Celery - Distributed Task Queue — Celery 5.5.0 documentation
The official documentation site for Celery, a distributed task queue system written in Python. It provides comprehensive guides, tutorials, and API references for developers to implement asynchronous task queues and scheduled jobs in their applications.
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Website Key Features
Comprehensive Documentation
Detailed guides and tutorials covering all aspects of Celery, from basic setup to advanced features.
API Reference
Complete reference for all Celery APIs, including task decorators, configuration options, and worker commands.
Best Practices
Guidelines and recommendations for optimizing Celery performance and reliability in production environments.
Community Contributions
Includes contributions from the Celery community, offering additional insights, tips, and tricks.
Version Compatibility
Information on compatibility between different versions of Celery and Python, helping developers choose the right versions for their projects.
Integration Guides
Step-by-step guides for integrating Celery with popular frameworks and services like Django, Flask, and RabbitMQ.
Troubleshooting
Common issues and their solutions, helping developers quickly resolve problems encountered while using Celery.
Performance Tuning
Tips and techniques for tuning Celery for better performance, including worker configuration and task optimization.
Security Practices
Best practices for securing Celery applications, including authentication, authorization, and data protection.
Scalability
Strategies for scaling Celery applications to handle increased load, including distributed task execution and result storage.
Additional information
License
Celery is open-source and released under the BSD License.
Source Code
The source code for Celery is available on GitHub, allowing developers to contribute to the project or customize it for their needs.
Community Support
Celery has a vibrant community of developers who contribute to its development, provide support through forums, and share their experiences and best practices.
Extensions
There are several extensions and plugins available for Celery, enhancing its functionality and integration with other technologies.
Concurrency
Celery supports multiple concurrency models, including multiprocessing, eventlet, and gevent, allowing developers to choose the best model for their application's needs.
Broker Support
Celery supports multiple message brokers, including RabbitMQ, Redis, and Amazon SQS, providing flexibility in how tasks are queued and distributed.
Result Backends
Celery can store task results in various backends, such as Redis, Memcached, and Django ORM, allowing for flexible result retrieval and storage.
Periodic Tasks
Celery supports periodic tasks through Celery Beat, enabling scheduled task execution at fixed intervals or specific times.
HTTP headers
Security headers report is a very important part of user data protection. Learn more about http headers for docs.celeryproject.org