Z G.
Could be easier to use
I speak from the standpoint of a data scientist who uses Python, if you are a software engineer I'm sure your experience will be smoother: Pros: - wide range of assets and indicators available (although many are premium). - out-of-the-box backtesting capabilities - many powerful built-in functions such as different position sizing, fee assumptions, execution assumptions, risk management, etc... Cons: - not beginner-friendly: unnecessarily complex API, it forces you to use OOP; runtime errors are common and often hard to debug. - poor documentation, can never find what I'm looking for. And on the occasion you find it on their forums, the code may already be outdated and won't work anymore My suggestions would be to provide a few code templates with different use cases, this would make it a lot easier to start, improve the documentation and also rework on the platform's interface, it's very annoying to find past projects for example. It definitely has a great potential.




