How does thread pooling works, and how to implement it in an async/await env like NodeJS?

Reimplementation of that Bluebird function I linked to:

const mapWithConcurrency = async (values, concurrency, fn) => {
    let i = 0;
    let results = values.map(() => null);

    const work = async () => {
        while (i < values.length) {
            const current = i++;
            results[current] = await fn(values[current]);
        }
    };

    await Promise.all(Array.from({length: concurrency}, work));

    return results;
};

mapWithConcurrency(Array.from({length: 30 * 15}, (_, i) => i), 10, async i => {
    const el = document.body.appendChild(document.createElement('i'));
    el.style.left = 5 * (i % 30) + 'px';
    el.style.top = 5 * (i / 30 | 0) + 'px';
    await new Promise(resolve => { setTimeout(resolve, Math.random() * 500); });
    el.style.background = 'black';
    return 2 * i;
}).then(results => {
    console.log(results.length, results.every((x, i) => x === 2 * i));
});

i {
    background: grey;
    transition: background 0.3s ease-out;
    position: absolute;
    width: 5px;
    height: 5px;
}

Not sure it is how ThreadPool and other libraries are implemented but here is a hint : use Queues to count how many tasks/threads are running.
I didn't try this code but it can give you an idea: we create a Thread checking every 0.2 second if we should start another Thread.
This implies a lot of context switching however and might not be efficient.

class Pool:
    def __init__(self, func: Callable, params: list, thread_max = 10):
        self.func = func
        self.params = params
        self.running = 0
        self.finished = []
        self.thread_max = thread_max
        self.threads = []

    def start(self):
        Thread(target=check, args=(0.2)).start()

    def check(self, t_sleep=0.5):
        done = False
        while not done:
            sleep(t_sleep)
            # first check for finished threads
            for t in threads:
                if not t.isAlive():
                    # do something with return value
                    # ...
                    self.threads.remove(t)

            if not len(self.params): # mean there is no more task left to LAUNCH
                done = len(self.threads) # gonna be 0 when every tasks is COMPLETE
                continue # avoid the next part (launching thread)

            # now start some threads if needed
            while len(self.threads) < self.thread_max:
                arg = self.params.pop()
                thread = Thread(target=self.func, args=(arg, ))
                threads.insert(thread)
                thread.start()

I however do not have any clue for async/await (keywords now available in python)