old_contents: import numpy as np
  from optlang import Model, Variable, Constraint, Objective
  
  # All the (symbolic) variables are declared, with a name and optionally a lower
  # and/or upper bound.
  x = np.array([Variable('x{}'.format(i), lb=0) for i in range(1, 4)])
  
  bounds = [100, 600, 300]
  
  A = np.array([[ 1, 1, 1],
                [10, 4, 5],
                [ 2, 2, 6]])
  
  w = np.array([ 10, 6, 4])
  
  obj = Objective(w.dot(x), direction='max')
  
  c = np.array([Constraint(row, ub=bound) for row, bound in zip(A.dot(x), bounds)])
  
  model = Model(name='Numpy model')
  model.objective = obj
  model.add(c)
  
  status = model.optimize()
  
  print("status:", model.status)
  print("objective value:", model.objective.value)
  print("----------")
  for var_name, var in model.variables.iteritems():
      print(var_name, "=", var.primal)
  
new_contents: import numpy as np
  from optlang import Model, Variable, Constraint, Objective
  
  # All the (symbolic) variables are declared, with a name and optionally a lower
  # and/or upper bound.
  x = np.array([Variable('x{}'.format(i), lb=0) for i in range(1, 4)])
  
  bounds = [100, 600, 300]
  
  A = np.array([[1, 1, 1],
                [10, 4, 5],
                [2, 2, 6]])
  
  w = np.array([10, 6, 4])
  
  obj = Objective(w.dot(x), direction='max')
  
  c = np.array([Constraint(row, ub=bound) for row, bound in zip(A.dot(x), bounds)])
  
  model = Model(name='Numpy model')
  model.objective = obj
  model.add(c)
  
  status = model.optimize()
  
  print("status:", model.status)
  print("objective value:", model.objective.value)
  print("----------")
  for var_name, var in model.variables.iteritems():
      print(var_name, "=", var.primal)
  
subject: Update simple_numpy.py