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Performance testing and optimization on Django REST API

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Albin Antony,Software Engineer

The role of APIs in web and app development has increased significantly. API has become vital to our connected world. It is the set of tools, protocols, standards, and code that binds our digital world together. APIs allow organizations to become more agile, for everything to work together in a streamlined and integrated way. 

No matter how well your front-end applications are built. It is of no use if the APIs take several seconds to respond. Therefore the performance and optimization of APIs are really important. An efficient API should respond within one second.

Read also: When should you choose Django Framework

Django REST API Performance testing tools

Let us look at some prominent open source performance testing tools for Django REST API

Apache JMeter  

The Apache JMeter application is open-source software designed to test the performance on static and dynamic resources (Webservices (SOAP/REST), and Web dynamic languages such as PHP, Java, ASP.NET, Files, etc. It can be used to simulate a heavy load of API calls. You can use it to make a graphical analysis of API performance or to test your server/script/object behavior under heavy concurrent load. It is a full multithreading framework that allows concurrent sampling by many threads and simultaneous sampling of different functions by separate thread groups.

Read also: Why performance testing demands JMeter!


SoapUI is an open-source, cross-platform testing tool. It can automate functional, regression, compliance, and load testing of both SOAP and REST web services.  It comes with an easy-to-use graphical interface and supports industry-leading technologies and standards to mock and stimulate the behavior of web services. SoapUI creates test cases directly from the web method request and enables organizing test cases in test suites. It also has support for test coverage and requirements management and allows to change test setup depending on the target environment.


ApacheBench (ab) is a benchmarking tool that can load test servers by sending an arbitrary number of concurrent requests. It was designed for testing Apache installations.


cURL is a command-line tool to send and receive data using various protocols like  HTTP, HTTPS, FTP, LDAP, etc. It comes by default with most of the Linux distributions. To test a REST API using cURL, we just need to enter the command for the appropriate HTTP method in Linux.


HTTPie is an open-source CLI HTTP client that is a user-friendly cURL alternative that provides a simple HTTP command designed for painless debugging and interaction with HTTP servers, RESTful APIs, and web services.


Wrk is a tool that is similar to the traditional Apache Benchmark. It is configured and executed through a command-line tool. It consists of all the essential and powerful settings required for generating HTTP load. Wrk has several improvements over the more traditional tools. It is multi-threaded, so it makes it much easier to generate higher loads as it can take advantage of multi-core processors.wrk is the best tool when your goal is to find what is the maximum load your API can handle. 


Vegeta is an open-source command-line tool but one that takes a different approach than all the previous ones we’ve seen before. It focuses on making it easy to achieve and sustain a target rate of requests per second. It’s meant to test how a service behaves at X requests per second. This is extremely useful when you have actual data or an estimation of what your peak traffic will be, and you want to validate that your API will be able to keep up with it.

Browser API Testing Tools

  • Postman

  • REST Easy

  • REST Client

  • Advanced  REST Client

  • DHC – REST/HTTP API Client

Read also: Parameterization using JMeter in simple 7 steps

Optimization of Django REST API

The Django REST framework allows Django developers to build simple yet robust standards-based REST APIs for their applications. 

Eager loading

Let's say the database is queried once for data in a table, for example, customers. And one or more time per 'customer' inside a loop to get, say ''. This leads to a slow response from APIs. This common Django REST framework performance problem can be reduced by implementing eager loading without any major restructuring of the code. It requires the use of the underutilized select_related and prefetch_related methods on the Django ORM (and the newer Prefetch object as well) to perform what is called "eager loading".


Many times we call the same queries via APIs to fetch data. If data is not changing rapidly, we can cache the QuerySet which is returned by the particular query. Caching systems generate a hash of SQL query and map them to the cached results. So whenever API tries to call the model query-sets, the cached query-sets will be called.

Merge Responses

Do not provide entities the way they are structured on the backend.  Focus on balancing simplicity and complexity, and scale your API response to only what the user is intending to display. In this case, it helps to have a close relationship with the teams creating the mobile application so as your API can be augmented to their specific needs.

Database access optimization

APIs mainly return data retrieved from the database, and hence speeding up the database access time can bring a noticeable change in APIs response time. Various database access optimization techniques that can be adopted are: 

  • Retrieve everything at once if yll need itou know you wi

  • Don’t retrieve things you don’t need

  • Use foreign key values directly

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