i] == dt.strftime('%Y-%m-%d %H:%M:%S'):
                if orders['DIRECTION'][i] == 'BUY':
                    self.log('OPEN BUY ORDER, %.2f' % self.dataclose[0])
                    self.order = self.buy(exectype=bt.Order.StopTrail, price=float(self.dataclose[0] + self.params.distance), trailamount=self.params.trail, valid=bt.Order.DAY)
                elif orders['DIRECTION'][i] == 'SELL':
                    self.log('OPEN SELL ORDER, %.2f' % self.dataclose[0])
                    self.order = self.sell(exectype=bt.Order.StopTrail, price=float(self.dataclose[0] - self.params.distance), trailamount=self.params.trail, valid=bt.Order.DAY)
                i = i + 1

            if dt.strftime('%H:%M') == '21:00': self.close()

        except:
            pass

    def stop(self):
        self.log('(Start distance %2d, Trail distance %2d) Ending Value %.2f' %
                 (self.params.distance, self.params.trail, self.broker.getvalue()))


if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()
    i = 0
    state = False

    # Add a strategy
    # cerebro.addstrategy(TestStrategy)

    strats = cerebro.optstrategy(TestStrategy,distance=range(3,8), trail=range(3,8))

    datapath = os.path.join('backtrader/deepanalysis/US500/US50015m_bid_chart_data_with_vol.csv')

    # Create a Data Feed
    data = dataFeed(dataname=datapath, timeframe=bt.TimeFrame.Minutes, compression=15)

    # Read Orders

    orders = pd.read_csv('backtrader/deepanalysis/US500/US500_orders_20180601_to_20180815_Norm_priority.csv')

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

    # Set our desired cash start
    cerebro.broker.setcash(5000.0)

    # Add a FixedSize sizer according to the stake
    cerebro.addsizer(bt.sizers.FixedSize, stake=1)

    # 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())

Here is the output that i get:

C:\Users\jaspa\AppData\Local\conda\conda\envs\backtrader\python.exe C:/Users/jaspa/PycharmProjects/backtrader/US500_backtest_1.py
Starting Portfolio Value: 5000.00
2018-08-15, (Start distance  3, Trail distance  6) Ending Value 5000.00
2018-08-15, (Start distance  3, Trail distance  7) Ending Value 5000.00
2018-08-15, (Start distance  6, Trail distance  7) Ending Value 5000.00
2018-08-15, (Start distance  4, Trail distance  6) Ending Value 5000.00
2018-08-15, (Start distance  3, Trail distance  3) Ending Value 5000.00
2018-08-15, (Start distance  3, Trail distance  4) Ending Value 5000.00
2018-08-15, (Start distance  4, Trail distance  3) Ending Value 5000.00
2018-08-15, (Start distance  5, Trail distance  5) Ending Value 5000.00
2018-08-15, (Start distance  4, Trail distance  5) Ending Value 5000.00
2018-08-15, (Start distance  5, Trail distance  6) Ending Value 5000.00
2018-08-15, (Start distance  4, Trail distance  4) Ending Value 5000.00
2018-08-15, (Start distance  3, Trail distance  5) Ending Value 5000.00
2018-08-15, (Start distance  6, Trail distance  4) Ending Value 5000.00
2018-08-15, (Start distance  7, Trail distance  4) Ending Value 5000.00
2018-08-15, (Start distance  5, Trail distance  4) Ending Value 5000.00
2018-08-15, (Start distance  5, Trail distance  3) Ending Value 5000.00
2018-08-15, (Start distance  7, Trail distance  6) Ending Value 5000.00
2018-08-15, (Start distance  6, Trail distance  6) Ending Value 5000.00
2018-08-15, (Start distance  4, Trail distance  7) Ending Value 5000.00
2018-08-15, (Start distance  5, Trail distance  7) Ending Value 5000.00
2018-08-15, (Start distance  6, Trail distance  3) Ending Value 5000.00
2018-08-15, (Start distance  7, Trail distance  5) Ending Value 5000.00
2018-08-15, (Start distance  7, Trail distance  7) Ending Value 5000.00
2018-08-15, (Start distance  6, Trail distance  5) Ending Value 5000.00
2018-08-15, (Start distance  7, Trail distance  3) Ending Value 5000.00
Final Portfolio Value: 5000.00

