cvxopt/cvxopt
FreeCVXOPT -- Python Software for Convex Optimization
FreeFree tier
About cvxopt/cvxopt
CVXOPT is a free and open-source Python library for convex optimization. It provides a Python interface to interior-point methods for solving linear programming (LP), quadratic programming (QP), second-order cone programming (SOCP), and semidefinite programming (SDP) problems. The library is implemented in Python with a C core for performance, and is accompanied by extensive documentation, a community forum, and related interfaces for Julia and MATLAB.
Key Features
Python interface to interior-point solvers for LP, QP, SOCP, and SDP
C core for efficient computation
Open-source (GPL license) and freely available
Includes documentation, examples, and Google Groups community forum
Related interfaces available for Julia and MATLAB
Pros & Cons
Pros
- Free and open-source with a permissive GPL license
- Well-documented with examples and community support
- Integrates easily with Python's scientific ecosystem (NumPy, SciPy)
- Mature project with stable releases and active maintenance
Best For
Solving linear and quadratic programming problems in PythonConvex optimization in research, engineering, and data scienceImplementing semidefinite programming for control and signal processing
FAQ
What is CVXOPT?
CVXOPT is a free Python library for convex optimization, providing solvers for linear programming, quadratic programming, second-order cone programming, and semidefinite programming.
Is CVXOPT free?
Yes, CVXOPT is open-source software released under the GPL license and is available for free.
Where can I find documentation for CVXOPT?
Documentation is available on the official CVXOPT website at cvxopt.org and through the GitHub repository.