#convex #optimization #sdp #qp #socp


Clarabel Conic Interior Point Solver for Rust / Python

6 releases (breaking)

0.5.0 Apr 26, 2023
0.4.1 Mar 8, 2023
0.4.0 Feb 26, 2023
0.3.0 Sep 13, 2022
0.1.0 Jul 30, 2022

#400 in Math

Download history 2/week @ 2023-02-04 12/week @ 2023-02-11 7/week @ 2023-02-18 23/week @ 2023-02-25 25/week @ 2023-03-04 20/week @ 2023-03-11 32/week @ 2023-03-18 5/week @ 2023-03-25 11/week @ 2023-04-01 30/week @ 2023-04-08 69/week @ 2023-04-15 60/week @ 2023-04-22 35/week @ 2023-04-29 54/week @ 2023-05-06 39/week @ 2023-05-13 75/week @ 2023-05-20

212 downloads per month


11K SLoC

Interior Point Conic Optimization for Rust and Python


Clarabel.rs is a Rust implementation of an interior point numerical solver for convex optimization problems using a novel homogeneous embedding. Clarabel.rs solves the following problem:

$$ \begin{array}{r} \text{minimize} & \frac{1}{2}x^T P x + q^T x\\[2ex] \text{subject to} & Ax + s = b \\[1ex] & s \in \mathcal{K} \end{array} $$

with decision variables $x \in \mathbb{R}^n$, $s \in \mathbb{R}^m$ and data matrices $P=P^\top \succeq 0$, $q \in \mathbb{R}^n$, $A \in \mathbb{R}^{m \times n}$, and $b \in \mathbb{R}^m$. The convex set $\mathcal{K}$ is a composition of convex cones.

For more information see the Clarabel Documentation (stable | dev).

Clarabel is also available in a Julia implementation. See here.


  • Versatile: Clarabel.rs solves linear programs (LPs), quadratic programs (QPs), second-order cone programs (SOCPs) and semidefinite programs (SDPs). It also solves problems with exponential and power cone constraints.
  • Quadratic objectives: Unlike interior point solvers based on the standard homogeneous self-dual embedding (HSDE), Clarabel.rs handles quadratic objectives without requiring any epigraphical reformulation of the objective. It can therefore be significantly faster than other HSDE-based solvers for problems with quadratic objective functions.
  • Infeasibility detection: Infeasible problems are detected using a homogeneous embedding technique.
  • Open Source: Our code is available on GitHub and distributed under the Apache 2.0 License


Clarabel can be imported to Cargo based Rust projects by adding

clarabel = "0"  

to the project's Cargo.toml file. To install from source, see the Rust Installation Documentation.

To use the Python interface to the solver:

pip install clarabel

To install the Python interface from source, see the Python Installation Documentation.

License 🔍

This project is licensed under the Apache License 2.0 - see the LICENSE.md file for details.


~315K SLoC