Process finished with exit code 0

Here is the output I get when I run the strategy with the default parameter values:

C:\Users\jaspa\AppData\Local\conda\conda\envs\backtrader\python.exe C:/Users/jaspa/PycharmProjects/backtrader/US500_backtest_1.py
Starting Portfolio Value: 5000.00
2018-06-05, OPEN BUY ORDER, 2748.13
2018-06-05, BUY EXECUTED, Price: 2749.75, Cost: 2749.75, Comm 0.00
19:45:00
2018-06-05, SELL EXECUTED, Price: 2751.51, Cost: 2749.75, Comm 0.00
21:15:00
2018-06-05, OPERATION PROFIT, GROSS 1.76, NET 1.76
2018-06-06, OPEN SELL ORDER, 2755.69
2018-06-07, OPEN BUY ORDER, 2775.99
2018-06-07, BUY EXECUTED, Price: 2771.76, Cost: 2771.76, Comm 0.00
20:30:00
2018-06-07, SELL EXECUTED, Price: 2771.60, Cost: 2771.76, Comm 0.00
21:15:00
2018-06-07, OPERATION PROFIT, GROSS -0.16, NET -0.16
2018-06-08, OPEN SELL ORDER, 2765.90
2018-06-12, OPEN SELL ORDER, 2784.50
2018-06-13, OPEN SELL ORDER, 2788.59
2018-06-13, SELL EXECUTED, Price: 2780.88, Cost: -2780.88, Comm 0.00
19:00:00
2018-06-13, BUY EXECUTED, Price: 2773.30, Cost: -2780.88, Comm 0.00
21:15:00
2018-06-13, OPERATION PROFIT, GROSS 7.58, NET 7.58
2018-06-14, OPEN BUY ORDER, 2783.62
2018-06-15, OPEN BUY ORDER, 2769.40
2018-06-15, BUY EXECUTED, Price: 2776.40, Cost: 2776.40, Comm 0.00
19:15:00
2018-06-15, SELL EXECUTED, Price: 2779.87, Cost: 2776.40, Comm 0.00
21:15:00
2018-06-15, OPERATION PROFIT, GROSS 3.47, NET 3.47
2018-06-18, OPEN SELL ORDER, 2761.90
2018-06-19, OPEN SELL ORDER, 2752.10
2018-06-20, OPEN BUY ORDER, 2770.13
2018-06-21, OPEN BUY ORDER, 2762.47
2018-06-21, BUY EXECUTED, Price: 2760.22, Cost: 2760.22, Comm 0.00
16:45:00
2018-06-21, SELL EXECUTED, Price: 2749.00, Cost: 2760.22, Comm 0.00
21:15:00
2018-06-21, OPERATION PROFIT, GROSS -11.22, NET -11.22
2018-06-25, OPEN SELL ORDER, 2733.98
2018-06-25, SELL EXECUTED, Price: 2720.98, Cost: -2720.98, Comm 0.00
15:00:00
2018-06-25, BUY EXECUTED, Price: 2719.10, Cost: -2720.98, Comm 0.00
21:15:00
2018-06-25, OPERATION PROFIT, GROSS 1.88, NET 1.88
2018-06-26, OPEN BUY ORDER, 2724.19
2018-06-26, BUY EXECUTED, Price: 2730.26, Cost: 2730.26, Comm 0.00
18:00:00
2018-06-26, SELL EXECUTED, Price: 2725.91, Cost: 2730.26, Comm 0.00
21:15:00
2018-06-26, OPERATION PROFIT, GROSS -4.35, NET -4.35
2018-06-27, OPEN SELL ORDER, 2730.00
2018-06-27, SELL EXECUTED, Price: 2734.02, Cost: -2734.02, Comm 0.00
16:00:00
2018-06-27, BUY EXECUTED, Price: 2702.05, Cost: -2734.02, Comm 0.00
21:15:00
2018-06-27, OPERATION PROFIT, GROSS 31.97, NET 31.97
2018-06-28, OPEN BUY ORDER, 2699.73
