Celery is an asynchronous task queue frequently used with Python-based web frameworks like Django or Flask. It is open-source and extensively used to organize background work outside the traditional request/response cycle. Celery can be a producer or consumer and is interoperable with many message brokers, including RabbitMQ and Redis.
Although Celery is built in Python, the protocol can be used with any language. Webhooks allow it to function with other languages as well. Celery can run on a single system, many machines, or several data centers.
Celery is free and open-source, which entices businesses or developers to utilize Celery.
It is a small, simplistic library that is simple to install. The command "pip install - U Celery" can be installed from the terminal.
Celery's components, including custom pool implementations, serializers, and more, can be expanded or utilized independently.
A single Celery process has a round-trip latency of less than one millisecond while processing millions of jobs per minute.
Celery supports a variety of message brokers, including the well-known RabbitMQ and Amazon SQS. However, it is deficient in several functionalities.
Celery integrates with many Python web frameworks, including Flask, Pyramid, Pylons, Django, Tornado, and Trylons.
It uses a collection of sophisticated primitives known as "canvas" to create basic and complicated work routines.
For UNIX systems, Celery is a distributed task queue. You may delegate tasks from your Python application with this.
Celery helps run several tasks together utilizing the primary process, and while you focus on your work, Celery will finish the immediate smaller jobs. For example, you can create queues, deal with data chunks on lengthy tasks, and schedule execution periods for your tasks.
Not only would using Celery with the FastAPI application increase performance and efficiency overall, but it would also facilitate better management of background processes for longer tasks.