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You can divide a number 'n' into random k numbers using either Dirichlet distribution or the multinomial distribution. You need to draw k samples from one of these distributions that will sum to the given number.

**Using the multinomial distribution**

The below code uses n as the number of experiments in the multinomial distribution. The second parameter is the probabilities of each of the k different outcomes.

>>> import numpy as np

>>> n, k = 132, 5>>> k_nums = np.random.default_rng().multinomial(n, [1/k]*k, size=1)[0]

>>> print(np.sum(k_nums), k_nums)

132 [29 22 36 23 22]

**Using Dirichlet distribution**

The below code generates k float values using the Dirichlet() function such that their sum is 1. Then, those float values are multiplied by n and rounded to get integer values.

>>> import numpy as np

>>> n, k = 132, 5>>> vals = np.random.default_rng().dirichlet(np.ones(k), size=1)

>>> vals

array([[0.37236123, 0.50029459, 0.04043982, 0.02848854, 0.05841581]])

>>> k_nums = [round(v) for v in vals[0]*n]

>>> print(np.sum(k_nums), k_nums)

132 [49, 66, 5, 4, 8]