Node.js vs Python: Choosing the Right Technology for Your Project

A back-end programming language forms the backbone of every web application. But it is necessary to choose the proper technology for custom web app development services to generate the desired outcomes and meet the project's business and technical objectives.

By contrasting back-end programming languages, we can obtain detailed insights into their advantages, limitations, and technical capabilities as well as their background. In this way, a Python vs Node.js comparison can provide CTOs and business owners with food for thought since it involves the two most popular back-end technologies in the world. 

Node.js vs Python: Brief Overview

Both Node.js and Python are extensively utilized in creating web applications for industry-leading companies and less mature enterprises. Although the technologies were created to reach different purposes, they remain one of the most widespread options for software developers.

The latest Stackoverflow Developer Survey indicates that 42.73% of professional developers choose Node.js as the primary web technology. It is worth mentioning that JavaScript is ranked number one as the most popular programming language. This is crucial for our overview since Node.js is actually a web framework built on Google's JavaScript engine V8 that is also used inside the Chrome browser. 

As for Python, roughly 45.32% of Stackoverflow respondents use this technology in their daily work. The TIOBE index indicates that Python surpassed all other rivaled for the first time as of June 2022 and is still on top of the list in July 2023. The language is highly popular among those learning to code and professional developers as well.

But all this is just general information regarding popularity. Let's delve into the topic and focus on the technical features which can make Python vs Node.js comparison more valid. We'll start with a quick summary of the essential characteristics of each back-end technology.

What Is Node.js?

Node.js is an open-source runtime environment built on top of the above-mentioned JavaScript language called V8. It enables developers to run pieces of JS code outside of the browser and unite the front- and back-end scripts of the app as a single tech stack. When you use JavaScript both on front-end and back-end sides, your app is called an isomorphic JavaScript application.

Node.js is primarily used to create HTTP servers, web crawlers, shell scripts, and to create automated tests. Despite the general-purpose nature of Node.js, it's almost never used for machine learning and data analysis – mostly because it's believed that Python is more suitable for that kind of things and has mature tooling for that.

What Is Python?

Just like Node.js, it can be used to create HTTP servers, web crawlers, shell scripts, and automated QA testing. And, moreover, it's number 1 solution when you need machine learning, data science, math, etc. No other environment has such convenient and developed tools for that.

Now that we've summarized the essence of Python and Node.js technologies let's move on to highlighting their technical peculiarities.

Node.js vs Python: Performance and Speed

Not so long ago, there was a huge gap between Python and Node performance and how their interpreters worked. Node.js was inherently single-threaded but non-blocking (asynchronous). That means that it was suitable for tasks when you needed to handle many clients in parallel, but with a small amount of CPU work – that's what a generic HTTP server does, maintaining numerous users simultaneously and passing the job to the database as soon as possible. But if you had massive calculations on the CPU, you would have problems.

Python worked differently. It had no non-blocking APIs; it supported multithreading instead. Due to the garbage collector issues in the most used Python interpreter, CPython, multithreading was going poorly. Some other interpreters tried to resolve the problem (e.g., PyPy). Also, there were attempts to introduce "better" threads called "green threads". All solutions had their own problems.

But these days are in the past. Today, Node.js has threads support (via the so-called worker threads). And Python didn't stand still and now moves towards native asynchronous APIs support (e.g., asyncio).

In terms of Node js and Python speed, both are generally slower than comparable C++ code. When you need to do some tough math, you actually want to delegate it to C++ code, and both Node.js and Python give you that opportunity. For example, that's how Tensorflow for Python works: it delegates its work to C++ code because Python is slow for that sort of things.

Node.js vs Python: Backward Compatibility

Imagine the following situation: some library you use gets updated and adds a new feature you really waited for. You change the package version, run your package manager… and it won't work! It turns out that the package requires a newer interpreter version. "Ok", you update the interpreter version. Now it's ok, the package works, but there is another problem: everything else stopped working, as it doesn't support the shiny new version of the interpreter. This is what we call a dependency hell.

What about backward compatibility in Node.js? It's simply great. JavaScript by itself is very conservative, as, in browsers, we need to support sites that have been written tens of years ago. Node.js is also outstanding, it's uncommon to find an API that gets broken in the next version.

And what about Python? Well, Python 3 minor versions are pretty fine at keeping backward compatibility. But we still remember that billion-dollar mistake in Python 2 to Python 3 update. It's hard to say how many thousands of hours of human lives were spent in vain updating almost every package to support Python 3, and it's still going! Many codebases are bound to Python 2 legacy code forever. Though there is Six, which is a Python 2 and 3 compatibility library, that helps to solve some of these problems.

Node.js vs Python: Extensibility

To create powerful apps, programming languages and environments need to go beyond standard functionality and extend their capabilities easily. In this way, it is possible to define the strong and weak sides of Python vs Node js for web development and application delivery. 

Node.js adds new functionalities for easier front-end development, project management, unit testing, and data migration. Besides, it can be paired with web development frameworks such as Meteor and Express. This helps to leverage a vast number of ready-made tools that streamlines the development process.

