I’m learning about concurrency in Python

I set up Celery run a script to fetch a request for 50 times and it only takes 0.13 seconds to finish, really surprise me !

When I compare with regular synchronous programming, it took ~ 1 minute to complete.

afaik, celery will spawn a pool of processes to execute the tasks. But I don’t think 500 tasks executed by celery worker can be much faster than sync execution of a single task.

# sync.py
import json
import requests
from timer import Timer

URL = 'https://httpbin.org/uuid'

def fetch(url):
    response = requests.get(url)
    data = json.loads(response.text)
    print(data['uuid'])


def main():
    with Timer():
        for _ in range(1):
            fetch(URL)

main()
# take ~50 seconds

# celery_demo.py
from celery import Celery
from timer import Timer
import json
import requests

URL = 'https://httpbin.org/uuid'

BROKER_URL = 'redis://localhost:6379/0'
RESULT_BACKEND = 'redis://localhost:6379/0'

app = Celery(__name__, broker=BROKER_URL, backend=RESULT_BACKEND)


@app.task(name='fetch')
def fetch():
    res = requests.get(URL)
    return res.json()['uuid']


def main():
    with Timer():
        for i in range(50):
            res = fetch.delay()
            print(res)


if __name__ == '__main__':
    main()

# Celery configuration
# celery -A celery_demo.app worker --concurrency=4

# takes ~0.1 to 0.2 seconds

May we give me some insights on this fact ?