python celery Reviews & Product Details

Light weight, scheduler, retry failed tasks Review collected by and hosted on G2.com.

Command based interface only, need to add GUI in build support Review collected by and hosted on G2.com.

The most helpful part of Celery is that it can use a plethora of different backends for distributing and coordinating tasks. For example, Celery can use RabbitMQ, Redis, or Amazon SQS as brokers and backends. Through SQLAlchemy, it can also interface with even more storage backends, like PostgreSQL, SQLite, and MySQL. Programming with Celery hides intricate details of those message queues and database engines and feels very pythonic, much like simply calling functions with some added decorators. I also love that it is open source, so if I cannot find an answer in the documentation, I can study the source code to understand how Celery behaves in certain edge cases. Review collected by and hosted on G2.com.

I like most of the Celery experience but would like to see more nontrivial examples in the documentation and tutorials. For instance, it helps a lot to know the backend system you chose to use with Celery. Complex message-brokering scenarios can be solved elegantly without coding if you know how to configure RabbitMQ. By programming Redis directly through Lua scripts, you can gain some performance and, for example, improve Celery's rate-limiting system. I think more tutorials that show how such—and other— scenarios may be solved would significantly improve the Celery documentation. Review collected by and hosted on G2.com.

A great tool for developers to manage and scheduled the tasks in queue format as well as gives ease to developers to code.

Its very easy to install by just a pip command and you are good to go to use this as per your need. Review collected by and hosted on G2.com.

Nothing much its fast, easy to install and does the great job. Review collected by and hosted on G2.com.

As a software, we can easily code something with its developer-centric structure and include it in the job queue and run it. I think this makes the product great. It is also very important that it can be integrated with messaging tools like RabitMQ and Redis.In this way, the product can fully respond to all our needs. If I give the product a score, I give 85 out of 100. Review collected by and hosted on G2.com.

Python celery documents can sometimes be confusing. Because these documents contain information with two different meanings. However, in general, I am very pleased with the ease of use and performance of the product. Review collected by and hosted on G2.com.

Python celery is best for scheduling the task and task in queue and generation of automation Review collected by and hosted on G2.com.

The thing which is disliked is that sometimes all the data can be leaked Review collected by and hosted on G2.com.

I specifically like how the Celery architecture is based on task queues and the number of workers we can assign to each task queue. This way, a developer can uniformly distribute the heavier jobs to celery task with greater number of workers. It's compatibility with RabbitMQ and Redis makes it more convenient to work on. Review collected by and hosted on G2.com.

It is sometimes a headache to debug errors in Python Celery. I personally face an issue that Celery sometimes resets itself completely without finishing the pending tasks, thereby, wasting the whole iteration of data collection and processing before reset. Couldn't find a dependable solution to this problem yet. So, I need to eventually reinstall Celery whenever I face this, once in a blue moon. Review collected by and hosted on G2.com.

We use celery, in combination with RabbitMQ and celery-beat, to execute periodic tasks, as well as some long-running tasks initiated by the user on the server. Review collected by and hosted on G2.com.

Something that bothers me that the celery documentation of dynamic programming defined by the user is not good, It may be that I do not have skill that I had difficulties. I have to work another way to solve the problem with celery. But I'm happy with celery. Review collected by and hosted on G2.com.

I like python celery in light of it's developer situated organization as a product bundle. I can take it and begin incorporating things and send with the task queue and run streams.

Celery is written in python, however the convention is executed in any language. It can likewise work with different languages utilizing webhooks. There is additionally a Ruby-Client called RClerey, a PHPClient, Go customer and a Node.js customer. Review collected by and hosted on G2.com.

This is an open source bit of programming so support is to some degree restricted. Else, it is an extraordinary tool. Review collected by and hosted on G2.com.

Python Celery is a great real time, asyncronous job queue and scheduler and I think the best thing is that this job scheduler focuses on running concurrently as opposed to scheduling and running one task at a time. Review collected by and hosted on G2.com.

This is an open source piece of software so support is somewhat limited. Otherwise, it is a great tool. Review collected by and hosted on G2.com.

Ease of integration with django and python. Also has good documentation to get help. Also has good support. Review collected by and hosted on G2.com.

issues with task management when working with redis. Redis is not the best option to work with this specially when working with docker. Review collected by and hosted on G2.com.