Generating a list of random numbers that sum to a certain integer is a very difficult task. Keeping track of the remaining quantity and generating items sequentially with the remaining available quantity results in a non-uniform distribution, where the first numbers in the series are generally much larger than the others. On top of that, the last one will always be different from zero because the previous items in the list will never sum up to the desired total (random generators usually use open intervals in the maximum). Shuffling the list after generation might help a bit but won't generally give good results either.
A solution could be to generate random numbers and then normalize the result, eventually rounding it if you need them to be integers.
import numpy as np
totals = np.array([54,1536,36,14]) # don't use Sum because sum is a reserved keyword and it's confusing
a = np.random.random((6, 4)) # create random numbers
a = a/np.sum(a, axis=0) * totals # force them to sum to totals
# Ignore the following if you don't need integers
a = np.round(a) # transform them into integers
remainings = totals - np.sum(a, axis=0) # check if there are corrections to be done
for j, r in enumerate(remainings): # implement the correction
step = 1 if r > 0 else -1
while r != 0:
i = np.random.randint(6)
if a[i,j] + step >= 0:
a[i, j] += step
r -= step
Each column of a represents one of the lists you want.
Hope this helps.
