Step one:

brew install glpk pip install pulp |

Step two:

from pulp import * prob = LpProblem("test1", LpMinimize) # Variables x = LpVariable("x", 0, 4, cat="Integer") y = LpVariable("y", -1, 1, cat="Integer") z = LpVariable("z", 0, cat="Integer") # Objective prob += x + 4*y + 9*z # Constraints prob += x+y <= 5 prob += x+z >= 10 prob += -y+z == 7 GLPK().solve(prob) # Solution for v in prob.variables(): print v.name, "=", v.varValue print "objective=", value(prob.objective) |

In the documentation there are further examples, e.g. one to minimise the cost of producing cat food.