Our verdict
We have not reviewed Goptuna yet
No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.
From the listing
About Goptuna
Goptuna is a hyperparameter optimization framework written in Go, inspired by Optuna. It provides a lightweight, native library for automated search of optimal parameters in machine learning models or any other optimization problem.
Best for
Go developers who need a fast, embedded hyperparameter optimization library.
Use cases
- Tuning hyperparameters for Go-based machine learning pipelines
- Running automated parameter searches for simulation or configuration optimization
- Integrating Bayesian optimization into Go applications for decision-making
Notes
277 stars on GitHub. Last updated 2025-08-12. Licensed MIT.
Pros
- Native Go implementation with no external Python dependencies
- Lightweight and easy to embed in existing Go codebases
- Supports common optimization algorithms (e.g., TPE, CMA-ES)
Cons
- Smaller community and fewer prebuilt samplers compared to Optuna
- Limited documentation and examples relative to more mature frameworks
- Not designed for distributed or large-scale parallel optimization out of the box
Key facts
What we have checked
- GitHub stars
- 280
Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.
Stars and usage
How Goptuna is growing
277 to 280
Sources
Where this comes from
- github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438Registry
A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.
Changelog
What changed
No changes recorded yet. Releases, price changes and deprecations appear here, with their dates, once we track them for this record.
Pairs with
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