The zipline version seems also to require a bit of knowledge of numpy. Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian-- a free, community-centered, hosted platform for building and executing trading strategies.. Join our Community! #6 Zipline. Zipline is a package that ties the statistics, the data structures, and the data sources all together. Zipline is a Pythonic algorithmic trading library. Zipline currently supports Python 2.7, 3.5, and 3.6, and may be installed via either pip or conda. Quantopian is a free, community-centered, hosted platform for building and executing trading strategies. The framework then provides access to point-in-time correct features – for both – offline model training and online inference. The obscurity in backtrader is what happens with the code defined during __init__. It is an event-driven system for backtesting. Zipline is a Pythonic algorithmic trading library. Zipline reduces this task from months to days – by making the process declarative. Here's an example where we run an algorithm with zipline, then produce tear sheets for that algorithm. Python 3.5 or 3.6 (when using Zipline 1.3.0) or 3.6 (when using Zipline 1.4.1) only (this is a limitation of Zipline) Microsoft Windows An active Norgate Data subscription In this example, we start with 2017–01–02, as this is the first day for which we have pricing data. It is an event-driven system for backtesting. It is also possible to define your own trading calendar and you can find more information in zipline’s documentation here. It allows data scientists to easily define features in a simple configuration language. This is the third part of a series of articles on backtesting trading strategies in Python. Note: Installing Zipline is slightly more involved than the average Python package. Zipline algorithm analysis example in pyfolio. 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