Python's extensibility is comparable to that of Node.js. It relies on powerful libraries and frameworks to leverage additional features. Frameworks like Django, Flask, and FastAPI are extensively used by developers in combo with Python.

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Node.js vs Python: Libraries and Tools

Libraries and tools assist developers in completing non-trivial tasks without wasting their time on manual work. They solve common problems that are relevant for the majority of projects and give more freedom and flexibility to integrate a ready-made piece of code instead of recreating it from scratch again and again.

Node.js relies on a full-fledged ecosystem of tools and libraries called Node Package Manager (NPM). This repository stores one of the largest collections of open-source scripts, libraries, and packages. As for the documentation, contributors ensure that it is well-written and self-exhaustive, which facilitates a fast learning curve for users.

As for Python, it has a mature collection of libraries and development tools, which is managed by Pip ("Pip Installs Packages"). It allows developers to deploy any library without roadblocks, thanks to well-documented procedures.

There is an advantage of Python vs Node.js for back-end development: it has a well-established toolchain. You have one package to make SQL requests (sqlalchemy), one package to lint your code (Black), and one package to type-check your code (mypy). All remain the same over years.

When it comes to Node.js, its third-party libraries are… ugh... short-living. There is no one and only library to make SQL requests, no single code style checker (ESLint is commonly used, but it's too configurable up to complete fragmentation over community), not even a Django analog, etc. Every year there is a new package to "kill" its predecessors, and it's never-ending.

One thing to mention is that Node.js, despite its constant wars, has managed to migrate its community to static-type checking via TypeScript. Every decent package has TypeScript type definitions nowadays. Ten years ago, there was no TypeScript, and now it's everywhere. Python added type-checks almost simultaneously with TypeScript appearance and still hasn't managed to take over the community – Python developers still prefer non-type-safe code.

Node.js vs Python: Learning Curve and Syntax

Python is known for its simple syntax you can learn in one afternoon. As most of its code is synchronous, it's also very easy to understand what's going on in the code. Unlike Node.js, Python has established must-have tools that are well-known and easy to use. That's good if you're starting a project involving junior developers.

In contrast, JavaScript, despite its simple syntax, is notorious for its trademark asynchronous execution order, which almost always appears to be a huge problem when learning JavaScript. Node.js lack of must-have and well-known tooling also doesn't add points. It's almost always a pain to choose a library stack for every Node.js project.

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Node.js vs Python: Community

Peer support from developers or users with different levels of experience helps to simplify the work with the chosen technology. Judging by the timeline, Python is a bit older than Node.js, which can pose slight differences in the size of the documentation ecosystem. On the other hand, both the technologies are open-source and free of charge, which welcomes new and existing users to contribute to a preferred option.

Node.js has accumulated a large army of supporters and contributors, which makes it easy to resolve upcoming issues. Besides, businesses can have access to vast pools of international Node.js talent. The major issue in this regard is a scarcity of experienced senior developers with deep niche expertise.

As for Python, its community is growing by giant leaps despite the technology's age. A fast learning curve and ease of use encourage recent graduates and non-technical people to try their skills in Python development every day.

If you are hiring a developer at your company, you can always check out Python interview questions to make your hiring process easier. Plus, you may check out the advice on recruiting software engineers from Upsilon's experienced team.

Node.js vs Python: Use Cases

Node.js and Python paths go in different directions here as with many previously mentioned criteria. Unlike JS-based tools, Python is a universal and versatile programming language. On the other hand, Node.js peculiarities make it a preferred tool for numerous modern-day types of applications. Let's have a closer look at them.

‍Node.js is one of the best options for:

• high-load web apps;
• real-time apps (streaming, video conference, collaboration);
• full-stack applications;
• automated testing.

As experts in Python development services, our team is fully aware of the best use cases for this programming language. Python supports a wide range of apps, including:

• web servers;
• data science apps (AI and ML systems neural networks, image processing software, etc.);
• ETL pipelines;
• web crawlers;
• automated testing.

TLDR: Node.js or Python

So what to choose: Node.js or Python for back-end development? Here are our considerations regarding the tech stack (not financial advice):

Choose Node.js:

• when you need both front-end and back-end: having a single language for both environments will serve you good;
• when you have to serve hundreds and thousands of users simultaneously, due to its asynchronous nature it will make it less painful than using Python;
• if your project is going to grow big: static typing with TypeScript and chic backward compatibility will definitely help you.

Choose Python:

• when you need machine learning or data science, no one would beat Python here anytime soon;
• if your application involves complex business logic, as with Python it is easier to understand;
• if you want a simple setup: choosing the right stack in Python isn't as hard as in Node.js;
• if you want to be a real programmer, everybody knows that JavaScript programmers aren't real programmers (you simply can't use Python if you don't believe that, otherwise you would simply choose Node.js and not give a damn about a thing).

Is Python better than Node.js or vice versa? The choice of the right server-side technology for back-end development should reside on the needs and goals of a particular project. It is a good idea to list requirements and identify the right tools to implement them. If you have more questions on the topic, feel free to contact us, Upsilon will be glad to assist!