Convex Optimization Python Packages

cvxpy

A Python-embedded modeling language for convex optimization problems.

clarabel

Clarabel.rs: Interior-point solver for convex conic optimisation problems in Rust.

cvxpy-base

A Python-embedded modeling language for convex optimization problems.

riskfolio-lib

Portfolio Optimization and Quantitative Strategic Asset Allocation in Python

skfolio

Python library for portfolio optimization built on top of scikit-learn

qoco

Quadratic Objective Conic Optimizer

opfunu

A collection of Benchmark functions for numerical optimization problems

adelie

A fast and flexible Python package for efficiently solving lasso, elastic net, group lasso, and group elastic net problems.

polyfit

Scikit learn compatible constrained and robust polynomial regression in Python

cvxportfolio

Portfolio optimization and back-testing.

qoco-cuda

Quadratic Objective Conic Optimizer

pytmpinv

Tabular Matrix Problems via Pseudoinverse Estimation

toqito

|toqito> (Theory of Quantum Information Toolkit) is a Python library for research in quantum information theory.

pylppinv

Linear Programming via Regularized Least Squares

pyunlocbox

A Python convex optimization package using proximal splitting methods

tyba-cvxpy

A domain-specific language for modeling convex optimization problems in Python.

pyclsp

Modular Two-Step Convex Optimization Estimator for Ill-Posed Problems

deepdow

Portfolio optimization with deep learning.

cvxpnpl

A Perspective-n-Points-and-Lines method.

scico

Scientific Computational Imaging COde

decopt

In compressed decentralized optimization settings, there are benefits to having multiple gossip steps between subsequent gradient iterations, even when the cost of doing so is appropriately accounted for e.g. by means of reducing the precision of compressed information.

algormeter

Tool for developing, testing and measuring optimizers algorithms

torchregister

Common 2D and 3D image registration methods such as rigid, affine, and flow field for PyTorch.

cr-sparse

Functional models and algorithms for sparse signal processing