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What is Celery?

Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well.
Celery is a tool in the Message Queue category of a tech stack.
Celery is an open source tool with 16K GitHub stars and 3.9K GitHub forks. Here鈥檚 a link to Celery's open source repository on GitHub

Who uses Celery?

407 companies reportedly use Celery in their tech stacks, including Udemy, Robinhood, and Accenture.

748 developers on StackShare have stated that they use Celery.
Public Decisions about Celery

Here are some stack decisions, common use cases and reviews by companies and developers who chose Celery in their tech stack.

Michael Mota
Founder at AlterEstate | 6 upvotes 路 215.5K views

Automations are what makes a CRM powerful. With Celery and RabbitMQ we've been able to make powerful automations that truly works for our clients. Such as for example, automatic daily reports, reminders for their activities, important notifications regarding their client activities and actions on the website and more.

We use Celery basically for everything that needs to be scheduled for the future, and using RabbitMQ as our Queue-broker is amazing since it fully integrates with Django and Celery storing on our database results of the tasks done so we can see if anything fails immediately.

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Greg Smethells
CTO and Software Architect at Medstrat | 3 upvotes 路 10.8K views

We use AppOptics. I am curious what are the current leaders for APM for small companies (50 employees) that use Python, MariaDB, RabbitMQ, and Google Cloud Storage. We run both Celery and Gunicorn services. We are considering Datadog or some other deep code profiling tool that can spot I/O, DB, or other response time/request rate issues

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Shared insights

I am just a beginner at these two technologies.

Problem statement: I am getting lakh of users from the sequel server for whom I need to create caches in MongoDB by making different REST API requests.

Here these users can be treated as messages. Each REST API request is a task.

I am confused about whether I should go for RabbitMQ alone or Celery.

If I have to go with RabbitMQ, I prefer to use python with Pika module. But the challenge with Pika is, it is not thread-safe. So I am not finding a way to execute a lakh of API requests in parallel using multiple threads using Pika.

If I have to go with Celery, I don't know how I can achieve better scalability in executing these API requests in parallel.

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Blog Posts

Celery Alternatives & Comparisons

What are some alternatives to Celery?
RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
Cucumber is a tool that supports Behaviour-Driven Development (BDD) - a software development process that aims to enhance software quality and reduce maintenance costs.
Amazon SQS
Transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be always available. With SQS, you can offload the administrative burden of operating and scaling a highly available messaging cluster, while paying a low price for only what you use.
See all alternatives

Celery's Followers
1021 developers follow Celery to keep up with related blogs and decisions.