Introduction

Gurobi can be accessed through our own API in many programming languages, including gurobipy for Python. Although we recommend using the official APIs, many of our users come from a situation where they already have implemented a model in an open-source modeling framework and wish to solve that model with Gurobi without rewriting their code. This article describes how to do that for the most popular modeling frameworks

Comparison with official Gurobi APIs

There are important advantages to using the Gurobi APIs:

They are officially supported by our R&D and Experts team
They expose all Gurobi functionality, while much of that is hidden by modeling frameworks
They avoid any overhead (runtime and memory) caused by handing over the model from framework to Gurobi
They always work with the latest version of Gurobi

Using an existing model in an open-source modeling framework

For several modeling frameworks we have dedicated pages that show exactly how to use Gurobi through the framework, the caveats to be aware of and how to accomplish common tasks:

For several other modeling framework, below we provide a high-level overview of the steps required to get started using Gurobi in each framework.

Google OR-Tools

Do the full installation of Gurobi Optimizer; OR-Tools will not work if you only have gurobipy available
Make sure you are installing the most recent release of OR-Tools; this is currently only available via pip install (PyPI), and not via conda
Create or download your Gurobi license file
At runtime, OR-Tools will search for the Gurobi shared library in the default install path of the Gurobi installers or by using the GUROBI_HOME environment variable
Import the required package using from ortools.linear_solver import pywraplp
Create your model solver using solver = pywraplp.Solver.CreateSolver("GUROBI")
Once the model is defined properly, call status = solver.Solve() to solve it with Gurobi

PythonMIP

Install the full Gurobi software; PythonMIP will not work if you only have gurobipy available
During installation, make sure to define the GUROBI_HOME environment variable
Create or download your Gurobi license file
PythonMIP will use Gurobi automatically

CVXPY

Install the gurobipy package; you don't need the full Gurobi installation
Create or download your Gurobi license file
Assuming you have import cvxpy as cp and your model is defined in variable prob, solve your model using prob.solve(solver=cp.GUROBI())

Other resources

Related to