pulp

A python Linear Programming API

https://github.com/coin-or/pulp

Science Score: 36.0%

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3 of 99 committers (3.0%) from academic institutions
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Low similarity (15.0%) to scientific vocabulary

Keywords

constraints mip pulp python solver

Keywords from Contributors

mathematical-programming mesh distributed closember profiles sequences standardization genomics interactive embedded

Last synced: 6 months ago · JSON representation

Repository

A python Linear Programming API

Basic Info

Host: GitHub
Owner: coin-or
License: other
Language: Python
Default Branch: master
Homepage: http://coin-or.github.io/pulp/
Size: 95.4 MB

Statistics

Stars: 2,314
Watchers: 69
Forks: 414
Open Issues: 89
Releases: 13

Topics

constraints mip pulp python solver

Created almost 11 years ago · Last pushed 6 months ago

Metadata Files

Readme Changelog Contributing Funding License Authors

README.rst

pulp
**************************

.. image:: https://travis-ci.org/coin-or/pulp.svg?branch=master
    :target: https://travis-ci.org/coin-or/pulp
.. image:: https://img.shields.io/pypi/v/pulp
    :target: https://pypi.org/project/PuLP/
    :alt: PyPI
.. image:: https://img.shields.io/pypi/dm/pulp
    :target: https://pypi.org/project/PuLP/
    :alt: 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 ``LpVariable`` to create new variables. To create a variable x with 0  ≤  x  ≤  3::

     from pulp import *
     x = LpVariable("x", 0, 3)

To create a binary variable, y, with values either 0 or 1::

     y = LpVariable("y", cat="Binary")

Use ``LpProblem`` to create new problems. Create a problem called "myProblem" like so::

     prob = LpProblem("myProblem", LpMinimize)

Combine variables in order to create expressions and constraints, and then 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

* ``LpConstraintVar`` -- A special type of constraint for constructing column of the model in column-wise modelling

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


On Linux and MacOS systems, you must run the tests to make the default solver executable::

     sudo pulptest




Building the documentation
--------------------------

The PuLP documentation is built with `Sphinx `_.  We recommended using a
`virtual environment `_ to build the documentation locally.

To build, run the following in a terminal window, in the PuLP root directory

::

    python3 -m pip install --upgrade pip
    pip install --group=dev .
    cd doc
    make html

A folder named html will be created inside the ``build/`` directory.
The home page for the documentation is ``doc/build/html/index.html`` which can be opened 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!**

* Comments and suggestions: https://github.com/coin-or/pulp/discussions
* Bug reports: https://github.com/coin-or/pulp/issues
* Patches: https://github.com/coin-or/pulp/pulls

Copyright and License 
=======================
PuLP is distributed under an MIT license. 

     Copyright J.S. Roy, 2003-2005
     Copyright Stuart A. Mitchell
     See the LICENSE file for copyright information.

.. _Python: http://www.python.org/

.. _GLPK: http://www.gnu.org/software/glpk/glpk.html
.. _CBC: https://github.com/coin-or/Cbc
.. _CPLEX: http://www.cplex.com/
.. _GUROBI: http://www.gurobi.com/
.. _MOSEK: https://www.mosek.com/
.. _XPRESS: https://www.fico.com/es/products/fico-xpress-solver
.. _CHOCO: https://choco-solver.org/
.. _MIPCL: http://mipcl-cpp.appspot.com/
.. _SCIP: https://www.scipopt.org/
.. _HiGHS: https://highs.dev
.. _FSCIP: https://ug.zib.de

Owner

Name: COIN-OR Foundation
Login: coin-or
Kind: organization
Email: info@coin-or.org
Location: United States of America

Website: https://www.coin-or.org
Twitter: coin_or
Repositories: 80
Profile: https://github.com/coin-or

Computational Infrastructure for Operations Research.

GitHub Events

Total

Create event: 17
Release event: 1
Issues event: 47
Watch event: 220
Delete event: 6
Issue comment event: 217
Push event: 89
Pull request review comment event: 67
Pull request event: 92
Pull request review event: 63
Fork event: 29

Last Year

Create event: 17
Release event: 1
Issues event: 47
Watch event: 220
Delete event: 6
Issue comment event: 217
Push event: 89
Pull request review comment event: 67
Pull request event: 92
Pull request review event: 63
Fork event: 29

Committers

Last synced: 9 months ago

All Time

Total Commits: 411
Total Committers: 99
Avg Commits per committer: 4.152
Development Distribution Score (DDS): 0.706

Past Year

Commits: 50
Committers: 18
Avg Commits per committer: 2.778
Development Distribution Score (DDS): 0.7

Top Committers

Name	Email	Commits
Franco Peschiera	p**p@g**m	121
Stuart Mitchell	s**u@s**m	86
Stuart Mitchell	hg@s****m	32
Matthew Bradbury	M****y	11
Christophe-Marie Duquesne	c**e@g**m	10
Frederick Robinson	f**n@f**m	8
Ryan J. O'Neil	r**l@g**m	7
Ewout ter Hoeven	E**n@s**l	6
Antony Phillips	a**s@g**m	5
tgmath	t**t@g**m	5
Guillermo González-Santander de la Cruz	g**z@b**s	4
Will Usher	w**r@k**e	4
Rachel	3****o	4
Daniel Junglas	5****s	4
Utkarsh Detha	u**a@g**m	3
dependabot[bot]	4****]	3
sudermn	n**n@b**m	3
Christian Wassermann	c**n@w**e	2
Michael Behrisch	o**s@b**e	2
fjc	f**f@g**m	2
William Pettersson	w**m@e**e	2
Thiago Jobson	t****n	2
Maciej	m**j@w**m	2
Oleh Prypin	o**h@p**n	2
Sam Mathew	s****t	2
David GG	3****y	2
Fang Yu Hsueh	3****A	2
Toby Davies	t**s@b**m	2
pchtsp	f**a@g**m	2
smit023	s**3@g**r	2
and 69 more...

