We love Python—that much is clear.
But is it a miracle drug to remedy all your software development challenges?
No, it’s not. And if I were you, I’d be suspicious of anyone telling you otherwise.
Whether it’s building software or doing just about anything in life, it’s rare that you can apply the same solution to every problem.
Each software project comes with its own unique set of needs and requirements. What works for one may not work for another at all. At STX Next, we use whatever tech stack fits a given project best.
That being said, comparisons are inevitable. After all, there are so many programming languages and frameworks to choose from that you can’t be faulted for wanting a little help in picking the one that is right for you.
Right alongside Python vs. Golang or Python vs. Java, one of the most popular queries we’ve seen lately is Node.js vs. Python. We’re gonna shed some light on that.
Read on for our in-depth look at Python and Node.js to learn their differences and similarities, strengths and weaknesses, and most importantly: which is better?
Table of contents
8. The verdict
Before we jump to specifics, we should clarify what it is we’re actually comparing.
What this key difference between Python and Node.js means is that when you write in Node.js, you use the same language for both the frontend and the backend.
Without further ado, here’s a more detailed breakdown of both choices.
Python is much friendlier to junior developers
Python, on the other hand, is very beginner-friendly, which is likely why it’s currently the most popular introductory language at U.S. Universities. Most of the mistakes junior Python developers may make in some frameworks are more forgivable and less of a blocker moving forward.
Most Python frameworks don’t require a very high skill level from the developers
A good example of that is Django, which has a mature ecosystem and allows you to write quality code fast.
Python is more universal and versatile
While it can also be used for desktop apps, thanks to Electron, the main use case for Node.js is the web. The applications of Python, however, go far beyond the web.
Python is a major contender to become the leading programming language of data science. It’s a great asset to system administrators because it allows them to easily write small, one-off scripts, at the same time providing larger sysadmin tools like Ansible.
For an example, look no further than Dropbox, one of the most common desktop apps written in Python.
Python is simpler to use, better covered, and better documented
This gives Python an edge over Node.js, even though both technologies are admittedly very fast to write in.
Node.js developers are more flexible
The ecosystem of Node.js is less opinionated
Many Node.js packages are simple, single-purpose libraries and microframeworks forcing developers to make more conscious decisions what to use and when.
This makes Node.js more demanding and requires a higher level of advancement on the developers’ side than what it takes to write code in Python on top of Django, using built-in solutions for ORM, caching abstraction, and so on.
Using the same language for whole project removes that risk from the equation. You can even share a part of the code between the front and the back. It’s a huge benefit, not having to waste time doing the same thing twice.
Okay, let’s take a breather for a quick recap before we go on with our comparison of Python and Node.js.
Here’s a visual summary of everything we’ve covered so far:
There; all caught up!
In the beginning, the language was written haphazardly, and to this day it is still struggling with issues caused by its old versions and their compatibility.
So many developers have turned to the language in such a short period of time lately that it’s pretty difficult to keep up with all the new updates and tech intricacies. See for yourself!
Comparing technologies is always a challenge, and the question of Python vs. Node.js is no different.
Here are 3 main points, each focusing on a different side of the story, that will help you make an informed decision.
Python is perfectly suited for trending technologies, especially machine learning, because:
- Python is a major player in the world of data science and offers several tried and tested libraries that support ML.
As always, the choice is yours, and it depends on what you’re trying to build.
Node.js allows you to use new technological trends earlier, though it comes with a risk: you may need to rewrite your entire project later. For long-term projects, Python is far less risky.
It’s different with Python. Significant changes are introduced slowly, sometimes incredibly so. What other way is there to call the 10-year-long support for Python 2.7?
Speed and performance
Here’s the thing about Node.js: it can’t do too many things at the same time unless you write very well in it. Both Python and Node.js only pretend to be able to do a whole lot of stuff at once, but Python applications tend to use a simpler, more traditional multiprocessing model instead of a more advanced asynchronous paradigm.
Use Node.js poorly, and you might easily end up with a slow-working, low-performance product. If your project involves a particularly time-consuming task, it’ll put all the focus there while other functionalities will lag behind.
When written correctly, your software will send information to the operating system that it needs to perform a certain function and move on, while the system works on that. But if you write that poorly, the app will wait for the system to complete that task, doing nothing else in the meantime.
For the end user, this will seem like your software is slow. Such problems notoriously occur when a lot of people use your product at the same time.
A huge benefit of Python is that some of its frameworks are specifically designed to spare you the trouble. Granted, Django will also work slowly if written poorly, but it has built-in solutions to handle high load that make it easier to prevent that outcome. That is only one of many instances when Python puts fewer technical expectations on the developers.
The main difference is that Node.js is designed to use a small number of workers. This is why it may slow down easily when some of the workers hang. However, it may also perform much better due to not wasting time on context switching between them.
The opposite approach is to use many workers. In this case, when some of them hang, the users served by the rest of them don’t suffer. The most recent Node.js releases also support worker threads, for CPU-bound workloads, though it is still an experimental feature.
Like we said before, each project is special and has its own needs. You need to understand those needs to build it successfully.
However, the most important thing is your team composition.
Do you have good Python developers? Use Python!
Do you have good Node.js developers? Use Node.js!
Some team members work on one part of the project, some on the other. Sometimes team composition is decided upfront, but needs to be changed on the go, both on the frontend and the backend.
Who you have on your team dictates both the choice of language and the choice of frameworks, above everything else.
We do get that you were hoping for a short-and-sweet takeaway to help you make your choice, so here it goes:
If you only have a group of junior developers with little experience on hand, go with Python; if your team is more skilled and accomplished, choose Node.js.
But there’s more to it than that.
Even though Node.js favors seasoned players in the software engineering game, expert developers claim that it doesn’t actually offer them a whole lot in return. Yes, they need to call upon their expertise to use Node.js effectively, but it doesn’t really matter to them which of the two technologies they pick.
So in the grand scheme of things, you could say that Python wins, because it doesn’t discriminate against junior developers.
The bottom line is what the expert developers say: at the end of the day, it doesn't make that much of a difference whether you choose Python or Node.js.
Some Python frameworks, like asyncio, allow you to work in Python the same way you would in Node.js. It’s possible to make the experience really similar if you care about it enough.
The journey may differ, but the destination can be very much the same. From a certain point of view, comparisons such as “Python vs. Node.js” are maybe just a little bit… pointless.
Why? Because it all comes down to your team.
The language and the frameworks you choose may not necessarily be better, but it won’t matter as long as you have the right people on the team.
Talk to your team members. Ask them questions.
How do they feel about the choice of language?
Would they prefer to work in Python or Node.js?
Don’t pay that much attention to tool selection; pay all the attention to team composition.
Your team is what makes or breaks your software project.
Thanks a lot for reading our article.
Since you’ve taken an interest in learning about Python vs. Node.js, why don’t you check out our comparisons of Python and other programming languages, too?
Or maybe you’re already sold on Python and would like to get started on your first Python project? If so, we have an ebook with your name on it.
Also, while Python may be our bread and butter—we are a Python Powerhouse, after all—we also have Node.js experience. We’ve used it to deliver software for clients such as Credit Rubric, Key Ingredient, or TBSeen. Click on any of those links to head over to our Portfolio for more information.
And if you have any questions or comments, feel free to drop us a line; we’ll get right back to you!