Practical overview
When it fits
Use the repository when you need a code-level starting point for an Optuna optimization workflow and can adapt the example to your objective and dependencies.
Who it is for
- Python developers adding hyperparameter search to machine-learning experiments.
- Optuna users looking for examples of framework integrations, pruning or distributed optimization.
Documented uses
- Define an objective function and optimize parameters across trial evaluations.
- Adapt Optuna examples to machine-learning frameworks such as scikit-learn, PyTorch, Keras, LightGBM or XGBoost.
- Explore examples for pruning, multi-objective searches, visualization and distributed workflows.
Requirements & limits
The repository is public and lists an MIT license.
- The simplest example depends on Python and Optuna and demonstrates a quadratic objective rather than a complete model-training workflow.
- The example catalog names integrations across many machine-learning libraries; selecting one determines the additional framework context needed.
- Distributed examples are provided for Dask, Kubernetes and Ray, while the README does not present them as a single hosted service.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Adapt the basic Optuna study pattern
Use the README’s minimal example as a starting point for an objective-function optimization.
Before you start
- Python
- Optuna
Steps
Define an objective function that receives a trial.
Use the trial to suggest a parameter value and return an objective result.
Create an Optuna study and pass the objective to study.optimize with trial-count or timeout limits.
Read the best parameters and objective value from the study.
Expected outcome
A study searches the defined parameter range and reports its best parameter values and objective result.
Guide limitations
- The README’s minimal example optimizes a quadratic function; adapting it to a model requires providing the relevant evaluation logic.
- Framework-specific examples may require dependencies beyond Python and Optuna.
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 5 November 2026
- Original website title
- optuna/optuna-examples · Official homepage title · retained in its source language