OptimizationTips
Django has established itself as a software framework rich in features and suitable for developing high load sites and web applications in Python. However, the code does not always work following the logic that assumes a quick result. This is where you need to improve the performance of the code so as not to radically affect its behavior (ideally to completely reduce such an impact to zero).
The tasks Django optimization solves
Speaking about improving performance, we recommend specifying your goals. In most cases, you need to increase the speed, but sometimes the performance can be affected by a large amount of memory consumption or high database requirements (which are to be optimized).
It is important to understand that, in most cases, improving one parameter negatively affects the other one. Thus, if the program works faster now, then, most likely, the amount of memory consumed also will increase. Optimization measures sometimes just harm, reducing the quality of the program performance in general.
Approach the issue globally: sometimes, the time spent on implementing improvements is incommensurably more valuable than the perceived benefit. Otherwise, optimization affects the portability and maintainability of a code.
By outlining the tasks set, you can use tools that will help you find sources of inefficient work. More on that in the next section.
Comparative analysis of efficiency
Tools that will help identify the things that make the operation of the application worse:
● Django Debug Toolbar makes it possible to understand what actions the code performs and for what period of time. For example, you can find out the SQL queries generated by the page, as well as how long it will take.
● Other free services, the work of which is based on imitation of the actions of a real user. With their help, you won't understand how the code works from the inside out, but you'll learn information that you can't get from the Django environment. These are both free Google PageSpeed and paid services with the option of integration into the code base.
● paid services such as NewRelic (https://newrelic.com/) or DataDog (https://www.datadoghq.com/).
Correct actions not only after but also before
Django optimization includes actions that can help you address performance weaknesses. But at the same time, it is important to introduce experience in the process of writing code, which will make the application more productive while reducing the amount of work to correct defects. In this aspect, the Python language is very effective: it gives organic insight, which provides the most brilliant performance.
For example, you can determine the number of items in several ways using a QuerySet, Python, or a template. But practice shows that this can be done quickly at the lower levels.
Django caching
Calculating value sometimes costs a lot of resources and time, so storing it in a cache with quick access is more convenient. Since this technique is
essential and significantly impacts the result, Django implements a multicomponent caching framework.
● The caching framework preserves dynamic content, eliminating the need to compute it each time. You can cache the entire site, some views, or parts of them. Important: using caching is not an alternative to poorly written code. Rather, it is one of the final steps that will improve the code.
● The decorator cashed_property is applicable when the method of a class instance must be called repeatedly. The decorator is responsible for preserving the value returned by the property. Please note that the tool is applicable when the method takes self as the only argument.
Laziness: the essence of strategy and implementation in Django
If caching solves the problem of repeated calculations, then laziness postpones them until the moment when they are really needed. Thanks to it, you can refer to things before the instantiation time. For example, lazy translation is used before the user learns about the target language.
In such a way, laziness allows you to accumulate efforts to avoid doing something you may not need later. This means the relationship with productivity: with the increase in labor costs, the benefit of laziness increases too.
The principle of laziness is implemented in Django. For example, a QuerySet object can be created, moved, and combined with other objects without applying to the database. QuerySet is the only object in the collection of elements to be passed.
Let's talk about our own caching features in Django projects below.The keep_lazy() decorator works according to the same principle. It ensures the lazy performance of the function called with a lazy argument before the evaluation stage.
Django database optimization
The Django database describes various ways to improve productivity. If you have to spend a lot of time processing a request, enabling persistent connections might help, which is vital for virtualized hosts with low performance.
HTTP performance
Middleware
Django contains some components of Middleware:
● ConditionalGetMallieware, which reports on modern browser support for a GET response based on the Last-Modified ETag;
● GZipMiddleWare, which compresses responses for browsers and thereby increases throughput, speeds up the transmission. It is now regarded as a risk factor and leveling protection against TLS / SSL.
Sessions
Cached sessions can remove the need to load data from a slow storage source, improving performance.
Static files
ManifestStaticFilesStorage excludes network requests for a particular file after the initial download. Adding a tag provides durable caching. The tag also changes when the file changes, which entails reloading the asset.
Some extra tools allow you to minimize the language by removing unnecessary spaces and lines.
Template execution
Templates with a high degree of fragmentation do not allow you to optimize the code. In order not to compile the template every time, a cached template loader is used.
Various versions of available software
More experienced users can test another method for optimization and take advantage of higher performance versions of the software. It is not worth placing high hopes, as this is rather a sample. Still, there are sometimes cases of poor performance of new versions, and Django is no exception.
Alternative systems of templates
If you can't solve some particular problems with Django, it might be reasonable to turn to an extra source. For instance, another implementation of your Python program allows faster operation. However, the pattern of such shortcomings is not at the Python level but in the inefficiency of database queries, caching, and templates. An alternative implementation may result in problems with compatibility, deployment, portability, or maintenance. Assessing how significant the productivity gains will be in such a decision is important.
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