from scipy.optimize import minimize

def objective(x):
    return x[1]

def constraint(x):
    return x[1] - (x[0]**1.5 - 2*x[0] + 3.0) # placeholder for large calculation

x0 = [4.0,2.2]

b = (0.0,5.0)
bnds = (b,b)

cons = [{'type': 'ineq', 'fun':constraint}]

sol = minimize(objective, x0, method='SLSQP',bounds=bnds,constraints=cons)