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Opti\n\n[![Tests](https://github.com/basf/mopti/actions/workflows/main.yml/badge.svg)](https://github.com/basf/mopti/actions)\n[![Docs](https://github.com/basf/mopti/actions/workflows/docs.yml/badge.svg)](https://basf.github.io/mopti/)\n[![PyPI](https://img.shields.io/pypi/v/mopti.svg?color=%2334D058)](https://pypi.org/project/mopti)\n\n**Opti is deprecated. Consider using [BoFire](https://github.com/experimental-design/bofire) instead.**\n\nOpti is a Python package for specifying problems in a number of closely related fields, including experimental design, multiobjective optimization, decision making and Bayesian optimization.\n\n**Docs**: https://basf.github.io/mopti/ \u003cbr/\u003e\n**Code**: https://github.com/basf/mopti\n\n### Why opti? \nOpti ...\n* supports mixed continuous, discrete and categorical parameter spaces for system inputs and outputs,\n* separates objectives (minimize, maximize, close-to-target) from the outputs on which they operate,\n* supports different specific and generic constraints as well as black-box output constraints,\n* provides sampling methods for constrained mixed variable spaces,\n* json-serializes problems for use in RESTful APIs and json/bson DBs, and\n* provides a range of benchmark problems for (multi-objective) optimization and Bayesian optimization.\n\n## BoFire\n\nWe are developing a successor of opti called [BoFire](https://github.com/experimental-design/bofire) and recommend using that. 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