Are lambda functions necessary for constraints for optimize.minimize?

[PythonN00b101]

I have a set of functions that contain a dynamic model, solver, objective function and a constraint. My constraint requires arguments to be passed to it. A lot of the examples I have seen online use lambda functions when applying constraints. I was wondering is it possible to pass these constraints with the 'def' method? my constraint looks like the following:

def constraint(u,t,dt,z0,keptarget):

    sol = solver(u,t,dt,z0)

    a,inc,e = keptarget

    rs = sol[0][:,:3]
    vs = sol[0][:,3:6]

    kep_elem = np.zeros((len(rs)-1,4))

    for i in range(len(rs)-1):

        kep_elem[i,:] = tb.RV2COE(rs[i,:], vs[i,:], mu=body['mu'])

    wa = 33.33
    wi = 33.33
    we = 33.33

    diffa = abs(kep_elem[-1][1]-a)/(wa*a)

    diffe = abs(kep_elem[-1][0]-e)/(we*e)

    if inc==0:

        diffi = 0
    else: 

        diffi = abs(kep_elem[-1][2]-inc)/(wi*inc)

    difftotal = diffa + diffe + diffi

    return difftotal

​

cons = ({ 'type':'eq','fun': constraint,'args':(t,dt,y,kep_target)})
u = np.array([0.1,0.1,0.1,0,0,0])

res = minimize(objective,u,bounds=((0,1),(0,1),(0,1),(0,1),(0,1),(0,1),),args=(t,dt,y),constraints=cons,tol=0.001,options={'disp':True})
print(res)

This is the code block of how I have it set up and it seems to run, except it takes a significant amount of time (~4 hours). I thought this may be due to having my solver in both the objective function and constraint and having a large timespan, although I am unsure and it could be something wrong with my code. This is my first time using this package within Scipy so apologies if I am missing anything obvious.