# LP Solvers for Python
[](https://github.com/stephane-caron/lpsolvers/actions)
[](https://coveralls.io/github/stephane-caron/lpsolvers?branch=main)
[](https://stephane-caron.github.io/lpsolvers/)
[](https://pypi.org/project/lpsolvers/)
Wrapper around Linear Programming (LP) solvers in Python, with a unified interface.
## Installation
To install the library and all available LP solvers at the same time:
```console
$ pip install lpsolvers[open_source_solvers]
```
To install the library only, assuming LP solvers are installed separately: ``pip install lpsolvers``.
## Usage
The function [`solve_lp`](https://stephane-caron.github.io/lpsolvers//linear-programming.html#lpsolvers.solve_lp) is called with the ``solver`` keyword argument to select the backend solver. The linear program it solves is, in standard form:
$$
\begin{split}
\begin{array}{ll}
\mbox{minimize} &
c^T x \\
\mbox{subject to}
& G x \leq h \\
& A x = b
\end{array}
\end{split}
$$
Vector inequalities are taken coordinate by coordinate.
## Example
To solve a linear program, build the matrices that define it and call the ``solve_lp`` function:
```python
from numpy import array
from lpsolvers import solve_lp
c = array([1., 2., 3.])
G = array([[1., 2., -1.], [2., 0., 1.], [1., 2., 1.], [-1., -1., -1.]])
h = array([4., 1., 3., 2.])
x = solve_lp(c, G, h, solver="cvxopt") # select solver here
print(f"LP solution: {x=}")
```
This example outputs the solution ``[2.2, -0.8, -3.4]``.
## Solvers
The list of supported solvers currently includes:
- [cdd](https://github.com/mcmtroffaes/pycddlib)
- [CVXOPT](http://cvxopt.org/)
- [CVXPY](https://www.cvxpy.org/) (interface)
- [PDLP](https://developers.google.com/optimization/lp/pdlp_math)
- [ProxQP](https://github.com/Simple-Robotics/proxsuite#proxqp)
Raw data
{
"_id": null,
"home_page": null,
"name": "lpsolvers",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.7",
"maintainer_email": "St\u00e9phane Caron <stephane.caron@normalesup.org>",
"keywords": "linear programming,solver,numerical optimization",
"author": null,
"author_email": "St\u00e9phane Caron <stephane.caron@normalesup.org>",
"download_url": "https://files.pythonhosted.org/packages/10/3a/c518f5bc28cdbcb02c941efc3c9c798c352cfbeaee3d5622ae2b82c6d4f6/lpsolvers-2.0.0.tar.gz",
"platform": null,
"description": "# LP Solvers for Python\n\n[](https://github.com/stephane-caron/lpsolvers/actions)\n[](https://coveralls.io/github/stephane-caron/lpsolvers?branch=main)\n[](https://stephane-caron.github.io/lpsolvers/)\n[](https://pypi.org/project/lpsolvers/)\n\n\nWrapper around Linear Programming (LP) solvers in Python, with a unified interface.\n\n## Installation\n\nTo install the library and all available LP solvers at the same time:\n\n```console\n$ pip install lpsolvers[open_source_solvers]\n```\n\nTo install the library only, assuming LP solvers are installed separately: ``pip install lpsolvers``.\n\n## Usage\n\nThe function [`solve_lp`](https://stephane-caron.github.io/lpsolvers//linear-programming.html#lpsolvers.solve_lp) is called with the ``solver`` keyword argument to select the backend solver. The linear program it solves is, in standard form:\n\n$$\n\\begin{split}\n\\begin{array}{ll}\n \\mbox{minimize} &\n c^T x \\\\\n \\mbox{subject to}\n & G x \\leq h \\\\\n & A x = b\n\\end{array}\n\\end{split}\n$$\n\nVector inequalities are taken coordinate by coordinate.\n\n## Example\n\nTo solve a linear program, build the matrices that define it and call the ``solve_lp`` function:\n\n```python\nfrom numpy import array\nfrom lpsolvers import solve_lp\n\nc = array([1., 2., 3.])\nG = array([[1., 2., -1.], [2., 0., 1.], [1., 2., 1.], [-1., -1., -1.]])\nh = array([4., 1., 3., 2.])\n\nx = solve_lp(c, G, h, solver=\"cvxopt\") # select solver here\nprint(f\"LP solution: {x=}\")\n```\n\nThis example outputs the solution ``[2.2, -0.8, -3.4]``.\n\n## Solvers\n\nThe list of supported solvers currently includes:\n\n- [cdd](https://github.com/mcmtroffaes/pycddlib)\n- [CVXOPT](http://cvxopt.org/)\n- [CVXPY](https://www.cvxpy.org/) (interface)\n- [PDLP](https://developers.google.com/optimization/lp/pdlp_math)\n- [ProxQP](https://github.com/Simple-Robotics/proxsuite#proxqp)\n",
"bugtrack_url": null,
"license": null,
"summary": "Linear programming solvers in Python with a unified API.",
"version": "2.0.0",
"project_urls": {
"Changelog": "https://github.com/stephane-caron/lpsolvers/blob/main/CHANGELOG.md",
"Documentation": "https://stephane-caron.github.io/lpsolvers/",
"Source": "https://github.com/stephane-caron/lpsolvers",
"Tracker": "https://github.com/stephane-caron/lpsolvers/issues"
},
"split_keywords": [
"linear programming",
"solver",
"numerical optimization"
],
"urls": [
{
"comment_text": null,
"digests": {
"blake2b_256": "b20090bb9cfacb29d058016498ece3fde40e37eb1a84088e42ef57e77ebb2b92",
"md5": "94f59b5e8d857a4ffed718c85e6ca83d",
"sha256": "fffcecd52b7a40b782d9bd98577537d6a0ca98b5c5c37e0af8b32f96deba2406"
},
"downloads": -1,
"filename": "lpsolvers-2.0.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "94f59b5e8d857a4ffed718c85e6ca83d",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.7",
"size": 14039,
"upload_time": "2024-01-09T16:17:54",
"upload_time_iso_8601": "2024-01-09T16:17:54.785537Z",
"url": "https://files.pythonhosted.org/packages/b2/00/90bb9cfacb29d058016498ece3fde40e37eb1a84088e42ef57e77ebb2b92/lpsolvers-2.0.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "103ac518f5bc28cdbcb02c941efc3c9c798c352cfbeaee3d5622ae2b82c6d4f6",
"md5": "1779757cad03ae03903e191c9589e35d",
"sha256": "aff363e5e59c48b21a1c1da3ec6d010f2b5f6469bcbf4c8a83bb6f23da31656c"
},
"downloads": -1,
"filename": "lpsolvers-2.0.0.tar.gz",
"has_sig": false,
"md5_digest": "1779757cad03ae03903e191c9589e35d",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.7",
"size": 18139,
"upload_time": "2024-01-09T16:17:57",
"upload_time_iso_8601": "2024-01-09T16:17:57.139253Z",
"url": "https://files.pythonhosted.org/packages/10/3a/c518f5bc28cdbcb02c941efc3c9c798c352cfbeaee3d5622ae2b82c6d4f6/lpsolvers-2.0.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-01-09 16:17:57",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "stephane-caron",
"github_project": "lpsolvers",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"tox": true,
"lcname": "lpsolvers"
}
JSON
