import scipy.optimize as opt
import random


def f(x):
    return sum(x)


def integer_step(x):
    return tuple(1-i if random.randint(0, 1) == 1 else i for i in x)


bounds = tuple((0, 1) for _ in range(100))
minimizer_kwargs = {"method": "L-BFGS-B", "bounds": bounds}
x0 = tuple(1 for i in range(100))

result = opt.basinhopping(f, x0, T=50, minimizer_kwargs=minimizer_kwargs, take_step=integer_step, niter_success=1)
print(result)