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Python Backtesting library for trading strategies
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paperswithbacktest/pwb-backtrader
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Yahoo API Note:
[2018-11-16] After some testing it would seem that data downloads can beagain relied upon over the web interface (or APIv7)
Tickets
The ticket system is (was, actually) more often than not abused to ask foradvice about samples.
Forfeedback/questions/... use theCommunity <https://community.backtrader.com>_
Here a snippet of a Simple Moving Average CrossOver. It can be done in severaldifferent ways. Use the docs (and examples) Luke!::
from datetime import datetimeimport backtrader as bt
class SmaCross(bt.SignalStrategy):definit(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 samplesassigsmacross/sigsmacross2.py. Along it issigsmacross.py which can beparametrized 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 aninstalledpytz) - Visual Chart (needs a fork of
comtypesuntil a pull request isintegrated in the release and benefits frompytz) - Oanda (needs
oandapy) (REST API Only - v20 did not supportstreaming when implemented)
- Interactive Brokers (needs
Data feeds from csv/files, online sources or frompandas andblaze
Filters for datas, like breaking a daily bar into chunks to simulateintraday 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 pythonta-lib / check the docs)
Easy development of custom indicators
Analyzers (for example: TimeReturn, Sharpe Ratio, SQN) and
pyfoliointegration (deprecated)Flexible definition of commission schemes
Integrated broker simulation withMarket,Close,Limit,Stop,StopLimit,StopTrail,StopTrailLimitandOCO orders, bracket order,slippage, volume filling strategies and continuous cash adjustmet forfuture-like instruments
Sizers for automated staking
Cheat-on-Close and Cheat-on-Open modes
Schedulers
Trading Calendars
Plotting (requires matplotlib)
The blog:
Blog <http://www.backtrader.com/blog>_
Read the full documentation at:
Documentation <http://www.backtrader.com/docu>_
List of built-in Indicators (122)
Indicators Reference <http://www.backtrader.com/docu/indautoref.html>_
Python >=
3.2It also works with
pypyandpypy3(no plotting -matplotlibisnot supported underpypy)
backtrader is self-contained with no external dependencies (except if youwant to plot)
Frompypi:
pip install backtraderpip install backtrader[plotting]If
matplotlibis not installed and you wish to do some plotting
.. note:: The minimum matplotlib version is1.4.1
An example forIB Data Feeds/Trading:
IbPydoesn't seem to be in PyPi. Do either::pip install git+https://github.com/blampe/IbPy.git
or (if
gitis not available in your system)::pip installhttps://github.com/blampe/IbPy/archive/master.zip
For other functionalities like:Visual Chart,Oanda,TA-Lib, checkthe dependencies in the documentation.
From source:
- Place thebacktrader directory found in the sources inside your project
X.Y.Z.I
- X: Major version number. Should stay stable unless something big is changedlike 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, smallchanges, small bug fixes
- I: Number of Indicators already built into the platform
To build the package, run:
python -m pip install --upgrade buildrm -r distpython -m build
To upload the package to PyPI, run:
twine upload dist/*About
Python Backtesting library for trading strategies
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