This metric-learn repository contains Python implementations of metric learning algorithms.
Open source
24 alternativesOpytimizer
Opytimizer provides Python implementations of metaheuristic optimization algorithms for search problems.
About Opytimizer
Opytimizer is an open source Python library that implements meta-heuristic optimization algorithms for search problems. Its topics describe the algorithms as nature-inspired, or bio-inspired. The repository includes an architecture guide, an examples folder, a tests folder, and a documentation folder.
The repository states that the project is now maintained by the Recogna Laboratory, and it directs users to a newer repository for updates. Pricing is unknown.
Key features
- Python implementations of meta-heuristic optimization algorithms
- Nature-inspired (bio-inspired) optimization algorithms, per repository topics
- Examples folder with sample code in the repository
- Architecture guide describing the current API and development workflow
- Released under the Apache-2.0 license
Best for: Python developers and researchers who want to apply nature-inspired metaheuristic optimization algorithms to their own search problems.
Good for
- Open source under the Apache-2.0 license
- Includes an architecture guide, examples, and tests in the repository
Watch out for
- The repository notes that maintenance has moved to the Recogna Laboratory, with updates in a separate repository
Opytimizer at a glance
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Opytimizer FAQ
Who maintains this project now?
The repository states that the project is now maintained by the Recogna Laboratory. Users are directed to a new repository for updates.
What license does Opytimizer use?
The repository is licensed under Apache-2.0.
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