When settings.DEBUG is set to False, exception tracebacks will be sent to settings.ADMINS. To make it simpler to track down how and why the exception was raised, it's beneficial to know which user caused the exception.

It's quite simple to do this using some custom middleware. In the Hub, we include the associated users email address in the exception with the following:

So you developed a Django web application and now need to deploy it into production, but still need to actively continue development (bugfixes, tweaks, adding and testing new features, etc.)

In your development environment you probably had debugging enabled, performance settings disabled, used SQLite as your database, and other settings that make development easier and faster. 

But in production you need to disable debugging, enable performance, and use a real database such as MySQL or PostgreSQL, etc.

By reducing the file size of your CSS, JavaScript and images, as well as the number of unnecessary browser requests made to your site, load time of your applications pages can be drastically reduced, not to mention the load on your server.

Yahoo have created a list of the 35 best practices to speed up your website, a recommended read for any web developer. I wanted to summarize a few I recently implemented in a Django application.

In a nutshell:

Or, Celery + RabbitMQ = Django awesomeness!

As you know, Django is synchronous, or blocking. This means each request will not be returned until all processing (e.g., of a view) is complete. It's the expected behavior and usually required in web applications, but there are times when you need tasks to run in the background (immediately, deferred, or periodically) without blocking.

Some common use cases:

• Give the impression of a really snappy web application by finishing a request as soon as possible, even though a task is running in the background, then update the page incrementally using AJAX.
• Executing tasks asynchronously and using retries to make sure they are completed successfully.
• Scheduling periodic tasks.
• Parallel execution (to some degree).