backtrader2 : An on going and open project

Important Update

Backtrader is a flexible and powerful backtesting engine written in python. The original project found wide appeal due to its versatility. Over time however, the original code base became inaccessible to bug fixes and enhancements.

Backtrader2 is a forked copy of backtrader by the community of users that seeks to make backtrader an ongoing project.

Initially backtrader2 will fix bugs. Just submit an issue and pull requests.

New code ideas are welcome but will not be addressed at this time. But please do enter them as an issue and tag it with 'enhancement' so that we can track your idea down the road.

Backtrader's back and we look forward to its future!

For feedback/questions/... use the Community

Here a snippet of a Simple Moving Average CrossOver. It can be done in several different ways. Use the docs (and examples) Luke!

from datetime import datetime
import backtrader as bt

class SmaCross(bt.SignalStrategy):
    def __init__(self):
        sma1, sma2 = bt.ind.SMA(period=10), bt.ind.SMA(period=30)
        crossover = bt.ind.CrossOver(sma1, sma2)
        self.signal_add(bt.SIGNAL_LONG, crossover)

cerebro = bt.Cerebro()
cerebro.addstrategy(SmaCross)

data0 = bt.feeds.YahooFinanceData(dataname='MSFT', fromdate=datetime(2011, 1, 1),
                                  todate=datetime(2012, 12, 31))
cerebro.adddata(data0)

cerebro.run()
cerebro.plot()

Including a full featured chart. Give it a try! This is included in the samples as sigsmacross/sigsmacross2.py. Along it is sigsmacross.py which can be parametrized from the command line.

Features:

Live Trading and backtesting platform written in Python.

• Live Data Feed and Trading with
  • Interactive Brokers (needs IbPy and benefits greatly from an installed pytz)
  • Visual Chart (needs a fork of comtypes until a pull request is integrated in the release and benefits from pytz)
  • Oanda (needs oandapy) (REST API Only - v20 did not support streaming when implemented)
• Data feeds from csv/files, online sources or from pandas and blaze
• Filters for datas, like breaking a daily bar into chunks to simulate intraday or working with Renko bricks
• Multiple data feeds and multiple strategies supported
• Multiple timeframes at once
• Integrated Resampling and Replaying
• Step by Step backtesting or at once (except in the evaluation of the Strategy)
• Integrated battery of indicators
• TA-Lib indicator support (needs python ta-lib / check the docs)
• Easy development of custom indicators
• Analyzers (for example: TimeReturn, Sharpe Ratio, SQN) and pyfolio integration (deprecated)
• Flexible definition of commission schemes
• Integrated broker simulation with Market, Close, Limit, Stop, StopLimit, StopTrail, StopTrailLimit*and *OCO orders, bracket order, slippage, volume filling strategies and continuous cash adjustmet for future-like instruments
• Sizers for automated staking
• Cheat-on-Close and Cheat-on-Open modes
• Schedulers
• Trading Calendars
• Plotting (requires matplotlib)

Documentation

The blog:

• Blog

Read the full documentation at:

• Documentation

List of built-in Indicators (122)

• Indicators Reference

Python 2/3 Support

• Python >= 3.2
• It also works with pypy and pypy3 (no plotting - matplotlib is not supported under pypy)

Installation

backtrader is self-contained with no external dependencies (except if you want to plot)

Install the latest version from the backtrader2 repository:

• pip install git+https://github.com/backtrader2/backtrader

Or install the original version of backtrader from pypi:

• pip install backtrader

• pip install backtrader[plotting]

  If matplotlib is not installed and you wish to do some plotting

Note

The minimum matplotlib version is 1.4.1

An example for IB Data Feeds/Trading:

• IbPy doesn't seem to be in PyPi. Do either:

  pip install git+https://github.com/blampe/IbPy.git
  

  or (if git is not available in your system):

  pip install https://github.com/blampe/IbPy/archive/master.zip
  

For other functionalities like: Visual Chart, Oanda, TA-Lib, check the dependencies in the documentation.

From source:

• Place the backtrader directory found in the sources inside your project

Version numbering

X.Y.Z.I

• X: Major version number. Should stay stable unless something big is changed like an overhaul to use numpy
• Y: Minor version number. To be changed upon adding a complete new feature or (god forbids) an incompatible API change.
• Z: Revision version number. To be changed for documentation updates, small changes, small bug fixes
• I: Number of Indicators already built into the platform