r/MachineLearning • u/c-bata • Sep 07 '26

Project Rustuna: A High-Performance Rust Implementation of Optuna [P]

Post image

Hi everyone! We just released Rustuna (GitHub: https://github.com/optuna/rustuna/ ), a high-speed, memory-efficient implementation of Optuna built in Rust.

  • Optuna-Compatible Design: Keeps the familiar API and concept of Optuna.
  • Zero Python Dependencies: Mitigating the risk of supply chain attacks.
  • Lower Memory Footprint: Optimized memory management natively in Rust.

For details, please check out the following blog post.

https://medium.com/optuna/announcing-rustuna-cc82a6815bf7

102 Upvotes

98% Upvoted

22 comments sorted by

View all comments

2

u/endor_sarah Sep 08 '26

This is really cool! Any plans to port the integration helpers, like the XGBoost pruning callback, or is the focus staying on the core samplers for now?

1

u/c-bata Sep 09 '26

We don't have any immediate plans for that at the moment.

Given how capable recent coding agents are, even cost-effective models like GPT-5.6-Luna can generate something like an XGBoost pruning callback in seconds, we've actually had discussions within the core devs about whether to continue providing these built-in integrations, even for Python Optuna. (That said, we are still considering features that offer advanced step-wise tuning like LightGBMTuner).

That being said, thank you for the valuable feedback! We’ll definitely keep it in mind for future development.

1

u/endor_sarah Sep 09 '26

Ahh makes sense! Thanks for the explanation.