2018-06-28, BUY EXECUTED, Price: 2707.06, Cost: 2707.06, Comm 0.00
16:00:00
2018-06-28, SELL EXECUTED, Price: 2717.05, Cost: 2707.06, Comm 0.00
21:15:00
2018-06-28, OPERATION PROFIT, GROSS 9.99, NET 9.99
2018-06-29, OPEN BUY ORDER, 2735.20
2018-06-29, BUY EXECUTED, Price: 2743.16, Cost: 2743.16, Comm 0.00
16:00:00
2018-06-29, SELL EXECUTED, Price: 2720.23, Cost: 2743.16, Comm 0.00
21:15:00
2018-06-29, OPERATION PROFIT, GROSS -22.93, NET -22.93
2018-07-30, OPEN BUY ORDER, 2812.63
2018-07-31, OPEN BUY ORDER, 2813.06
2018-07-31, BUY EXECUTED, Price: 2819.25, Cost: 2819.25, Comm 0.00
16:45:00
2018-07-31, SELL EXECUTED, Price: 2822.88, Cost: 2819.25, Comm 0.00
21:15:00
2018-07-31, OPERATION PROFIT, GROSS 3.63, NET 3.63
2018-08-01, OPEN SELL ORDER, 2819.48
2018-08-01, SELL EXECUTED, Price: 2814.76, Cost: -2814.76, Comm 0.00
16:45:00
2018-08-01, BUY EXECUTED, Price: 2809.82, Cost: -2814.76, Comm 0.00
21:15:00
2018-08-01, OPERATION PROFIT, GROSS 4.94, NET 4.94
2018-08-02, OPEN SELL ORDER, 2799.40
2018-08-03, OPEN BUY ORDER, 2830.09
2018-08-03, BUY EXECUTED, Price: 2838.84, Cost: 2838.84, Comm 0.00
20:00:00
2018-08-03, SELL EXECUTED, Price: 2838.85, Cost: 2838.84, Comm 0.00
21:15:00
2018-08-03, OPERATION PROFIT, GROSS 0.01, NET 0.01
2018-08-06, OPEN SELL ORDER, 2837.96
2018-08-07, OPEN SELL ORDER, 2858.17
2018-08-08, OPEN BUY ORDER, 2855.45
2018-08-09, OPEN SELL ORDER, 2856.91
2018-08-09, SELL EXECUTED, Price: 2851.92, Cost: -2851.92, Comm 0.00
20:45:00
2018-08-09, BUY EXECUTED, Price: 2851.81, Cost: -2851.92, Comm 0.00
21:15:00
2018-08-09, OPERATION PROFIT, GROSS 0.11, NET 0.11
2018-08-10, OPEN SELL ORDER, 2838.98
2018-08-10, SELL EXECUTED, Price: 2829.47, Cost: -2829.47, Comm 0.00
18:45:00
2018-08-10, BUY EXECUTED, Price: 2835.86, Cost: -2829.47, Comm 0.00
21:15:00
2018-08-10, OPERATION PROFIT, GROSS -6.39, NET -6.39
2018-08-13, OPEN BUY ORDER, 2837.68
2018-08-13, BUY EXECUTED, Price: 2831.50, Cost: 2831.50, Comm 0.00
19:15:00
2018-08-13, SELL EXECUTED, Price: 2824.10, Cost: 2831.50, Comm 0.00
21:15:00
2018-08-13, OPERATION PROFIT, GROSS -7.40, NET -7.40
2018-08-14, OPEN BUY ORDER, 2831.96
2018-08-14, BUY EXECUTED, Price: 2840.96, Cost: 2840.96, Comm 0.00
15:45:00
2018-08-14, SELL EXECUTED, Price: 2839.56, Cost: 2840.96, Comm 0.00
21:15:00
2018-08-14, OPERATION PROFIT, GROSS -1.40, NET -1.40
2018-08-15, OPEN SELL ORDER, 2822.43
2018-08-15, SELL EXECUTED, Price: 2809.43, Cost: -2809.43, Comm 0.00
15:00:00
2018-08-15, (Start distance  3, Trail distance 10) Ending Value 5010.83
Final Portfolio Value: 5010.83