Committer Domains (Top 20 + Academic)

stuartmitchell.com: 2 frrad.com: 1 student.tudelft.nl: 1 baobabsoluciones.es: 1 kth.se: 1 basf.com: 1 behrisch.de: 1 ewpettersson.se: 1 wave.com: 1 pryp.in: 1 biarri.com: 1 lehigh.edu: 1 gams.com: 1 boissier.de: 1 thebrown.net: 1 getmail.no: 1 163.com: 1 duck.com: 1 iki.fi: 1 nonner.de: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 150
Total pull requests: 205
Average time to close issues: 8 months
Average time to close pull requests: 2 months
Total issue authors: 120
Total pull request authors: 63
Average comments per issue: 2.57
Average comments per pull request: 2.02
Merged pull requests: 138
Bot issues: 0
Bot pull requests: 5

Past Year

Issues: 27
Pull requests: 93
Average time to close issues: about 1 month
Average time to close pull requests: 9 days
Issue authors: 23
Pull request authors: 21
Average comments per issue: 3.44
Average comments per pull request: 1.39
Merged pull requests: 60
Bot issues: 0
Bot pull requests: 3

View more stats

Top Authors

Issue Authors

davidggphy (5)
simon-b (4)
tle4336 (3)
WPettersson (3)
yurivict (3)
torressa (2)
s-u-m-a-n-t-h (2)
christiansegercrantz (2)
musicinmybrain (2)
pchtsp (2)
dbokal (2)
zxt5 (2)
GoogleCodeExporter (2)
vladimirvalenta (2)
kaijing-zhang (2)

Pull Request Authors

pchtsp (39)
MBradbury (29)
frrad (17)
G-Carneiro (7)
aphi (7)
EwoutH (6)
Iroy30 (5)
dependabot[bot] (5)
WPettersson (4)
ggsdc (4)
pepeleduin (4)
djunglas (4)
jebob (3)
rutger-van-beek-cqm (3)
davidggphy (3)

Top Labels

Issue Labels

Type-Defect (2) Priority-Medium (2) auto-migrated (2) good first issue (2) help wanted (1) enhancement (1) docs (1)

Pull Request Labels

dependencies (5) github_actions (3)

Packages

Total packages: 4
Total downloads:
- pypi 2,854,167 last-month
Total docker downloads: 128

Total dependent packages: 124
(may contain duplicates)
Total dependent repositories: 689
(may contain duplicates)
Total versions: 59
Total maintainers: 4

pypi.org: pulp

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.

Documentation: https://pulp.readthedocs.io/
License: MIT
Latest release: 3.2.2
published 7 months ago

Versions: 49
Dependent Packages: 115
Dependent Repositories: 639
Downloads: 2,854,167 Last month
Docker Downloads: 128

Rankings

Dependent packages count: 0.2%

Downloads: 0.4%

Dependent repos count: 0.5%

Average: 1.5%

Stargazers count: 1.7%

Forks count: 2.7%

Docker downloads count: 3.8%

Maintainers (3)

pchtsp js StuartMitchell

Last synced: 6 months ago

conda-forge.org: pulp

Homepage: https://github.com/coin-or/pulp
License: MIT
Latest release: 2.7.0
published over 3 years ago

Versions: 8
Dependent Packages: 8
Dependent Repositories: 50

Rankings

Dependent repos count: 5.1%

Dependent packages count: 7.1%

Average: 7.8%

Forks count: 9.2%

Stargazers count: 9.9%

Last synced: 7 months ago

spack.io: py-pulp

PuLP is an LP modeler written in Python. PuLP can generate MPS or LP files and call GLPK, COIN-OR CLP/CBC, CPLEX, GUROBI, MOSEK, XPRESS, CHOCO, MIPCL, SCIP to solve linear problems.

Homepage: https://github.com/coin-or/pulp
License: []
Latest release: 2.6.0
published almost 4 years ago

Versions: 1
Dependent Packages: 1
Dependent Repositories: 0

Rankings

Dependent repos count: 0.0%

Forks count: 5.2%

Stargazers count: 5.8%

Average: 9.8%

Dependent packages count: 28.1%

Maintainers (1)

marcusboden

Last synced: 6 months ago

anaconda.org: pulp

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.

Homepage: https://github.com/coin-or/pulp
License: MIT
Latest release: 3.2.2
published 6 months ago

Versions: 1
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Dependent packages count: 42.3%

Average: 44.4%

Dependent repos count: 46.5%

Last synced: 6 months ago

Dependencies

.github/workflows/build_docs.yml actions

actions/checkout v3 composite
actions/setup-python v4 composite
ad-m/github-push-action master composite

.github/workflows/publish-to-test-pypi.yml actions

actions/checkout master composite
actions/setup-python v4 composite
pypa/gh-action-pypi-publish release/v1 composite

.github/workflows/pythonpackage.yml actions

actions/checkout v3 composite
actions/setup-python v4 composite