dima/backtrader

Python Backtesting library for trading strategies

backtrader

Yahoo API Note:

[2018-11-16] After some testing it would seem that data downloads can be again relied upon over the web interface (or API v7)

Tickets

If it's NOT an issue (i.e.: bug), don't post it as an issue. It will be automatically closed.

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 IbPy2 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 (supports 2 backends: matplotlib and bokeh)

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

Compatibility is tested during development with 2.7 and 3.5

The other versions are tested automatically with Travis.

Installation

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

From pypi:

• pip install backtrader

• pip install backtrader[plotting]

  If matplotlib and bokeh are 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:

• pip install ibpy2

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