Metadata-Version: 2.1
Name: PuLP
Version: 2.1
Summary: 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.
Home-page: https://github.com/coin-or/pulp
Author: J.S. Roy and S.A. Mitchell
Author-email: pulp@stuartmitchell.com
License: UNKNOWN
Keywords: Optimization,Linear Programming,Operations Research
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering :: Mathematics
Description-Content-Type: text/x-rst
Requires-Dist: pyparsing (>=2.0.1)

pulp
**************************
.. image:: https://travis-ci.org/coin-or/pulp.svg?branch=master
    :target: https://travis-ci.org/coin-or/pulp

PuLP is an LP modeler written in Python. PuLP can generate MPS or LP files
and call GLPK[1], COIN CLP/CBC[2], CPLEX[3], and GUROBI[4] to solve linear
problems.

Installation
================

The easiest way to install pulp is via `PyPi <https://pypi.python.org/pypi/PuLP>`_

If pip is available on your system::

     pip install pulp

Otherwise follow the download instructions on the PyPi page.
On Linux and OSX systems the tests must be run to make the default
solver executable.

::

     sudo pulptest

Examples
================

See the examples directory for examples.

PuLP requires Python >= 2.7.

The examples use the default solver (CBC), to use other solvers they must be available.

Documentation
================

Documentation is found on https://coin-or.github.io/pulp/.


Use LpVariable() to create new variables. To create a variable 0 <= x <= 3::

     x = LpVariable("x", 0, 3)

To create a variable 0 <= y <= 1::

     y = LpVariable("y", 0, 1)

Use LpProblem() to create new problems. Create "myProblem"::

     prob = LpProblem("myProblem", LpMinimize)

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

     prob += x + y <= 2

If you add an expression (not a constraint), it will
become the objective::

     prob += -4*x + y

To solve with the default included solver::

     status = prob.solve()

To use another sovler 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

Exported Classes:

* LpProblem -- Container class for a Linear programming problem
* LpVariable -- Variables that are added to constraints in the LP
* LpConstraint -- A constraint of the general form

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

*  LpConstraintVar -- Used to construct a column of the model in column-wise modelling

Exported Functions:

* value() -- Finds the value of a variable or expression
* lpSum() -- given a list of the form [a1*x1, a2x2, ..., anxn] 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 epression to be used as a constraint or variable

Comments, bug reports, patches and suggestions are welcome.
pulp-or-discuss@googlegroups.com

     Copyright J.S. Roy (js@jeannot.org), 2003-2005
     Copyright Stuart A. Mitchell (stu@stuartmitchell.com)
     See the LICENSE file for copyright information.

References:

[1] http://www.gnu.org/software/glpk/glpk.html
[2] http://www.coin-or.org/
[3] http://www.cplex.com/
[4] http://www.gurobi.com/


