merenlin

import numpy as np

AAs = list('ACEDGFIHKMLNQPSRTWVY')
alphas = [0.05]*20
sequence = ''
weights = np.random.dirichlet(alphas)
for i in range(100):
    sequence += np.random.choice(AAs,p=weights)

merenlin

import random
import bisect
import itertools

def weighted_choice_b2(weights):
    partsums = list(itertools.accumulate(weights))
    total = partsums[-1]
    rnd = random.random() * total
    return bisect.bisect_right(partsums, rnd)

merenlin

import numpy as np

def weighted_choice(weights):
    totals = np.cumsum(weights)
    norm = totals[-1]
    throw = np.random.rand()*norm
    return np.searchsorted(totals, throw)