zipline VS backtesting.py

https://github.com/quantopian/zipline (event-driven)

Zipline by Quantopian: An Open-Source tool for algorithmic trading. It is a platform for developing and testing quantitative trading strategies using Python.

For personal use only. I'm currently looking at QuantConnect's LEAN and Quantopian's Zipline (which hasn't seen any updates since 2020, presumably because Quantopian was dissolved).

(1) I remember there were decent libraries for this setting a while back. Maybe take a look at Quantopian/Zipline.

zipline – Zipline is a Pythonic algorithmic trading library. It is an event-driven system that supports both backtesting and live trading.

I found two opensource tools 1. .https://github.com/quantopian/zipline Quantopian 2. https://analyzingalpha.com/backtrader-backtesting-trading-strategies backtrader

Some of the notable libraries in Python are backtesting.py, bt and zipline. Personally I like bt the most, as its tree model makes the most intuitive sense.

We chose backtesting.py for a backtesting framework. There are several to choose from but that one seems like the most well-supported and actively worked on at the moment.

The process might vary a bit based on what you want to trade, but I've had some success with back-testing by using the IBKR API to download historical data for the stocks I want, then plugging in that data to some other back-testing framework, like https://kernc.github.io/backtesting.py/

https://kernc.github.io/backtesting.py/ offers nice way to zoom backtesting. It has some bugs, but good for visualization.

Are there any free trading platform options to import and backtest millisecond historical tick data? Do you use something like https://github.com/kernc/backtesting.py and then translate algorithms into mql4/5 or pinescript?

But even if you don't know that, you can Google the library to find its documentation and installation instructions - in this case, here where it does indeed tell you to run pip install backtesting.

Sure. My strategy is actually very simple using common indicators like MACD and RSI. Most of the code is actually based on https://github.com/kernc/backtesting.py and I use it to check whether I should buy or sell on a particular day. Hope this helps!

I'm leaning towards using the backtesting.py library, but from the example on their main page, it looks like you need to program your strategy using their library?