Standardized system for parameter management across Scientific Python libraries

[EwoutH]

Over at Mesa we’re working on a system for managing model/agent default values and ranges, and I believe this could be beneficial beyond Mesa. We’re exploring how to create a standardized way to define parameter spaces, including default values, ranges, and distributions, to be used by any internal and potentially external components.

The idea is to develop a ParameterSpec structure that can be used for continuous, discrete, ordered, and categorical data, with flexibility for specifying distributions, sampling strategies, and default values. Then each software component (samplers, visualisation, batch runners) can extract the pieces of information it needs. By defining everything in one place, it makes it easier to integrate different components and much less error prone.

Since we also did something similar in the EMAworkbench (see parameters), we where thinking such a spec might be beneficial for more simulation and other scientific libraries. It might have potential for a SPEC.

We’ve started discussions here, and we’d love to hear your thoughts and see if there’s potential for a broader collaboration. If there’s much interest, we can start a centralized discussion with the Scientific Python community.

• A system for managing Model/Agent default values and ranges projectmesa/mesa#2268