Process finished with exit code 0

I'm sure it is probably something obvious but we all have to start somewhere :) All help greatly appreciated!

@backtrader great! And thank you. Can’t wait to get stuck into this in the morning!

Hi,

I have an external strategy that has already created my orders which have date/time stamps and order sizes.

I would like to:

1. import these orders and test against OHLC data that I have in CSV files
2. use backtrader to optimise with different stop and limit values
3. if possible test with trailing stops
4. if possible implement a mechanism that has a "trailing start" - where I monitor the status of the last closing bar and decide whether or not execute the order in this CSV file.

could somebody kindly tell me which of the above is possible with backtrader, and if possible, advise on how to implement?

@j45p41 Hi guys, with the additional info provided can you help me understand why my code is not processing trades? - thanks.

My apologies - i thought there was a problem due to discontinues dates.

here is my code in which I have disabled my analysers as they end up giving me a keyerror. When disabled I get a graph that does not execute trades.

import datetime
import time
import os.path
import sys
import backtrader as bt
import backtrader.feeds as btfeed
import ccxt
import csv
import io
import pandas as pd
from collections import OrderedDict
from multiprocessing import Pool, cpu_count
import math
import os



# DECLARE MODE FOR PROGRAM - OPTOMISATION OR STRATEGY
opt_mode = False
DEBUG = False

# LOG OUTPUT TO FILE
class Logger(object):
    def __init__(self, filename="Default.log"):
        self.terminal = sys.stdout
        self.log = open(filename, "a")

    def write(self, message):
        self.terminal.write(message)
        self.log.write(message)

    def flush(self):
        pass

# CSV INPUT FILE FORMAT CONFIGURATION
class dataFeed(btfeed.GenericCSVData):
    params = (
        ('dtformat', '%Y%m%d'),
        ('datetime', 0),
        ('open', 1),
        ('high', 2),
        ('low', 3),
        ('close', 4),
        ('volume', 5),
        ('openinterest', 6)
    )
class OrderObserver(bt.observer.Observer):
    lines = ('created', 'expired',)

    plotinfo = dict(plot=True, subplot=True, plotlinelabels=True)

    plotlines = dict(
        created=dict(marker='*', markersize=8.0, color='lime', fillstyle='full'),
        expired=dict(marker='s', markersize=8.0, color='red', fillstyle='full')
    )

    def next(self):
        for order in self._owner._orderspending:
            if order.data is not self.data:
                continue

            if not order.isbuy():
                continue

            # Only interested in "buy" orders, because the sell orders
            # in the strategy are Market orders and will be immediately
            # executed

            if order.status in [bt.Order.Accepted, bt.Order.Submitted]:
                self.lines.created[0] = order.created.price

            elif order.status in [bt.Order.Expired]:
                self.lines.expired[0] = order.created.price

# MAIN STRATEGY DEFINITION - DEFINE VALUES HERE FOR NON-OPTOMISATION MODE
class firstStrategy(bt.Strategy):
    params = (
        ("period", 28),
        ("rsi_low", 30),
        ("rsi_high", 70),
    )

    #TRADE LOGGING FUNCTION
    def log(self, txt, dt=None):
        ''' Logging function fot this strategy'''
        if not opt_mode:
            dt = dt or self.datas[0].datetime.datetime(0)
            print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        self.startcash = self.broker.getvalue()
        self.rsi = bt.indicators.RSI_SMA(self.data.close, period=self.params.period, safediv=True)


