Introduction to Python and Node.js
Node.js and Python are the most popular backend development technologies. Both are constantly gaining new users - web designers and software developers - worldwide.
Regarding Python’s comparison with other languages, Guido van Rossum said:
We won’t be going deep into what Python is (check out our article All you need to know about Python), but just a quick reminder:
it is an interpreted, object-oriented, high-level programming language with dynamic semantics. Often used to build websites and software, automate tasks, and conduct data analysis.
Python is a general-purpose language, which means it can be used to create various programs and isn't specialized for any specific problems.
It is written in C, C++, and JS and has extreme power. It runs on the V8 JS runtime engine and uses event-driven, non-blocking I/O architecture. That’s why it is used for real-time apps such as chat, news feeds, web push notifications, web applications, video streaming sites, and single-page applications.
To have a complete picture, here are the critical features of Node.js and Python:
Python versus Node.js - fundamental differences
What to consider when comparing Node.js and Python?
Architecture, speed and performance, scalability, extensibility, libraries, popularity, and ease of learning. Let’s start.
Node.js uses the “Single Threaded Event Loop” architecture to handle multiple concurrent clients. It uses fewer threads and utilizes fewer resources overall, resulting in faster task execution.
The event loop is the main component that lets Node.js run blocking I/O operations in a non-blocking way. Thanks to its non-blocking nature Node.js is capable of handling thousands of concurrent connections, making it a perfect choice for real-time applications.
When there is just one thread on the surface, but at the same time, there are a bunch of auxiliary threads in the system kernel, Node.js can be utilized for extensive disk and network-based async operations. This group of threads makes the worker pool.
Python and Node.js do not directly convert their code into machine code - it compiles the code into bytecode, which is later converted to machine code using an interpreter.
Python supports multi-threading through its multithreading libraries. But you can build asynchronous and event-driven applications using modules like asyncio.
b. Speed and performance
It executes the code outside the web browser, which means that the app is more resource-efficient and performs better. Thanks to this, you can use features that cannot be used in the browser, e.g., TCP sockets.
The event-driven non-blocking architecture lets several requests be processed simultaneously, accelerating code execution. Also, single module caching is enabled in Node.js, reducing app loading time and making it more responsive.
Python is a single-flow language, and requests are processed slower than in Node.js. Python is not the best choice if your app prioritizes speed and performance or includes complex calculations.
In the Node.js case, you create a set of microservices and modules instead of creating a sizable monolithic core. Each will communicate with a lightweight mechanism and run its process. The development process is relatively flexible because you can easily add an extra microservice and module.
There is an option to scale an app - horizontally and vertically. To scale it horizontally - add new nodes to the already existing system; to scale it vertically - add extra resources to the node you have.
It is unsuitable for large projects with growing development teams as a dynamically typed language. It is a better choice for complex data-intensive tasks.
Node.js can be customized and integrated with various tools. For example, it can be combined with Babel (as a JS transcompiler) - it facilitates front-end development with an old Node version or the browser. It can also be extended with the help of built-in APIs for developing HTTP or DNS servers and with frameworks such as Express, Hapi, Meteor, Koa, Fastify, Nest, Restify, and others.
Python can be integrated with a wide range of developer tools, starting from the popular code editor Sublime Text, which offers additional editing features and syntax extensions, to cutting-edge IDEs like PyCharm from JetBrains. There is also a Robot Framework for test automation and plenty of web development frameworks such as Django, Flask, Bottle, FastAPI, Starlette, Cyclone, TurboGears, Tornado, Zope, Falcon, Pyramid, Web2Py, or CherryPy.
Libraries and packages in Node.js are managed by the Node Package Manager (NPM), one of the biggest repositories of software libraries, well documented and easy to work with. As mentioned before - this is both the advantage and disadvantage of Node.js.
As a disadvantage, the above might lead to “dependency hell”, and following Michael Jang’s definition, it is a colloquial term for the frustration of some software users who have installed software packages that have dependencies on specific versions of other software packages.
In the Node.js case, let’s imagine that there are three modules: A, B, and C. A requires B at v1.0, and C also requires B at v2.0. Now, let’s say we have to create an application that requires both modules A and C.
A package manager would need to provide a version of module B. In all other runtimes before Node.js, this is what a package manager would try to do. In short, this is dependency hell.
Python, on the other hand, relies on Pip - PyPi, which is fast, reliable, and easy to use.
When it comes to popularity, the important indication is the matter of the community around the language. And in this case, both languages have active, strong, and large communities of developers.
Both user communities have immense contributors with different levels of experience.
g. Easy of learning
Installing Node.js is simple, but it may be challenging to understand the event-driven architecture at first; it significantly impacts an app’s performance but usually takes some time to master.
Installing Python is a bit more complex than installing Node.js. If you are a Linux or Windows user, you shouldn’t have any problems installing it; if you use macOS, you will notice that Python 2.0 is already preinstalled, but you can’t use it (it will interfere with the system libraries). You have to download and use another version.
When to choose Python and when to use Node.js.
Each has its strengths and weaknesses, which we already have covered. Both languages have lots of use cases. Some tasks are made for Python due to the packages and community built around it, and some are suitable for Node.js because of the architecture and other factors.
Speaking about Node.js’s architecture because of its characteristics, it tends to be used for:
- CPU bound operations - thanks to good multi-threading support;
- I/O operations - due to non-blocking and event-driven architecture;
- real-time applications - by using libraries like socket.io
Node.js runtime makes it ideal for apps that require a persistent connection between the browser-side apps and the server. For example, a chatbot won’t work correctly if it is not connected to the server; it won’t be able to respond to customer requests. Hence, if live streaming is an essential factor in your project, you should choose Node.js.
It is worth mentioning that Node.js works on both the client and server sides. This helps to reduce the deployment time and allows the teams to maintain code during coordination easily.
To efficiently handle the interaction between a client app and a cloud server, choose Node.js.
Python is, however, heavily supported by the scientific community. It is used as a default language for popular data science training courses. The result is many packages, such as NumPy, SciPy, and Matplotlib, ideal for machine learning, data analysis and visualization, image-processing software, neural networks, and many more.
Moreover, Python supports web development with frameworks like Django and Flask - you can create desktop and business applications and even games with Python. An interesting fact is that Reddit was rewritten in 2005 using Python (originally, it was written using Lisp).
Python is an excellent choice if your app focuses on data analysis or uses tools specifically for scientists. Also, thanks to its uncomplicated syntax, giants like Facebook and Google use it to develop their technology.
What is better? Python or Node.js?
The answer is neither.
Both are good - it depends on what you want to use them for. We must realize that once a language works for one project does not necessarily mean it will work for another. There is no such thing as an ideal tool.
As you can see, both are used internally in web development. Node.js is focused on the server side, whereas Python is a general-purpose language created for many areas and tasks. Node.js, on the other hand, is fast, lightweight, and has full JS development. Python has a simple structure, extensive AI and ML libraries, and an active dev community.
If you do not have a lot of experience in the programming world, go with Python; if your skills are more advanced, then choose Node.js.
Thank you for reading.
If you would like to read more about Python or compare Python with other programming languages, take a look: