I have implemented a Python library for modelling, inference and updating with Almost Desirable Gambles (ADG) models. It is both friendly and flexible.
It works with continuous, discrete and mixed variables.
Here you can find some additional info, setup instructions and 4 examples (notebooks):
The notebooks (and relative examples) are very simple, their purpose (at the moment) is only to highlight the functionalities of the library.
I welcome contributions, after all it is an open source project.
You can contribute in several ways:
1. giving me some feedback as user;
2. being an author of new notebooks where you can write down your favorite models
3. extending the library by including other functionalities, models etc.