    #TRADE LOGGING FUNCTION
    def notify_trade(self, trade):
        if not trade.isclosed and not opt_mode:
            return

        self.log('TRADE INFO, PRICE  %.2f, GROSS %.2f, NET %.2f' %
                 (trade.price, trade.pnl, trade.pnlcomm))

    def next(self):
        if not self.position:
            if self.rsi < self.params.rsi_low:
                self.buy(size=10)
        else:
            if self.rsi > self.params.rsi_high:
                self.sell(size=10)
        if opt_mode and DEBUG:
            print('period: {}, rsi low: {}, rsi high {}'.format(self.params.period,self.params.rsi_low,self.params.rsi_high))

# if opt_mode == False:
#     def printTradeAnalysis(analyzer):
#         '''
#         Function to print the Technical Analysis results in a nice format.
#         '''
#         #Get the results we are interested in
#         total_open = analyzer.total.open
#         total_closed = analyzer.total.closed
#         total_won = analyzer.won.total
#         total_lost = analyzer.lost.total
#         win_streak = analyzer.streak.won.longest
#         lose_streak = analyzer.streak.lost.longest
#         pnl_net = round(analyzer.pnl.net.total,2)
#         strike_rate = round((total_won / total_closed) * 100,2)
#         #Designate the rows
#         h1 = ['Total Open', 'Total Closed', 'Total Won', 'Total Lost']
#         h2 = ['Strike Rate','Win Streak', 'Losing Streak', 'PnL Net']
#         r1 = [total_open, total_closed,total_won,total_lost]
#         r2 = [strike_rate, win_streak, lose_streak, pnl_net]
#         #Check which set of headers is the longest.
#         if len(h1) > len(h2):
#             header_length = len(h1)
#         else:
#             header_length = len(h2)
#         #Print the rows
#         print_list = [h1,r1,h2,r2]
#         row_format ="{:<15}" * (header_length + 1)
#         print("Trade Analysis Results:")
#         for row in print_list:
#             print(row_format.format('',*row))
#
#     def printSQN(analyzer):
#         sqn = round(analyzer.sqn,2)
#         print('SQN: {}'.format(sqn))

# INPUT CONDITIONS TO FEED INTO CEREBRO IS ADDED HERE
if __name__ == '__main__':
    sys.stdout = Logger("strat_evaluator.log")


    #periods = pd.DataFrame(columns=['FROM','TO'],index=[1,2,3,4,5,6,7,8,9,10,11,12])
    periods = pd.DataFrame(columns=['FROM','TO'],index=[1])
    periods.loc[1] = ('1990-1-01','2017-12-31')
    #periods.loc[2] = ('2017-02-01','2017-03-01')
    #periods.loc[3] = ('2017-03-01','2017-04-01')
    #periods.loc[4] = ('2017-04-01','2017-05-01')
    #periods.loc[5] = ('2017-05-01','2017-06-01')
    #periods.loc[6] = ('2017-06-01','2017-07-01')
    #periods.loc[7] = ('2017-07-01','2017-08-01')
    #periods.loc[8] = ('2017-08-01','2017-09-01')
    #periods.loc[9] = ('2017-09-01','2017-10-01')
    #periods.loc[10] = ('2017-10-01','2017-11-01')
    #periods.loc[11] = ('2017-11-01','2017-12-01')
    #periods.loc[12] = ('2017-12-01','2017-12-31')

    for index, row in periods.iterrows():


        # Variable for our starting cash
        startcash = 10000
        # Create an instance of cerebro
        cerebro = bt.Cerebro(optreturn=False)

