HPOlib2

Overview

HPOlib2 is a Python library that provides a collection of benchmark problems for hyperparameter optimization. It standardizes the evaluation of optimization algorithms by offering a common interface to test functions and real-world tasks.

Best for

Best for
Researchers and developers building or evaluating hyperparameter optimization algorithms

Use cases

• Benchmarking new hyperparameter optimization algorithms against standard problems
• Comparing the performance of different optimization methods on reproducible tasks
• Developing and testing custom optimization strategies with a consistent evaluation framework

Notes

HPOlib2 is a Python library that provides a collection of benchmark problems for hyperparameter optimization. It standardizes the evaluation of optimization algorithms by offering a common interface to test functions and real-world tasks.

168 stars on GitHub. Last updated 2025-05-21. Licensed Apache-2.0.

Use cases

• Benchmarking new hyperparameter optimization algorithms against standard problems
• Comparing the performance of different optimization methods on reproducible tasks
• Developing and testing custom optimization strategies with a consistent evaluation framework

Pros

• Provides a standardized set of benchmarks for reproducible research
• Lightweight and easy to integrate into existing Python optimization workflows
• Community-maintained with a focus on automated machine learning

Cons

• Limited to hyperparameter optimization benchmarks, not a general-purpose optimization library
• Small community with only 168 GitHub stars, so less support and fewer contributions
• May lack documentation or examples for advanced use cases

Indexed from awesome-llmops and enriched against its public facts.