📅  最后修改于: 2023-12-03 14:59:54.328000             🧑  作者: Mango
Celery is a powerful and flexible task queueing library that allows you to distribute tasks across multiple worker processes, machines, and even data centers. It supports a wide range of message brokers, including RabbitMQ, Redis, Amazon SQS, and more. Celery can be used for many kinds of distributed tasks, such as running scheduled jobs, processing emails, and resizing images, just to name a few.
Gevent is a coroutine-based Python networking library that allows you to write asynchronous, non-blocking code in a synchronous style. Gevent uses greenlets, an abstraction of lightweight threads, to enable high concurrency with low overhead. Gevent is also compatible with many networking frameworks, such as Flask and Django.
Celery can use Gevent as a worker pool to process tasks concurrently. This allows you to take advantage of Gevent's lightweight concurrency model to handle many concurrent tasks efficiently. To use Gevent with Celery, you need to install the celery[gevent] package:
pip install celery[gevent]
Then you can configure Celery to use the Gevent pool:
from celery import Celery
from celery import platforms
app = Celery('tasks', broker='amqp://guest:guest@localhost:5672//')
# Set the default concurrency limit
app.conf.task_concurrency = 1000
# Use the Gevent pool
app.conf.worker_pool = 'gevent'
# Allow the worker to gracefully shutdown
platforms.signals['TERM'] = platforms.signals['INT'] = platforms.signals['HUP'] = platforms.signals['QUIT'] = 'worker_term'
@app.task
def add(x, y):
return x + y
In this example, we've set the task_concurrency
to 1000 to limit the maximum number of concurrent tasks that can be processed at once. We've also set the worker_pool
to "gevent" to use the Gevent worker pool. Finally, we've added a simple task called add
that adds two numbers together.
Celery and Gevent are powerful libraries that can help you build distributed, high-performance Python applications. By combining Celery's task queueing capabilities with Gevent's lightweight concurrency model, you can efficiently process many concurrent tasks with ease.