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PuLP is an LP modeler written in python. PuLP can generate MPS or LP files and call GLPK, COIN CLP/CBC, CPLEX, and GUROBI to solve linear problems.

Project description

https://travis-ci.org/coin-or/pulp.svg?branch=master PyPI PyPI - Downloads

PuLP is an linear and mixed integer programming modeler written in Python. With PuLP, it is simple to create MILP optimisation problems and solve them with the latest open-source (or proprietary) solvers. PuLP can generate MPS or LP files and call solvers such as GLPK, COIN-OR CLP/CBC, CPLEX, GUROBI, MOSEK, XPRESS, CHOCO, MIPCL, HiGHS, SCIP/FSCIP.

The documentation for PuLP can be found here.

PuLP is part of the COIN-OR project.

Installation

PuLP requires Python 3.9 or newer.

The easiest way to install PuLP is with pip. If pip is available on your system, type:

python -m pip install pulp

Otherwise follow the download instructions on the PyPi page.

Installing solvers

PuLP can use a variety of solvers. The default solver is the COIN-OR CBC solver, which is included with PuLP. If you want to use other solvers, PuLP offers a quick way to install most solvers via their pypi package (some require a commercial license for running or for running large models):

python -m pip install pulp[gurobi]
python -m pip install pulp[cplex]
python -m pip install pulp[xpress]
python -m pip install pulp[scip]
python -m pip install pulp[highs]
python -m pip install pulp[copt]
python -m pip install pulp[mosek]
python -m pip install pulp[cylp]
If you want to install all open source solvers (scip, highs, cylp), you can use the shortcut::

python -m pip install pulp[open_py]

For more information on how to install solvers, see the guide on configuring solvers.

Quickstart

Use LpProblem to create a problem, then add variables with add_variable. Create a problem called “myProblem” and a variable x with 0 ≤ x ≤ 3:

from pulp import *
prob = LpProblem("myProblem", LpMinimize)
x = prob.add_variable("x", 0, 3)

To create a binary variable y (values 0 or 1):

y = prob.add_variable("y", cat="Binary")

Combine variables to create expressions and constraints and add them to the problem:

prob += x + y <= 2

An expression is a constraint without a right-hand side (RHS) sense (one of =, <= or >=). If you add an expression to a problem, it will become the objective:

prob += -4*x + y

To solve the problem with the default included solver:

status = prob.solve()

If you want to try another solver to solve the problem:

status = prob.solve(GLPK(msg = 0))

Display the status of the solution:

LpStatus[status]
> 'Optimal'

You can get the value of the variables using value. ex:

value(x)
> 2.0

Essential Classes

  • LpProblem – Container class for a Linear or Integer programming problem

  • LpVariable – Variables that are added into constraints in the LP problem

  • LpConstraint – Constraints of the general form

    a1x1 + a2x2 + … + anxn (<=, =, >=) b

Useful Functions

  • value() – Finds the value of a variable or expression

  • lpSum() – Given a list of the form [a1*x1, a2*x2, …, an*xn] will construct a linear expression to be used as a constraint or variable

  • lpDot() – Given two lists of the form [a1, a2, …, an] and [x1, x2, …, xn] will construct a linear expression to be used as a constraint or variable

More Examples

Several tutorial are given in documentation and pure code examples are available in examples/ directory .

The examples use the default solver (CBC). To use other solvers they must be available (installed and accessible). For more information on how to do that, see the guide on configuring solvers.

For Developers

If you want to install the latest version from GitHub you can run:

python -m pip install -U git+https://github.com/coin-or/pulp

Building from source

This version of PuLP includes a Rust extension (pulp._rustcore) that provides the core model, variables, constraints, and expressions. The build uses maturin and requires a Rust toolchain in addition to Python.

Requirements

  • Python 3.9 or newer

  • Rust (latest stable). Install from https://rustup.rs/

  • uv (recommended for install and dev). Install with: curl -LsSf https://astral.sh/uv/install.sh | sh (Linux/macOS) or powershell -c "irm https://astral.sh/uv/install.ps1 | iex" (Windows)

  • OS: Windows, macOS (x86_64, arm64), or Linux (x86_64, arm64). The Rust extension is built for the host platform.

Build steps

From the PuLP root directory, create a virtual environment and install the package in editable mode with dev dependencies:

uv venv
uv pip install --group dev -e .

Or with plain pip (maturin will be used automatically by the build backend):

python -m venv .venv
source .venv/bin/activate   # Windows: .venv\Scripts\activate
python -m pip install --upgrade pip
pip install --group dev -e .

Running tests

uv run python -m unittest discover -s pulp/tests -v

On Linux and macOS you may need to make the default CBC solver executable:

sudo pulptest

Building the documentation

The PuLP documentation is built with Sphinx. Use a virtual environment and the dev install above, then:

cd doc
make html

A folder named html will be created inside doc/build/. Open doc/build/html/index.html in a browser.

Contributing to PuLP

Instructions for making your first contribution to PuLP are given here.

Comments, bug reports, patches and suggestions are very welcome!

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