{"id":24194306,"url":"https://github.com/optimagic-dev/optimagic","last_synced_at":"2025-10-21T19:59:09.006Z","repository":{"id":37249878,"uuid":"166381699","full_name":"optimagic-dev/optimagic","owner":"optimagic-dev","description":"optimagic is a Python package for numerical optimization. It is a unified interface to optimizers from SciPy, NlOpt and other packages.  optimagic's minimize function works just like SciPy's, so you don't have to adjust your code. You simply get more optimizers for free. 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Version](https://img.shields.io/pypi/v/optimagic)\n[![image](https://img.shields.io/pypi/pyversions/optimagic)](https://pypi.org/project/optimagic)\n[![image](https://img.shields.io/conda/vn/conda-forge/optimagic.svg)](https://anaconda.org/conda-forge/optimagic)\n[![image](https://img.shields.io/conda/pn/conda-forge/optimagic.svg)](https://anaconda.org/conda-forge/optimagic)\n[![image](https://img.shields.io/pypi/l/optimagic)](https://pypi.org/project/optimagic)\n[![image](https://readthedocs.org/projects/optimagic/badge/?version=latest)](https://optimagic.readthedocs.io/en/latest)\n[![image](https://img.shields.io/github/actions/workflow/status/optimagic-dev/optimagic/main.yml?branch=main)](https://github.com/optimagic-dev/optimagic/actions?query=branch%3Amain)\n[![image](https://codecov.io/gh/optimagic-dev/optimagic/branch/main/graph/badge.svg)](https://codecov.io/gh/optimagic-dev/optimagic)\n[![image](https://results.pre-commit.ci/badge/github/optimagic-dev/optimagic/main.svg)](https://results.pre-commit.ci/latest/github/optimagic-dev/optimagic/main)\n[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)\n[![image](https://pepy.tech/badge/optimagic/month)](https://pepy.tech/project/optimagic)\n[![image](https://img.shields.io/badge/NumFOCUS-affiliated%20project-orange.svg?style=flat\u0026colorA=E1523D\u0026colorB=007D8A)](https://numfocus.org/sponsored-projects/affiliated-projects)\n[![image](https://img.shields.io/twitter/follow/aiidateam.svg?style=social\u0026label=Follow)](https://x.com/optimagic)\n\n## Introduction\n\n*optimagic* is a Python package for numerical optimization. It is a unified interface to\noptimizers from SciPy, NlOpt and many other Python packages.\n\n*optimagic*'s `minimize` function works just like SciPy's, so you don't have to adjust\nyour code. You simply get more optimizers for free. On top you get powerful diagnostic\ntools, parallel numerical derivatives and more.\n\n*optimagic* was formerly called *estimagic*, because it also provides functionality to\nperform statistical inference on estimated parameters. *estimagic* is now a subpackage\nof *optimagic*.\n\n## Documentation\n\nThe documentation is hosted at https://optimagic.readthedocs.io\n\n## Installation\n\nThe package can be installed via pip or conda. To do so, type the following commands in\na terminal:\n\n```bash\npip install optimagic\n```\n\nor\n\n```bash\n$ conda config --add channels conda-forge\n$ conda install optimagic\n```\n\nThe first line adds conda-forge to your conda channels. This is necessary for conda to\nfind all dependencies of optimagic. The second line installs optimagic and its\ndependencies.\n\n## Installing optional dependencies\n\nOnly `scipy` is a mandatory dependency of optimagic. Other algorithms become available\nif you install more packages. We make this optional because most of the time you will\nuse at least one additional package, but only very rarely will you need all of them.\n\nFor an overview of all optimizers and the packages you need to install to enable them\nsee {ref}`list_of_algorithms`.\n\nTo enable all algorithms at once, do the following:\n\n`conda install nlopt`\n\n`pip install Py-BOBYQA`\n\n`pip install DFO-LS`\n\n`conda install petsc4py` (Not available on Windows)\n\n`conda install cyipopt`\n\n`conda install pygmo`\n\n`pip install fides\u003e=0.7.4 (Make sure you have at least 0.7.1)`\n\n## Citation\n\nIf you use optimagic for your research, please do not forget to cite it.\n\n```\n@Unpublished{Gabler2024,\n  Title  = {optimagic: A library for nonlinear optimization},\n  Author = {Janos Gabler},\n  Year   = {2022},\n  Url    = {https://github.com/optimagic-dev/optimagic}\n}\n```\n\n## Acknowledgements\n\nWe thank all institutions that have funded or supported optimagic (formerly estimagic)\n\n\u003cimg src=\"docs/source/_static/images/aai-institute-logo.svg\" width=\"185\"\u003e\n\u003cimg src=\"docs/source/_static/images/numfocus_logo.png\" width=\"200\"\u003e\n\u003cimg src=\"docs/source/_static/images/tra_logo.png\" width=\"240\"\u003e\n\n\u003cimg src=\"docs/source/_static/images/hoover_logo.png\" width=\"192\"\u003e\n\u003cimg src=\"docs/source/_static/images/transferlab-logo.svg\" width=\"400\"\u003e\n","funding_links":[],"categories":["Python","Simulation, Forecasting and Macro Modeling"],"sub_categories":["DSGE and Structural Models"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Foptimagic-dev%2Foptimagic","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Foptimagic-dev%2Foptimagic","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Foptimagic-dev%2Foptimagic/lists"}