python - 优化python中的程序

Question

我正在尝试在 HackerRank 上解决这个问题:

Animesh has N empty candy jars numbered from 1 to N with infinite capacity. He performs M operations. Each operation is described by 3 integers a, b and k where a and b are index of >the jars and k is the number of candies to be added inside each jar with index between a and >b (both inclusive). Can you tell the average number of candies after M operations? I have written the below code in Python 3:

def operate(a, b, k, array):
    for i in range(a - 1, b):
        array[i] += k
def mean(array):
    return int(sum(array) / len(array))
splitinput = [int(x) for x in input().split()]
candy = []
for i in range(splitinput[0]):
    candy.append(0)
for j in range(splitinput[1]):
    splitinput2 = input().split()
    operate(int(splitinput2[0]), int(splitinput2[1]), int(splitinput2[2]), candy)
print(mean(candy))

它有效，但在某些测试用例上超时。我怎样才能使它更快？我用 Python 编写代码已有一段时间了，但我仍然没有找到更精细的优化点。

Answer 1

你不关心糖果在哪里。只要知道有多少糖果和多少 jar ，就可以计算均值。因此，您可以只计算所有糖果的数量:

jars, ops = map(int, input().split())
candies = 0
for i in range(ops):
    a, b, k = map(int, input().split())
    candies += k*(b-a+1)
print candies / jars

这避免了必须跟踪 N 个单独的计数或为每个操作递增 k 个计数器。当您获得较大的 k 值时，这非常重要。