Here is a list of the most popular (popularity measured by the number of GitHub stars) backtesting libraries related to Python ecosystem.
- vectorbt pro
backtrader is in the first position because it is a mature, battle-field-tested framework. It is very likely that you will find a solution to your problem related to backtrader on the internet or on a dedicated community page.
NOTE: The last release (220.127.116.11 ) was on 30 May 2019. There are PRs (mainly with fixes) accepted. The software reached a high level of maturity and new features seem to be not added.
According to the authors: [Jesse](https://github.com/jesse-ai/jesse](https://github.com/jesse-ai/jesse) is more accurate than other solutions, and way more simple. In fact, it is so simple that in case you already know Python, you can get started today, in a matter of minutes, instead of weeks and months.
With vectorbt you will find your trading edge, using the fastest engine for backtesting, algorithmic trading, and research. Optimized for speed - using matrix computations (NumPy) + acceleration of NumPy with Numba. Since it is fast when compared to other libraries, therefore it will be useful for:
- optimization (fast evaluation of the given set of parameters)
- large-scale sweeping of parameter space and visualizing as 2D heat map or 3D volume plot.
There is also a paid version, which is refactored with multiple enhancements over the free version. The free version is maintained but no new features are added by the author:
Yes, I still do smaller bug fixes and merge pull requests. But I won't develop any new features, everything is coming to vbt pro. (from: Issue #431)
A paid, proprietary, version of the vectorbt. See the features of vectorbt pro here.
backtesting.py - Backtest trading strategies with Python.
finmarketpy is a Python-based library that enables you to analyze market data and also backtest trading strategies using a simple-to-use API, which has prebuilt templates for you to define backtest. Included in the library
Bringing backtesting to the mainstream - fastquant allows you to easily backtest investment strategies with as few as 3 lines of python code. Its goal is to promote data-driven investments by making quantitative analysis in finance accessible to everyone.
zipline - despite its large popularity, it was put at the end of the list because it is not maintained anymore. However, the community took-over the project and created a fork that is being maintained and developed.
zipline-reloaded is a community fork of zipline.
See also: Lesser Known Backtesting Libraries
Lesser Known Backtesting Libraries Backtesting