在不使用任何numpy花哨的向量化计算的情况下，你已经可以通过预计算和记忆所有内容来大大减少时间（假设你对大量样本N重复这个过程）：

from itertools import combinations_with_replacement
import random
import timeit

N = 10000

ccc = [round(random.normalvariate(8,3)) for _ in range(N)]
num_deals = [random.randint(0,4) for _ in range(N)]

# first benchmark your solution:
def deal_months(ccc, num_deals, min=0, max=36):
    if len(ccc) != len(num_deals):
        raise Exception("ccc is not the same length as num_deals")
    integers = list(range(min, max + 1))
    combinations = [list(combinations_with_replacement(integers, 1)),
                    list(combinations_with_replacement(integers, 2)),
                    list(combinations_with_replacement(integers, 3)),
                    list(combinations_with_replacement(integers, 4))]
    final_combos = []
    for ccc, num_deals in zip(ccc, num_deals):
        if num_deals == 0: 
            final_combos += [0]
            continue
        matching_combos = [combo for combo in combinations[num_deals - 1] if sum(combo) == ccc * num_deals]
        if not matching_combos: 
            final_combos += [0]
            continue
        rand = random.randint(0, len(matching_combos) - 1)
        final_combos += [matching_combos[rand]]
    return final_combos

%timeit deal_months(ccc, num_deals)
# 10.2 s ± 71.5 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)


from collections import defaultdict

# now compare with mine:
def deal_months_2(ccc, num_deals, min=0, max=36):
    if len(ccc) != len(num_deals):
        raise Exception("ccc is not the same length as num_deals")
    integers = list(range(min, max + 1))
    all_matching_combos = defaultdict(list)
    for n in range(1,5):
        for c in combinations_with_replacement(integers, n):
            mean, rest = divmod(sum(c), n)
            if rest:
                continue
            all_matching_combos[(mean, n)].append(c)
    final_combos = []
    for c, n in zip(ccc, num_deals):
        matching_combos = all_matching_combos[(c, n)]
        if not matching_combos: 
            final_combos.append(0)
            continue
        final_combos.append(random.choice(matching_combos))
    return final_combos
    
%timeit deal_months_2(ccc, num_deals)
# 14.4 ms ± 576 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)

请注意，大部分时间是预先计算，一旦完成，即使是大量的采样也变得微不足道：

def get_all_matching_combos(min=0, max=36):
    integers = list(range(min, max + 1))
    all_matching_combos = defaultdict(list)
    for n in range(1,5):
        for c in combinations_with_replacement(integers, n):
            mean, rest = divmod(sum(c), n)
            if rest:
                continue
            all_matching_combos[(mean, n)].append(c)
    return all_matching_combos

%timeit get_all_matching_combos()
# 11.9 ms ± 12.5 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)

def sample(ccc, num_deals, all_matching_combos=get_all_matching_combos()):
    if len(ccc) != len(num_deals):
        raise Exception("ccc is not the same length as num_deals")
    final_combos = []
    for c, n in zip(ccc, num_deals):
        matching_combos = all_matching_combos[(c, n)]
        if not matching_combos: 
            final_combos.append(0)
            continue
        final_combos.append(random.choice(matching_combos))
    return final_combos

N = 10000
ccc = [round(random.normalvariate(8,3)) for _ in range(N)]
num_deals = [random.randint(0,4) for _ in range(N)]
%timeit sample(ccc, num_deals)
# 2.53 ms ± 7.63 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)

你也可以通过设置随机种子来确保相同的结果，让自己相信我的魔法等同于你的原始代码：

def deal_months(ccc, num_deals, min=0, max=36):
    if len(ccc) != len(num_deals):
        raise Exception("ccc is not the same length as num_deals")
    integers = list(range(min, max + 1))
    combinations = [list(combinations_with_replacement(integers, 1)),
                    list(combinations_with_replacement(integers, 2)),
                    list(combinations_with_replacement(integers, 3)),
                    list(combinations_with_replacement(integers, 4))]
    final_combos = []
    random.seed(0) # <<< ensure same sampling
    for ccc, num_deals in zip(ccc, num_deals):
        if num_deals == 0: 
            final_combos += [0]
            continue
        matching_combos = [combo for combo in combinations[num_deals - 1] if sum(combo) == ccc * num_deals]
        if not matching_combos: 
            final_combos += [0]
            continue
        rand = random.randint(0, len(matching_combos) - 1)
        final_combos += [matching_combos[rand]]
    return final_combos

def deal_months_2(ccc, num_deals, min=0, max=36):
    if len(ccc) != len(num_deals):
        raise Exception("ccc is not the same length as num_deals")
    integers = list(range(min, max + 1))
    all_matching_combos = defaultdict(list)
    for n in range(1,5):
        for c in combinations_with_replacement(integers, n):
            mean, rest = divmod(sum(c), n)
            if rest:
                continue
            all_matching_combos[(mean, n)].append(c)
    final_combos = []
    random.seed(0) # <<< ensure same sampling
    for c, n in zip(ccc, num_deals):
        matching_combos = all_matching_combos[(c, n)]
        if not matching_combos: 
            final_combos.append(0)
            continue
        final_combos.append(random.choice(matching_combos))
    return final_combos

N = 1000
ccc = [round(random.normalvariate(8,3)) for _ in range(N)]
num_deals = [random.randint(0,4) for _ in range(N)]
d = deal_months(ccc, num_deals)
d2 = deal_months_2(ccc, num_deals)
assert d == d2