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

A comprehensive wiki can be found at here http://code.google.com/p/pulp-or/wiki/ (in progress) or the more complete version at http://130.216.209.237/engsci392/pulp/OptimisationWithPuLP

A newsgroup pulp-or-discuss@googlegroups.com is operational for any questions

http://groups.google.co.nz/group/pulp-or-discuss

Use LpVariable() to create new variables. ex:

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

to create a variable 0 <= x <= 3

Use LpProblem() to create new problems. ex:

>>> prob = LpProblem("myProblem", LpMinimize)

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

>>> prob += x + y <= 2

If you add an expression (not a constraint, e.g. prob += 4*z + w), it will become the objective.

Choose a solver and solve the problem. ex:

>>> prob.solve(GLPK())

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

>>> value(x)

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 expression to be used as a constraint or variable