As Python’s lifetime grinds to a halt, a hot new competitor is emerging

Woman with hat covering her face in front of sunset
Woman with hat covering her face in front of sunset
If Julia is still a mystery to you, don’t worry. Photo by Julia Caesar on Unsplash

Don’t get me wrong. Python’s popularity is still backed by a rock-solid community of computer scientists, data scientists and AI specialists.

But if you’ve ever been at a dinner table with these people, you also know how much they rant about the weaknesses of Python. From being slow to requiring excessive testing, to producing runtime errors despite prior testing — there’s enough to be pissed off about.

Which is why more and more programmers are adopting other languages — the top players being Julia, Go, and Rust. …

And why you might consider switching if you’re dealing with front-end web, or back-end Node development

Woman sitting in front of laptop gazing upwards
Woman sitting in front of laptop gazing upwards
Python and TypeScript are among the most-loved programming languages. Photo by Obi Onyeador on Unsplash

Python is my bread-and-butter, and I love it. Even though I’ve got some points of criticism against the language, I strongly recommend it for anybody starting out in data science. More experienced people in the field tend to be Python-evangelists anyway.

However, this doesn’t mean that you can’t challenge the limits in your field from time to time, for example by exploring a different programming paradigm or a new language.

The list of Python’s competitors is long: Rust, Go, Scala, Haskell, Julia, Swift, C++, Java, and R all find an entry on it. …

When it comes to code, many scientists lack rigor. That carelessness could have disastrous effects on our ability to achieve reliable breakthroughs in a range of fields.

Man sitting in front of laptop with headphones on
Man sitting in front of laptop with headphones on
Software in science can be frustratingly messy. Photo by Wes Hicks on Unsplash

Science is messy. That’s why there’s some truth to the cliché of the scatterbrained professor. Not all scientists are like that, of course, but new theories and ideas are often birthed from downright chaos.

At the same time, many scientists are very clean and diligent when it comes to everyday tasks like keeping their desks tidy or their email inboxes uncluttered. This may sound paradoxical, but it really isn’t. All that mental mess needs to be managed somehow, and orderliness is a good strategy for keeping it contained within clear boundaries.

They set those boundaries by insisting on tidiness for anything that’s related to, but not directly part of, the mess that is science. That includes emails or the classes they teach, but also the experimental apparatuses they employ and any other tools they’re using. …


Rhea Moutafis

Pursuing my PhD on Dark Matter physics. Lover of art, music and beautiful things. Queer in every sense.

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