simple async ea

main.py

import asyncio
from random import random, choices

def clip(x, x0, x1):
    return x0 if x < x0 else x1 if x > x1 else x

def make_masks(geneSize, popSize, crossoverNum):
    mask0 = [0] * geneSize
    mask1 = [int(i / int(geneSize / crossoverNum)) % 2 for i in range(geneSize)]
    mask2 = [-x for x in mask1]
    return [mask0 if i == popSize - 1 else mask1 if i % 2 == 0 else mask2 for i in range(popSize)]

async def run(bound, func, popSize=100, selectSize=5, crossoverNum=3, mutation=0.01, maxGenNum=100):
    pop = [[lower + (upper - lower) * random() for lower, upper in bound] for i in range(popSize)]
    masks = make_masks(len(bound), popSize, crossoverNum)
    generation = 0
    while generation < maxGenNum:
        # get fitness
        ret = [[chromo, fitness] for chromo, fitness in zip(pop, await func(pop))]
        # select
        selected = sorted(ret, key=lambda x: x[1], reverse=True)[0:selectSize]
        # get parents
        parents = [choices([c[i] for c, _ in selected], [w for _, w in selected], k=popSize) for i in range(len(bound))]
        # crossover to create offsprings
        offsprings = [[parents[j][i + m[j]] for j in range(len(parents))] for i, m in enumerate(masks)]
        # mutation
        for offspring in offsprings:
            for i, [lower, upper] in enumerate(bound):
                if random() < mutation:
                    delta = random() * (upper - lower)
                    offspring[i] = clip(offspring[i] + delta, lower, upper)
        pop = offsprings
        generation += 1
    
    return selected[0]

async def eval(xs):
    return [sum([v * v for v in x]) for x in xs]

async def main():
    print(await run([[0, 1]] * 100, eval))

asyncio.run(main())