Converting Julia jump to Python pulp : I stumbled upon a piece of software that I'd like to convert from Julia to Python (don't have much experience with either).  I've spent a good amount of time on this section here and can't seem to get it working no matter what I do.  

    @defVar(m, used_team[i=1:num_teams], Bin) 
    @addConstraint(m, constr[i=1:num_teams], used_team[i] <= sum{skaters_teams[t, i]*skaters_lineup[t], t=1:num_skaters}) 
    @addConstraint(m, constr[i=1:num_teams], sum{skaters_teams[t, i]*skaters_lineup[t], t=1:num_skaters} <= 6*used_team[i]) 
    @addConstraint(m, sum{used_team[i], i=1:num_teams} == 3) 

If you see any glaring errors here please let me know.  I can also add all of the code I'm using if needed.

    used_team = [LpVariable("y{}".format(i+1), 0, 1,cat = pulp.LpInteger) for i in range(num_teams)]
    m += sum(u for u in(used_team)) == 3
    for j, (x,z) in enumerate( zip(xs, skaters_teams[:])):
       for i in range(num_teams):  
           m += sum(z[i]*x) >=ut[i]
           m += sum(z[i]*x) <=6*ut[i]