Build great Celery tasks! Free Collaborative Startup Engineering Team Task List / Checklist / Guide Template.
Yes, Celery may be a vegetable, but it’s also an open-source asynchronous task queue/job queue which is based on distributed message passing. Tasks are the building blocks of Celery applications.
Filipe A Ximenes, partner at Vinta Software, has created a useful checklist for building great Celery tasks! We’ve repurposed his checklist in Taskade into this celery tasks checklist template so that you can easily use it in conjunction with your other projects and templates.
Celery is a distributed task queue where you can do work asynchronously and process the workload in the background. Using celery, you don’t need to wait to process your tasks. Instead, you can run your task lists asynchronously.
To use celery, you first need to install it on your machine – can be done on a server or locally.
Celery has a built-in message broker which you can use to pass messages between your application and worker processes. Celery is often used with a message broker like RabbitMQ or Redis.
Celery task management is a process that processes tasks and dependencies asynchronously. Tasks are units of work that your application performs, and can be broken down into smaller units of work. With Celery, multiple tasks can be processed at the same time asynchronously using multiple processors.
Task queues can drastically improve the performance of your application. With a task queue, you push tasks onto the queue, and the task queue pushes them onto one or more worker machines. The workers process the tasks asynchronously in the background.
Celery allows you to run any kind of Python code, including regular functions and class methods, as tasks. You can also pass arguments to your tasks and return values.
Celery makes it easy to scale up your worker machines by delegating the task queue to one or more worker machines, without getting in the way of the application. It simply becomes part of an existing architecture like Django’s database layer or Flask’s WSGI layer.
It also gives you fine-grained control of task execution. It lets you run tasks on a single machine, or in a cluster of machines, and it uses the AMQP protocol to get tasks between clients and workers.
Task queues have unlimited potential. They can be used for processing tasks images, uploading files, generating thumbnails, sending email via a transactional email service, transcoding video and audio files with FFmpeg, and performing calculations in the cloud using Boto, among many other applications.
When used properly, Celery can help you increase your work output.
A Celery Task is basically just a Python function that is run in the background. You can use any regular Python function as a Celery Task. A Celery Task must always return a TaskResult, even if that’s just the default result (usually None).
Celery allows you to schedule tasks to be executed at any time after they are queued. You can set this delay to be relative (for example 5 seconds from now) or absolute (for example from the time the message was sent).
A beat is a scheduler process, which sends scheduled tasks out to the worker nodes.
Task results are sent back to your app via regular task callbacks or celery events so you can use them in monitoring tools.
Celery comes with a monitoring dashboard that you can use to check the status of your tasks. You can access it from a web browser at http://localhost:5555
The dashboard is a database that shows statistics from recently completed tasks, as well as those which are currently being processed by workers. It also graphs task durations and how long it took each worker to process each task.
A Celery Worker is basically just a Python process that executes the tasks you want, as instructed by the Beat scheduler.
You can have as many workers as you like, and configure them all separately. You often have several workers, but one scheduler.
Tasks are executed by one or more worker processes. You can use any programming language that can work with the supported message brokers to write your worker tasks, which makes Celery a very flexible option.
Celery workers do all of the hard work in a Celery installation. They handle requests from the web server, scheduled tasks, and events among other things.
Use our free celery tasks checklist and follow the list to make sure that you cover all the bases when using Celery.