use uniform sum distribution to calculate e

uniform_sum_distribution_for_e.py

def uniform_sum_distribution_for_e(N,target):
    count_sum = 0
    import random
    for i in range(N):
        sum = 0
        while True:
            j = random.random()
            sum+=j
            count_sum+=1
            if sum > target:
                sum = 0
                break
    return count_sum/N
# when target = 1, it should be about e = 2.71828
# when target = 2, it should be about e^2 -e ~= 4.67077
# https://mathworld.wolfram.com/UniformSumDistribution.html
# this method do not have much precision
uniform_sum_distribution_for_e(100000,2)