akhushnazarov

Optimizing Django and Celery for Handling Many Concurrent Requests

Handling a high volume of concurrent requests in a Django application with Celery for background tasks can be challenging. This guide will walk you through the necessary steps to optimize your setup for better performance and scalability.

Default Setup with Gunicorn and Celery

By default, Gunicorn with Django and Celery uses synchronous workers to handle web requests and background tasks. This means:

• Gunicorn: Uses sync workers which can handle one request at a time per worker.
• Celery: Processes tasks synchronously within each worker.

rowillia

The Magic of the -3 Flag in Python 2

Porting code from Python 2 to Python 3 can be a daunting task. Tools like Futureize or Modernize can do most of the mechanical work for you, and Pylint can find obvious problems with code that's meant to be 2and3 compatible. You should absolutely be using these tools as they identify the lion's share of compatibility problems. Thanks to this work, it's really never been easier to port a large codebase to Python 3.

Even with these tools, however, porting code in a way that ensures identical behavior in Python 2 and Python 3 is tough. Python is a highly dynamic language and there is a huge breadth of changes between Python 2 and Python 3. Also, while we'd all love to work in code bases with 100% unit test coverage, the reality is unfortunately often very different. Given this, it's hard if not impossible for a static analysis tool t