NodeJS vs Python: Choosing the Best Technology to Develop Back-End of Your Web App
We take courage in both hands and claim that one of these technologies is winning it. Which one?
Thank you to Oleg Romanyuk for coauthoring this article.
Node.js and Python are among the most popular technologies for back-end development. The rule has it that there is no better or worse programming language, that everything depends on the preferences of a particular developer. Yet, in this article, I am going to take my courage in both hands and claim that one of these technologies – NodeJS vs Python 3 – is winning it. Which one? Let’s see.
The comparison criteria that I am going to consider are:
- Brief overview
- Learning curve
- Apps it is best suitable for
Before I jump into detailed side-by-side comparison, you can have a look at the infographics to get some general understanding.
Python is an open-sourced high-level programming language. It was first released in 1991 by Guido van Rossum. The latest version is Python 3.8, and it was released in October 2019. Yet, Python 3.7 is still more popular.
Python mainly runs on Google’s App Engine. Also developed by Google, the App Engine gives an opportunity to develop web apps with Python and benefit from numerous libraries and tools that the best Python developers use.
NodeJS vs Python: 0 – 0
Node.js is designed as an event-driven environment, which enables asynchronous input/output. A certain process is called as soon as the respective event occurs, which means that no process blocks the thread. The event-driven architecture of Node.js is perfectly suitable for the development of chat applications and web games.
By contrast, Python is not designed that way. It does have the possibility of building an asynchronous and event-driven app with the help of special tools. Such a module as asyncio makes it possible to write asynchronous code in Python as it would be done in Node.js. Yet, this library is not built in most Python frameworks, and in any case, it requires some additional hustle.
The event-driven architecture brings Node.js the first point.
NodeJS vs Python: 1 – 0
Since Node.js is faster, it wins a point in terms of Node JS vs Python performance and speed.
NodeJS vs Python: 2 – 0
Python’s syntax is often called the greatest advantage of it. While coding in Python, software developers need to write fewer code lines than if they were coding in Node.js. The syntax is very simple, and it is free of curly brackets. Respectively, the code is much easier to read and debug. In fact, Python code is so readable that it can be understood by clients with some technical background. But again, it depends on personal preferences.
Only because Python syntax is easier to understand and to learn for beginners than the syntax of Node.js, Python wins a point here.
NodeJS vs Python: 2 – 1
For the app to be scalable, multithreading needs to be enabled. Yet, Python does not support multithreading because it uses Global Interpreter Lock (GIL). Although Python has libs for multithreading, it is not “true” multithreading. Even if you have multiple threads, GIL does not let Python interpreter perform a few tasks simultaneously but makes it run only one thread at a time. Python has to use GIL even though it negatively affects performance because Python’s memory management is not thread-safe. Furthermore, Python is dynamically-typed. Yet, dynamically-typed languages are not suitable for large projects with the growing development team. When growing, the system gradually becomes excessively complex and difficult to maintain.
Evidently, Python somewhat loses to Node.js in terms of scalability.
NodeJS vs Python: 3 – 1
Node.js can be easily customized, extended, and integrated with various tools. It can be extended with the help of built-in APIs for developing HTTP or DNS servers. It can be integrated with Babel – a JS compiler, which will facilitate front-end development with old versions of Node or browser. Jasmine will be helpful for unit-testing, and Log.io will be helpful for project monitoring and troubleshooting. For data migration, process management, and module bundling, you can use Migrat, PM2, and Webpack. Moreover, Node.js can be extended with such frameworks as Express, Hapi, Meteor, Koa, Fastify, Nest, Restify, and others.
Python was introduced in 1991, and throughout its history, a lot of development tools and frameworks have been created. For example, Python can be integrated with a popular code editor Sublime Text, which offers some additional editing features and syntax extensions. For test automation, there is Robot Framework. There are also a few powerful web development frameworks, such as Django, Flask, Pyramid, Web2Py, or CherryPy.
So, both networks are easily extensible, and both win a point.
Node JS vs Python: 4 – 2
In Node.js, libraries and packages are managed by NPM – the Node Package Manager. It is one of the biggest repositories of software libraries. NPM is fast, well-documented, and easy to learn to work with.
In Python, the management of libraries and packages is ensured by Pip, which stands for “Pip installs Python”. Pip is fast, reliable, and understandable, so developers find it easy to learn to work with it.
Node JS vs Python: 5 – 3
Python is full-stack, so it can be used both for back-end and front-end development. Similarly to Node.js, Python is cross-platform, so, for example, a Python program written on Mac will run on Linux. Both Mac and Linux have Python pre-installed, but on Windows, you should install the Python interpreter yourself. Yet, while Python is great for web and desktop development, it is rather weak at mobile computing. Therefore, mobile applications are generally not written in Python. As for IoT and AI solutions, the popularity of Python as a language for writing these is growing.
In terms of universality, Node.js and Python go nose to nose. It would be fair to grant each with a point.
Node JS vs Python: 6 – 4
Both Python and Node.js are easy to learn. You cannot answer objectively which one is simpler because it also is a matter of personal preference. So, once again both technologies receive a point.
Node JS vs Python: 7 – 5
Node.js community is large and active. It is a mature open-sourced language with a huge user community. Ten years after the release were sufficient for the developers from all over the world to grow to love this technology. As a business owner, you can easily find Node.js developers. As a developer, you can always rely on peer support.
Python is somewhat older than Node.js, and it is also open-sourced. The user community has an immense number of contributors with a different level of experience. Once again, should you be a business owner or a developer, you benefit from the large-sized community.
Both Python and Node.js have great communities, so both receive a point.
Node JS vs Python: 8 – 6
Apps it is best suitable for
Due to its event-based architecture, Node.js perfectly suits applications that have numerous concurrent requests, heavy client-side rendering, or frequent shuffling of data from a client to a server. The examples of such apps are IoT solutions, real-time chatbots and messengers, complex single-page apps. Node.js also works well for developing real-time collaboration services or streaming platforms. However, Node.js is not the best option for developing applications that require a lot of CPU resources.
Python is suitable for the development of both small and large projects. It can be used for data science apps, which involve data analysis and visualization, for voice and face recognition systems, image-processing software, neural networks, and machine learning systems. Python can also be used for the development of 3D modeling software and games.
Both technologies let you develop a wide range of apps. Which one is more suitable depends exclusively on what you need. Therefore, choosing a better one does not have any sense. Here, neither technology gets a point because they do not compete.
Node JS vs Python: 8 – 6
To Wrap Up
Do you remember that I said I would prove that one technology is better than the other? Good! But you also should remember that each software project has its needs and requirements.
A language that works for one project may not work for another project at all.