backtrader

by mementum

mementum / backtrader

Python Backtesting library for trading strategies

4.8K Stars 1.5K Forks Last release: Not found GNU General Public License v3.0 2.4K Commits 139 Releases

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backtrader

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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

The ticket system is (was, actually) more often than not abused to ask for advice about samples.

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.signaladd(bt.SIGNALLONG, 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, StopTrailLimitand 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)

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

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