2.6k stars · MIT · v1.2.1 (2026-09-07)
GroupStats: hand it a DataFrame of many equity curves and get one table of performance statistics for all of them.
▶Repo detailsthe review · specs · pros & cons · install
What it is
A small finance toolkit. Its useful trick is called GroupStats. You hand it a table where each column is one strategy's results, and it gives you back one table of statistics for all of them at once.
Why it matters
Optuna (Ed. 7 #12) produces hundreds of trials. quantstats (Ed. 4 #11) makes a beautiful report for exactly one of them. The step in between is missing: look at all of them side by side and pick the three worth a proper check. This is the tool for the moment when you have too many candidates. That is the normal, permanent state of a strategy search, and eleven editions of ScalpingMate advice never addressed it.
- MIT licence, so unlike backtesting.py it can sit behind a paid feature.
- One call compares any number of strategies, which changes what you are willing to test.
- Very few extra dependencies on top of pandas. Nothing new to maintain.
- It overlaps with quantstats. The difference is many versus one. If you only ever look at a single strategy, you do not need this.
- The statistics only describe. It will happily rank four hundred overfitted results for you. arch (Ed. 6 #11) is still the tool that says whether the winner was luck.
- Small team, a few releases a year.
source venv/bin/activate pip install ffn
