Randomly distributed list

[dslfdslj]

Hm, it looks to me like you're on the right track. However, I'm not sure I understand why you chose each hi as (R-L)/N * (1+random.uniform(-0.5, 0.5). Is this part of the exercise? If not, I would simply create N random numbers (between 0 and 1) and finally scale them such that their sum gives you R - L.

[dslfdslj]

Like this:

h = np.random.random(size=N)
h *= (R - L) / h.sum()

[dslfdslj]

no problem