Install#

CORNETO provides flexible installation options depending on your needs. It integrates with various mathematical optimization solvers, which differ in their licensing, capabilities, and performance. Below are several installation options tailored to different use cases.

🔧 Quick Installation#

To get started quickly with open-source solvers, run:

pip install git+https://github.com/saezlab/corneto.git@dev scipy pyscipopt highspy cvxpy

This installs:

  • CORNETO (from the development branch)

  • PySCIPOpt: a Python interface for SCIP (a fast open-source solver)

  • highspy: Python bindings for the HIGHs solver

  • CVXPY: a modeling language for convex optimization problems

These libraries provide solid performance for most users and don’t require a commercial license.

🧩 Installation Options#

Basic Installation (CORNETO only)#

If you only want the core CORNETO package without any solver backend (useful for development or adding solvers manually later):

pip install git+https://github.com/saezlab/corneto.git@dev

You’ll need to install and configure a solver separately to make CORNETO fully functional.

⚙️ Installation with Commercial Solvers#

If you have access to Gurobi (a powerful commercial solver, free for academic use), you can install CORNETO along with Gurobi and its supported modeling tools:

pip install git+https://github.com/saezlab/corneto.git@dev cvxpy gurobipy

Note: Make sure you have a valid Gurobi license set up on your system. You can get a free academic license here.

🆓 Installation with Open-Source Solvers#

Prefer open-source? This installs CORNETO with:

  • SCIP (via pyscipopt)

  • HIGHs (via highspy)

  • CVXPY

pip install git+https://github.com/saezlab/corneto.git@dev scipy pyscipopt highspy cvxpy

These tools are effective and don’t require any licensing setup.

🧪 Alternative Backend: PICOS#

CORNETO also supports picos, another modeling layer for optimization. You can install CORNETO with picos and several solvers it supports:

pip install git+https://github.com/saezlab/corneto.git@dev scipy picos swiglpk qics

This setup uses:

  • PICOS: a high-level modeling tool

  • swiglpk: Python bindings for GLPK, a lightweight solver

  • qics: another solver supported by PICOS

✅ Verifying Installation#

To check that CORNETO is installed and ready:

import corneto

corneto.info()

This should print out CORNETO version info and configuration details.

🛠 Troubleshooting#

If you run into installation problems:

  1. ✅ Make sure you’re using Python 3.10 or higher

  2. 🧱 Check that you have at least cvxpy installed as a backend (this is the recommended one)

  3. 🔑 For Gurobi users, verify that your license is properly installed

In case of using Gurobi, you can check if the license and installation are correct by running:

from corneto.utils import check_gurobi
check_gurobi()

This will perform a series of checks to ensure that Gurobi is correctly installed and configured. You should see:

Gurobipy successfully imported.
Gurobi environment started successfully.
Starting optimization of the test model...
Test optimization was successful.
Gurobi environment disposed.
Gurobi is correctly installed and working.

If you’re still stuck, please open an issue on our GitHub Issues page—we’re happy to help!