        # Timing the whole operation
        time_at_start = time.time()

        if opt_mode:
            # ADD STRATEGY OPTIMISATION
            #cerebro.optstrategy(firstStrategy, period=range(11, 20), rsi_low=range(10, 50), rsi_high=range(51, 85))
            cerebro.optstrategy(firstStrategy, period=range(13, 14), rsi_low=range(20, 21), rsi_high=range(40, 41))
            cerebro.addanalyzer(bt.analyzers.SharpeRatio)
        else:
            #ADD STRATEGY
            cerebro.addstrategy(firstStrategy)

        #format dates for datafeed object
        fy,fm,fd = periods['FROM'][index].split('-')
        ty,tm,td = periods['TO'][index].split('-')


#READ DATA FROM CSV FILE

        filename = 'tickerData/F_BO.txt'
        modpath = os.path.dirname(os.path.abspath(sys.argv[0]))
        datapath = os.path.join(modpath,str(filename))
        data = dataFeed(dataname=datapath, timeframe=bt.TimeFrame.Days,
                        fromdate=datetime.datetime(int(fy),int(fm),int(fd)),
                        todate=datetime.datetime(int(ty),int(tm),int(td)),)

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

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

        if not opt_mode:
            # Add the analyzers we are interested in
            cerebro.addanalyzer(bt.analyzers.TradeAnalyzer, _name="ta")
            cerebro.addanalyzer(bt.analyzers.SQN, _name="sqn")


        #WRITER TEST
        #cerebro.addwriter(bt.WriterFile, csv=True, rounding=2)

        # RUN STRATEGY THROUGH CEREBRO USING INPUT DATA
        # Timing the operation
        time_at_end = time.time()
        time_elapsed = round(time_at_end - time_at_start,2)
        print('Time elapsed: {} seconds'.format(time_elapsed))
        print ('Running Cerebro')
        if not opt_mode: opt_runs = cerebro.run(tradehistory=False)
        else: opt_runs = cerebro.run(tradehistory=False, runonce = False, Exactbars=True)

        firstStrat = opt_runs[0]

        if opt_mode:
            # CREATE A LIST VARIABLE THAT CONTAINS RESULTS
            final_results_list = []
            for run in opt_runs:
                for strategy in run:
                    value = round(strategy.broker.get_value(), 2)
                    PnL = round(value - startcash, 2)
                    period = strategy.params.period
                    rsi_low = strategy.params.rsi_low
                    rsi_high = strategy.params.rsi_high
                    final_results_list.append([period, rsi_low, rsi_high, PnL])

            # Sort Results List
            by_period = sorted(final_results_list, key=lambda x: x[0])
            by_PnL = sorted(final_results_list, key=lambda x: x[3], reverse=True)

            # PRINT RESULTS IN OPTIMISATION AND FILTER TOP 3
            result_number = 0
            print('Results: Ordered by Profit:')
            for result in by_PnL:
                if result_number < 3:
                    print('Asset: {} Start: {}, End: {}, Period: {}, rsi_low: {}, rsi_high: {}, PnL: {}'.format(filename, periods['FROM'][index], periods['TO'][index], result[0], result[1], result[2], result[3]))
                    result_number = result_number + 1

        # Timing the operation
        time_at_end = time.time()
        time_elapsed = round(time_at_end - time_at_start,2)


        print('Time elapsed: {} seconds'.format(time_elapsed))
        if opt_mode == False:
            # print the analyzers
            # printTradeAnalysis(firstStrat.analyzers.ta.get_analysis())
            # printSQN(firstStrat.analyzers.sqn.get_analysis())

            #Get final portfolio Value
            portvalue = cerebro.broker.getvalue()

            #Print out the final result
            print('Final Portfolio Value: ${}'.format(portvalue))
            cerebro.plot(style='candlestick')

