Note:
Unless it is really an issue, please post feedback/questions and other things to https://community.backtrader.com
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='YHOO', 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.
Live Trading and backtesting platform written in Python.
- Live Data Feed and Trading with
- Interactive Brokers (needs
IbPyand benefits greatly from an installedpytz)- Visual Chart (needs a fork of
comtypesuntil a pull request is integrated in the release and benefits frompytz)- Oanda (needs
oandapy) (REST API Only - v20 does not support streaming)- 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
pyfoliointegration- Flexible definition of commission schemes
- Integrated broker simulation with Market, Close, Limit, Stop and StopLimit 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 (102)
- Python
2.7- Python
3.2/3.3/3.4/3.5- It also works with pypy and pypy3 (no plotting -
matplotlibis 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[matplotlib]If
matplotlibis 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:
IbPydoesn't seem to be in PyPi. Do either:pip install git+https://github.com/blampe/IbPy.gitor (if
gitis 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
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
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:
btslightly pre-datesbacktraderand has a completely different approach but it is funny bt was also chosen as the abbreviation forbacktraderduring imports and that some of the methods have the same naming (obvious naming anyhow):run,plot...