Getting Started

Welcome to the Getting Started section! This guide will help you install and configure PyORlib in your optimization project. For more detailed information about the library, you can refer to the PyORlib examples or API Reference.

Requirements¶

By default, PyORlib's core functionalities and optimization utilities only require Python 3.10+. However, additional optional dependencies may be needed to work with optimization models and solver integrations based on your use case. For more information on supported integrations, see the Optional Dependencies section below.

Installation¶

PyORlib is available as a Python package and can be easily installed using pip. To install the core functionalities, open your terminal and execute the following command:

pip install pyorlib

Optional Dependencies¶

While PyORlib's core functionality relies primarily on Python's standard library, the package is designed from the ground up to seamlessly integrate with popular solvers through a modular and unified API.

Solver License Notice

PyORlib integrates with solvers through their Python APIs but does not bundle the solvers themselves. Access to solvers is governed by individual licenses and requirements set by each provider. Please check the solver documentation for details on installation, configuration and licensing.

Supported Solver Integrations¶

CPLEX ─ PyORlib integrates with the powerful CPLEX solver through the CplexEngine interface. This integration allows you to optimize models using CPLEX's advanced algorithms and features. To install PyORlib with CPLEX support, please use the following command:
```
pip install pyorlib[cplex]
```

Gurobi ─ PyORlib integrates with Gurobi, a powerful solver renowned for its high-performance optimization capabilities, through the GurobiEngine interface. This integration enables efficient optimization of models using Gurobi's advanced algorithms and features. To install PyORlib with Gurobi support, use the following command:
```
pip install pyorlib[gurobi]
```

OR-Tools ─ PyORlib integrates with OR-Tools through the ORToolsEngine interface. This enables efficient optimization of linear and integer programming models using OR-Tools' advanced algorithms. To install PyORlib with OR-Tools support, use:
```
pip install pyorlib[ortools]
```

PuLP ─ PyORlib integrates with PuLP through the PuLPEngine interface. This enables optimization of models using PuLP's Python modeling language and interface to various solvers. To install PyORlib with PuLP support, use:
```
pip install pyorlib[pulp]
```

You can install all of them with:

pip install pyorlib[all]