[](https://pypi.org/project/gurobi-optimods)
[](https://pypi.org/project/gurobi-optimods)
[](https://github.com/Gurobi/gurobi-optimods/actions/workflows/test.yml?query=branch%3Amain++)
[](https://gurobi-optimization-gurobi-optimods.readthedocs-hosted.com/en/stable)
# gurobi-optimods: data-driven APIs for common optimization tasks
``gurobi-optimods`` is an open-source Python repository of implemented
optimization use cases, each with clear, informative, and pretty documentation
that explains how to use it and the mathematical model behind it.
## Features
`gurobi-optimods` allows users to:
- quickly apply optimization to solve a specific problem in their field of
interest via intuitive, data-driven APIs
- learn about the mathematical model behind their use-case through thorough
documentation
- contribute new mods to grow the library
## Installation
```console
pip install gurobi-optimods
```
## Dependencies
- [gurobipy: Python modelling interface for the Gurobi Optimizer](https://pypi.org/project/gurobipy/)
- [numpy: The fundamental package for scientific computing with Python](https://pypi.org/project/numpy/)
- [scipy: Fundamental algorithms for scientific computing in Python](https://pypi.org/project/scipy/)
- [pandas: powerful Python data analysis toolkit](https://pypi.org/project/pandas/)
- [gurobipy-pandas: Convenience wrapper for building optimization models from pandas data](https://pypi.org/project/gurobipy-pandas/)
## Documentation
Full documentation for `gurobi-optimods` is hosted on [readthedocs](https://gurobi-optimods.readthedocs.io/en/stable).
## License
`gurobi-optimods` is distributed under the terms of the [Apache License 2.0](https://spdx.org/licenses/Apache-2.0.html).
## Contact Us
For questions related to using gurobi-optimods please use the [Gurobi Community Forum](https://support.gurobi.com/hc/en-us/community/topics/10373864542609-GitHub-Projects>).
For reporting bugs, issues and feature requests, specific to `gurobi-optimods`, please [open an issue](https://github.com/Gurobi/gurobi-optimods/issues).
If you encounter issues with Gurobi or `gurobipy` please contact [Gurobi Support](https://support.gurobi.com/hc/en-us).
Raw data
{
"_id": null,
"home_page": null,
"name": "gurobi-optimods",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": null,
"keywords": "gurobipy, optimization, pandas, scipy",
"author": null,
"author_email": "Simon Bowly <bowly@gurobi.com>, Robert Luce <luce@gurobi.com>",
"download_url": "https://files.pythonhosted.org/packages/94/46/be7aa34d5a4e2358d6415f37f2cf3da371a061eaecfe255245244aad4e55/gurobi_optimods-2.2.0.tar.gz",
"platform": null,
"description": "[](https://pypi.org/project/gurobi-optimods)\n[](https://pypi.org/project/gurobi-optimods)\n[](https://github.com/Gurobi/gurobi-optimods/actions/workflows/test.yml?query=branch%3Amain++)\n[](https://gurobi-optimization-gurobi-optimods.readthedocs-hosted.com/en/stable)\n\n# gurobi-optimods: data-driven APIs for common optimization tasks\n\n``gurobi-optimods`` is an open-source Python repository of implemented\noptimization use cases, each with clear, informative, and pretty documentation\nthat explains how to use it and the mathematical model behind it.\n\n## Features\n\n`gurobi-optimods` allows users to:\n\n- quickly apply optimization to solve a specific problem in their field of\n interest via intuitive, data-driven APIs\n- learn about the mathematical model behind their use-case through thorough\n documentation\n- contribute new mods to grow the library\n\n## Installation\n\n```console\npip install gurobi-optimods\n```\n\n## Dependencies\n\n- [gurobipy: Python modelling interface for the Gurobi Optimizer](https://pypi.org/project/gurobipy/)\n- [numpy: The fundamental package for scientific computing with Python](https://pypi.org/project/numpy/)\n- [scipy: Fundamental algorithms for scientific computing in Python](https://pypi.org/project/scipy/)\n- [pandas: powerful Python data analysis toolkit](https://pypi.org/project/pandas/)\n- [gurobipy-pandas: Convenience wrapper for building optimization models from pandas data](https://pypi.org/project/gurobipy-pandas/)\n\n## Documentation\n\nFull documentation for `gurobi-optimods` is hosted on [readthedocs](https://gurobi-optimods.readthedocs.io/en/stable).\n\n## License\n\n`gurobi-optimods` is distributed under the terms of the [Apache License 2.0](https://spdx.org/licenses/Apache-2.0.html).\n\n## Contact Us\n\nFor questions related to using gurobi-optimods please use the [Gurobi Community Forum](https://support.gurobi.com/hc/en-us/community/topics/10373864542609-GitHub-Projects>).\n\nFor reporting bugs, issues and feature requests, specific to `gurobi-optimods`, please [open an issue](https://github.com/Gurobi/gurobi-optimods/issues).\n\nIf you encounter issues with Gurobi or `gurobipy` please contact [Gurobi Support](https://support.gurobi.com/hc/en-us).\n",
"bugtrack_url": null,
"license": null,
"summary": "Data-driven APIs for common optimization tasks",
"version": "2.2.0",
"project_urls": null,
"split_keywords": [
"gurobipy",
" optimization",
" pandas",
" scipy"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "3ac5c5e8c4fc1567fb7243a2485944c1a15b5bfa346760e2f2e0ba37aa88f174",
"md5": "90442b20462130e05138442ca8262a4f",
"sha256": "1002117d5806f191cd17b7c094dc873df097eaff287b8a724f85af670c71551e"
},
"downloads": -1,
"filename": "gurobi_optimods-2.2.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "90442b20462130e05138442ca8262a4f",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.8",
"size": 275434,
"upload_time": "2024-07-19T14:16:07",
"upload_time_iso_8601": "2024-07-19T14:16:07.244896Z",
"url": "https://files.pythonhosted.org/packages/3a/c5/c5e8c4fc1567fb7243a2485944c1a15b5bfa346760e2f2e0ba37aa88f174/gurobi_optimods-2.2.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "9446be7aa34d5a4e2358d6415f37f2cf3da371a061eaecfe255245244aad4e55",
"md5": "9947b72c187f6f7751c697d9f3257889",
"sha256": "6f281e44f9f2d0eda1206c5b6ae00d98131be5e4ec1842ee3765a921221b3f91"
},
"downloads": -1,
"filename": "gurobi_optimods-2.2.0.tar.gz",
"has_sig": false,
"md5_digest": "9947b72c187f6f7751c697d9f3257889",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.8",
"size": 3894749,
"upload_time": "2024-07-19T14:16:08",
"upload_time_iso_8601": "2024-07-19T14:16:08.610879Z",
"url": "https://files.pythonhosted.org/packages/94/46/be7aa34d5a4e2358d6415f37f2cf3da371a061eaecfe255245244aad4e55/gurobi_optimods-2.2.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-07-19 14:16:08",
"github": false,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"lcname": "gurobi-optimods"
}
JSON