In this short article, we will try to depict the best methods for Django performance optimization. We will discuss the most common mistakes and ways to avoid them but, before we start, for those who are interested in more articles like this one or related to Django to Heroku migration, we can recommend this Django to Heroku deployment tutorial. As for now, let’s dive deeper into Django performance optimization.
How to optimize performance
There are just a few basic Django performance optimization tips we would like to share with you today. They will cover the most common production practices we have come across in our research.
First, let’s have a look at database optimization. For decreasing the number of queries to the database, the majority of developers will probably use select_related and prefetch_related to the Django QuerySets, which does decrease the number of queries, to be honest. On the other hand, it also increases the total time for completing requests, which makes no sense to us.
So, our advice here is to use the log of long queries (for instance, with some help from PostgreSQL log or NewRelic) instead of trying to optimize them on the development side.
When it comes to coding in Django, RunProfileServer is probably the most commonly used Django-extension; however, in our opinion, it is too simple and not the most convenient option. Our recommendation is to replace it (or to combine both methods together) by using line_profiler.
To compare, the RunProfileServer gives you a hard time to read all the data with no option of breaking down the code for the performance check. Whereas, the alternative method allows users to see and measure the middlewares and Django code, which makes it easier to evaluate the code.
The two previous tips lead us to the very basic but valuable third recommendation. Look beyond the parameter stats. Concentrate your vision on a broader picture. By paying attention to calling out specific details and analyzing the work of the database, you will lose touch with the app’s logic.
For instance, a rise in queries doesn’t always show a loss of performance. In reverse, a lower number of queries can make the process go slower since they might be too complex, but you can miss that by paying attention only to the changes (i.e. time consumption) of the database.
As a bonus, we could also recommend the installation of Django-debug-toolbar for debugging SQL queries. This can serve as a great analyzing tool for measuring call time consumption and query execution.
Index the tables
One more important thing worth mentioning is how crucial it is to understand your data for the process of optimization. Now, it seems obvious but, no ORM improving technique really matters unless you master the table structures and queries.
For those who are interested in more methods and how to optimize Django performance, we could also suggest reading development companies’ blogs (such as gearheart.io). In these pages, you will find more detail-oriented articles and learn more about custom web development, like the common online projects for the business that are now trending, what startups are now in favor, what the best prices for custom development are, and many more.