aima/utils.py
def weighted_sampler(seq, weights):
    "Return a random-sample function that picks from seq weighted by weights."
    totals = []
    for w in weights:
        totals.append(w + totals[-1] if totals else w)
    return lambda: seq[bisect.bisect(totals, random.uniform(0, totals[-1]))]
def weighted_sampler(seq, weights):
    "Return a random-sample function that picks from seq weighted by weights."
    totals = []
    for w in weights:
        totals.append(w + totals[-1] if totals else w)
    return lambda: seq[bisect.bisect(totals, random.uniform(0, totals[-1]))]
Return a random-sample function that picks from seq weighted by weights.