        #cerebro.plot(style='candlestick')

for completeness here is the data that I am using

DATE, OPEN, HIGH, LOW, CLOSE, VOL, OI, P, R, RINFO
19900102,11520.0000,11520.0000,11316.0000,11322.0000,19779,38563,0,0,0.0000
19900103,11322.0000,11460.0000,11298.0000,11442.0000,16270,39377,0,0,0.0000
19900104,11472.0000,11520.0000,11340.0000,11346.0000,12743,39220,0,0,0.0000
19900105,11298.0000,11466.0000,11286.0000,11418.0000,11808,39932,0,0,0.0000
19900108,11448.0000,11808.0000,11442.0000,11784.0000,20844,40091,0,0,0.0000
19900109,11730.0000,11820.0000,11682.0000,11778.0000,19457,39502,0,0,0.0000
19900110,11760.0000,11778.0000,11598.0000,11724.0000,16266,39703,0,0,0.0000
19900111,11712.0000,11790.0000,11706.0000,11754.0000,13699,39704,0,0,0.0000
19900112,11826.0000,11844.0000,11634.0000,11640.0000,12677,38444,0,0,0.0000
19900115,11598.0000,11688.0000,11580.0000,11652.0000,6067,38307,0,0,0.0000
19900116,11610.0000,11640.0000,11490.0000,11496.0000,13691,37511,0,0,0.0000
19900117,11484.0000,11616.0000,11484.0000,11502.0000,12378,38223,0,0,0.0000
19900118,11508.0000,11580.0000,11496.0000,11538.0000,8570,37584,0,0,0.0000
19900119,11562.0000,11568.0000,11400.0000,11406.0000,14732,36865,0,0,0.0000
19900122,11400.0000,11448.0000,11316.0000,11358.0000,15163,36837,0,0,0.0000
19900123,11382.0000,11508.0000,11376.0000,11466.0000,13141,36918,0,0,0.0000
19900124,11472.0000,11514.0000,11436.0000,11448.0000,10550,36551,0,0,0.0000
19900125,11472.0000,11478.0000,11340.0000,11340.0000,14579,35655,0,0,0.0000
19900126,11340.0000,11430.0000,11328.0000,11418.0000,7547,34389,0,0,0.0000
19900129,11430.0000,11544.0000,11370.0000,11538.0000,11285,34198,0,0,0.0000
19900130,11544.0000,11574.0000,11442.0000,11460.0000,12167,33318,0,0,0.0000
19900131,11460.0000,11544.0000,11430.0000,11502.0000,10708,32328,0,0,0.0000
19900201,11520.0000,11700.0000,11502.0000,11532.0000,17957,32443,0,0,0.0000
19900202,11544.0000,11580.0000,11508.0000,11568.0000,14151,31419,0,0,0.0000
19900205,11568.0000,11634.0000,11460.0000,11478.0000,14241,30695,0,0,0.0000

Hi,

I am trying to read in futures data in the following fomat:

DATE, OPEN, HIGH, LOW, CLOSE, VOL, OI, P, R, RINFO
19900531,104687.5000,104850.0000,104387.5000,104525.0000,18592,32108,0,0,0.0000
19900601,104750.0000,105512.5000,104612.5000,104762.5000,26697,27205,0,0,0.0000
19900604,104250.0000,104562.5000,103937.5000,104437.5000,15315,25228,0,0,0.0000
19900605,104575.0000,105250.0000,104425.0000,105137.5000,18054,25452,0,0,0.0000
19900606,105187.5000,105437.5000,105112.5000,105300.0000,10104,24872,0,0,0.0000
19900607,105250.0000,105450.0000,105137.5000,105425.0000,9931,24237,199009,199009,0.0000
19900608,103562.5000,103562.5000,103125.0000,103437.5000,12791,9134,0,0,-1600.0000

I intend to trim the data so that it does not include the last three columns.

However when I run using this data, due to it not being continuous days cerebro does not process trades correctly - the graphs is plotted but the trades do not execute.

I suspect there is a setting somewhere which will allow this data to be handled.

I have read: https://www.backtrader.com/blog/posts/2016-08-31-rolling-over-futures/rolling-futures-over.html

but can't figure out how to handle this data - any suggestions pls?

@backtrader Thank you for your answer and I am sure a library will be coming together soon. I will certainly contribute as I get further into my backtrader journey :)