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BackTesting Engine

Project Description


Yahoo API Note:

With release data samples and YahooFinance data feeds have been updated to the latest available information. But being the format not documented, there could still be changes and unexpected corners.

For feedback/questions/issues 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()

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

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


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)
  • 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
  • Flexible definition of commission schemes
  • Integrated broker simulation with Market, Close, Limit, Stop, StopLimit, StopTrail, StopTrailLimit*and *OCO, orders, slippage and continuous cash adjustmet for future-like instruments
  • Plotting (requires matplotlib)


The blog:

Read the full documentation at:

List of built-in Indicators (116)

Python 2/3 Support

  • Python 2.7
  • Python 3.2 / 3.3/ 3.4 / 3.5 / 3.6
  • It also works with pypy and pypy3 (no plotting - matplotlib is not supported under pypy)

Compatibility is tested during development with 2.7 and 3.5

The other versions are tested automatically with Travis.


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


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+

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

    pip install

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: 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


If after seeing the docs and some samples (see the blog also) you feel this is not your cup of tea, you can always have a look at similar Python platforms:

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