Homepage | Celery: Distributed Task Queue
This document describes the current stable version of Celery (5.3). For development docs, go here. Celery - Distributed Task Queue¶ Celery is a simple, flexible, and reliable distributed system to process vast amounts of messages, while providing operations with the tools required to maintain such a system. It’s a task queue with focus on real-time processing, while also supporting task scheduling
RQ: Simple job queues for Python
RQ (Redis Queue) is a simple Python library for queueing jobs and processing them in the background with workers. It is backed by Redis and it is designed to have a low barrier to entry. It can be integrated in your web stack easily. RQ requires Redis >= 3.0.0. Getting started First, run a Redis server. You can use an existing one. To put jobs on queues, you don’t have to do anything special, just
A Better GitHub Issue Queue | Octokan
Transform your GitHub issue queue into a realtime kanban for your whole team Sign in with GitHub What's in the box? Organize your issues Start organizing issues and track their progress by picking labels you want to visualize as lists. Drag & Drop Keep your issues organized and up to date by simply dragging them from one list to another. Real-time collaboration Your whole team see changes by other
Queueing in the Linux Network Stack
[A slightly shorter and edited version of this article appeared in the July 2013 issue of Linux Journal. Thanks to Linux Journal’s great copyright policy I’m still allowed to post this on my site. Go here to subscribe to Linux Journal.] Packet queues are a core component of any network stack or device. They allow for asynchronous modules to communicate, increase performance and have the side affec
Q4M - a Message Queue for MySQL
Q4M (Queue for MySQL) is a message queue licensed under GPL that works as a pluggable storage engine of MySQL, designed to be robust, fast, flexible. It is already in production quality, and is used by several web services (see Users of Q4M). To start using Q4M, download either a binary or source distribution from the install page, and follow the installation instructions. A small tutorial is also
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GitHub - coleifer/huey: a little task queue for python
