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README.md

FastQueue

A high-performance, Redis-backed task worker designed for Python applications requiring non-blocking execution.

Table of Contents

• About the Project
• Features
• Tech Stack
• Getting Started
• Usage
• Contributing
• License

About the Project

FastQueue solves the bottleneck of synchronous task processing. By leveraging Redis, it allows Python developers to offload heavy workloads to background workers without blocking the main application thread, ensuring low latency and high throughput.

Features

• 🚀 Non-blocking Execution: Process tasks in the background effortlessly.
• ⚖️ Priority Levels: Assign weights to tasks to ensure critical jobs finish first.
• 📋 JSON Logging: Structured logs ready for ELK or Datadog integration.
• 🔄 Auto-Retry: Built-in mechanism for handling transient failures.

Tech Stack

• Language: Python 3.8+
• Infrastructure: Redis
• Serialization: JSON

Getting Started

Installation

Install the package via pip

pip install fastqueue-python

Prerequisites

Ensure you have a Redis instance running

docker run -p 6379:6379 redis

Usage

Basic example of defining and pushing a task:

from fastqueue import Worker

worker = Worker(redis_url="redis://localhost:6379")

@worker.task(priority="high")
def process_data(data):
    print(f"Processing: {data}")

process_data.delay({"id": 101, "status": "pending"})

Contributing

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

Next steps

1. Add a high-quality banner image URL to the header section.
2. Update the redis_url in the Usage example to match your production environment.
3. Replace the version badge value when you perform your first release.