Celery Background Jobs
Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well.
- Since:2010
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- Dockerhub:celery
- Docs:docs.celeryproject.org
- Github Topic:celery
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- Official:docs.celeryproject.org
- Reddit:r/celery
- Repository:github.com
- Twitter:@celeryproject
- Wikipedia:Celery_(software)
#What is Celery?
Celery is a distributed task queue that allows developers to run time-consuming and resource-intensive jobs asynchronously in the background. It is written in Python and is used by many web applications to handle tasks that cannot be handled in real-time. Celery can be used with many different message brokers such as RabbitMQ, Redis, or even Amazon SQS.
#Celery Key Features
Here are some of Celery’s most recognizable features:
- Task scheduling and execution: Celery allows developers to schedule tasks for a specific time or to execute tasks immediately.
- Distributed architecture: Celery enables distributed task processing across multiple worker nodes.
- Task prioritization: Celery supports prioritizing tasks based on their importance.
- Result storage: Celery allows the results of completed tasks to be stored in a database, cache, or message broker.
- Monitoring and reporting: Celery provides detailed information about the status of running tasks and can generate reports on completed tasks.
- Retries and error handling: Celery provides support for retrying tasks that fail due to errors or other issues.
#Celery Use-Cases
Here are some common use cases for Celery:
- Email delivery: Celery can be used to asynchronously send emails, which can be a time-consuming process.
- Image and video processing: Celery can be used to process images or videos, such as generating thumbnails or creating video previews.
- Periodic tasks: Celery can be used to run periodic tasks such as database backups or cleaning up old files.
#Celery Summary
Celery is a powerful task queue that enables developers to run background jobs asynchronously and distribute work across multiple worker nodes. It supports task prioritization, result storage, monitoring, and retrying failed tasks, making it an essential tool for many web applications.
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