Python

Numerical Libraries & Data

Structures

- [numpy](http://www.numpy.org) - NumPy is the fundamental

package for scientific computing with Python.

- [scipy](https://www.scipy.org) - SciPy (pronounced “Sigh

Pie”) is a Python-based ecosystem of open-source software for

mathematics, science, and engineering.

- [pandas](http://pandas.pydata.org) - pandas is an open

source, BSD-licensed library providing high-performance,

easy-to-use data structures and data analysis tools for the Python

programming language.

- [quantdsl](https://github.com/johnbywater/quantdsl) - Domain

specific language for quantitative analytics in finance and

trading

-

[statistics](https://docs.python.org/3/library/statistics.html) -

Builtin Python library for all basic statistical calculations

### Financial Instruments

- [PyQL](https://github.com/enthought/pyql) - QuantLib's

Python port

- [pyfin](https://github.com/opendoor-labs/pyfin) - Basic

options pricing in Python

- [vollib](https://github.com/vollib/vollib) - vollib is a

python library for calculating option prices, implied volatility

and greeks.

- [QuantPy](https://github.com/jsmidt/QuantPy) - A framework

for quantitative finance In python

-

[Finance-Python](https://github.com/wegamekinglc/Finance-Python) -

Python tools for Finance

- [ffn](https://github.com/pmorissette/ffn) - A financial

function library for Python

- [pynance](http://pynance.net) - PyNance is open-source

software for retrieving, analysing and visualizing data from stock

and derivatives markets.

- [tia](https://github.com/bpsmith/tia) - Toolkit for

integration and analysis

### Trading & Backtesting

- [TA-Lib](http://ta-lib.org) - perform technical analysis of

financial market data

- [trade](https://github.com/rochars/trade) - trade is a

Python framework for the development of financial

applications.

- [zipline](http://www.zipline.io) - Pythonic algorithmic

trading library

- [QuantSoftware

Toolkit](http://wiki.quantsoftware.org/index.php?title=QuantSoftware_ToolKit)

- Python-based open source software framework designed to support

portfolio construction and management.

-

[quantitative](https://github.com/jeffrey-liang/quantitative) -

Quantitative finance, and backtesting library

- [analyzer](https://github.com/llazzaro/analyzer) - Python

framework for real-time financial and backtesting trading

strategies

- [bt](https://github.com/pmorissette/bt) - Flexible

Backtesting for Python

- [backtrader](https://github.com/mementum/backtrader) -

Python Backtesting library for trading strategies

- [pythalesians](https://github.com/thalesians/pythalesians) -

Python library to backtest trading strategies, plot charts,

seamlessly download market data, analyse market patterns etc.

- [pybacktest](https://github.com/ematvey/pybacktest) -

Vectorized backtesting framework in Python / pandas, designed to

make your backtesting easier.

- [pyalgotrade](https://github.com/gbeced/pyalgotrade) -

Python Algorithmic Trading Library

-

[tradingWithPython](https://pypi.python.org/pypi/tradingWithPython)

- A collection of functions and classes for Quantitative

trading

- [pandas_talib](https://github.com/femtotrader/pandas_talib)

- A Python Pandas implementation of technical analysis

indicators

- [algobroker](https://github.com/joequant/algobroker) - This

is an execution engine for algo trading

- [pysentosa](https://pypi.python.org/pypi/pysentosa) - Python

API for sentosa trading system

- [finmarketpy](https://github.com/cuemacro/finmarketpy) -

Python library for backtesting trading strategies and analyzing

financial markets