ilpy 0.5.2

Unified API for ILP solvers.

ilpy

Unified python wrappers for popular ILP solvers

ilpy is a Python library that provides unified wrappers for popular Integer Linear Programming (ILP) solvers such as Gurobi and SCIP. It offers a consistent API that abstracts away the differences between solver implementations.

With ilpy, you can:

• Define linear and quadratic optimization problems using a simple, intuitive syntax
• Express constraints using natural Python expressions
• Switch between different solver backends (currently Gurobi and SCIP)
• Monitor solver progress through callback events
• Support for continuous, binary, and integer variables

Installation

Install from pip with:

pip install ilpy

Note that ilpy requires a solver backend: either pyscipopt (for SCIP) or gurobipy (for Gurobi).

... with SCIP

Currently, ilpy ships by default with support for the SCIP optimization suite, via pyscipopt, but you may also declare it explicitly:

pip install ilpy[scip]

... with Gurobi

If you want to use Gurobi (which requires a license), you can bring in the gurobipy dependency with:

pip install ilpy[gurobi]

On conda

If you prefer to use conda:

...with SCIP

conda install -c conda-forge ilpy pyscipopt

...with Gurobi

conda install -c conda-forge -c gurobi ilpy gurobi

Local development

pip install -e .[dev]
pytest