Additional open-source Python libraries for algorithmic trading and data collection include (see links on GitHub):

• QuantConnect is a competitor to Quantopian
• WorldQuant offers online competition and recruits community contributors to a crowd-sourced hedge fund
• Alpha Trading Labs offers high-frequency focused testing infrastructure with a business model similar to Quantopian
• Python Algorithmic Trading Library (PyAlgoTrade) focuses on backtesting and offers support for paper-trading and live-trading. It allows you to evaluate an idea for a trading strategy with historical data and aims to do so with minimal effort.
• pybacktest is a vectorized backtesting framework that uses pandas and aims to be compact, simple and fast (the project is currently on hold)
• ultrafinance is an older project that combines real-time financial data collection, analyzing and backtesting of trading strategies
• Trading with Python offers courses and a collection of functions and classes for Quantitative trading
• Interactive Brokers offers a Python API for live trading on their platform