Quick+dumb way to sort an array to try and maximize Hamming distance between adjacent elements

flopsort.py

import random

def hamming(a, b):
    x = a ^ b
    c = 0
    while x:
        x &= x - 1
        c += 1
    return c

def score(l):
    weights = [hamming(a, b) for [a, b] in zip(l, l[1:])]
    print(weights)
    return sum(weights)

def flop_sort(lst):
    for i in range(10000):
        # Randomly partition
        mid = random.randint(2, len(lst) - 2)
        [first, second] = [lst[:mid], lst[mid:]]
        # Get the endpoints of each segment
        [a, b, c, d] = [first[0], first[-1], second[0], second[-1]]
        # Find the best arrangement of segments
        weights = [(hamming(a, c), 0), (hamming(a, d), 1),
                (hamming(b, c), 2), (hamming(b, d), 3)]
        best = max(weights)[1]
        if   best == 0: lst = first[::-1] + second
        elif best == 1: lst = second + first
        elif best == 2: lst = first + second
        elif best == 3: lst = first + second[::-1]
    return lst

N = 32

# Anti-Gray code
l = [a ^ (a >> 1) ^ (N - 1 if a & 1 else 0) for a in range(N)]
print(l)
print(score(l))

# Flop sort
l = flop_sort(list(range(N)))
print(l)
print(score(l))