我会把choices实现从random模块中分离出来，比如：

from random import SystemRandom
from itertools import accumulate as _accumulate, repeat as _repeat
from bisect import bisect as _bisect

def choices(population, weights, *, k=1):
    randrange = SystemRandom().randrange
    n = len(population)
    cum_weights = list(_accumulate(weights))
    if len(cum_weights) != n:
        raise ValueError('The number of weights does not match the population')
    total = cum_weights[-1]
    if not isinstance(total, int):
        raise ValueError('Weights must be integer values')
    if total <= 0:
        raise ValueError('Total of weights must be greater than zero')
    bisect = _bisect
    hi = n - 1
    return [population[bisect(cum_weights, randrange(total), 0, hi)]
            for i in _repeat(None, k)]

其可以被测试为：

from collections import Counter

draws = choices([1, 2, 3], [1, 2, 3], k=1_000_000)
print(dict(sorted(Counter(draws).items())))

给了我：

{1: 166150, 2: 333614, 3: 500236}

看起来差不多。
更新：只是想检查一个错误，它似乎很好在这里：

print(
    choices([1, 2, 3], [1, 0, 0], k=5),
    choices([1, 2, 3], [0, 1, 0], k=5),
    choices([1, 2, 3], [0, 0, 1], k=5),
)

给出：

[1, 1, 1, 1, 1] [2, 2, 2, 2, 2] [3, 3, 3, 3, 3]

这似乎也是对的