Python Surges in Popularity. And So Does Perl (techrepublic.com) 34
Last month, Python "reached the highest ranking a programming language ever had in the TIOBE index," according to TIOBE CEO Paul Jansen.
"We thought Python couldn't grow any further, but AI code assistants let Python take yet another step forward." According to recent studies of Stanford University (Yegor Denisov-Blanch), AI code assistants such as Microsoft Copilot, Cursor or Google Gemini Code Assist are 20% more effective if used for popular programming languages. The reason for this is obvious: there is more code for these languages available to train the underlying models. This trend is visible in the TIOBE index as well, where we see a consolidation of languages at the top. Why would you start to learn a new obscure language for which no AI assistance is available? This is the modern way of saying that you don't want to learn a new language that is hardly documented and/or has too few libraries that can help you.
TIOBE's "Programming Community Index" attempts to calculate the popularity of languages using the number of skilled engineers, courses, and third-party vendors. It nows gives Python a 26.14% rating, which TechRepublic notes "is well ahead of the next two programming languages on this month's leaderboard: C++ is at 9.18% and C is 9.03%." But the first top six languages haven't changed since last year...
"We thought Python couldn't grow any further, but AI code assistants let Python take yet another step forward." According to recent studies of Stanford University (Yegor Denisov-Blanch), AI code assistants such as Microsoft Copilot, Cursor or Google Gemini Code Assist are 20% more effective if used for popular programming languages. The reason for this is obvious: there is more code for these languages available to train the underlying models. This trend is visible in the TIOBE index as well, where we see a consolidation of languages at the top. Why would you start to learn a new obscure language for which no AI assistance is available? This is the modern way of saying that you don't want to learn a new language that is hardly documented and/or has too few libraries that can help you.
TIOBE's "Programming Community Index" attempts to calculate the popularity of languages using the number of skilled engineers, courses, and third-party vendors. It nows gives Python a 26.14% rating, which TechRepublic notes "is well ahead of the next two programming languages on this month's leaderboard: C++ is at 9.18% and C is 9.03%." But the first top six languages haven't changed since last year...
- Python
- C++
- C
- Java
- C#
- JavaScript
Since August of 2024 SQL has dropped from its #7 rank down to #12 (meaning Visual Basic and Go each rise up one rank from their position a year ago, into the #7 and #8 positions).
In the last year Perl has risen from the #25 position to #9, beating out Delphi/Oracle Pascal at #10, and Fortran at #11 (last year's #10). TIOBE CEO Jansen "told TechRepublic in an email that many people were asking why Perl was becoming more popular, but he didn't have a definitive answer. He said he double-checked the underlying data and found the increase to be accurate, though the reason for the shift remains unclear."
What is (Score:1)
Re: (Score:3, Funny)
Something you don't cast before the swine.
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Great question... (Score:3)
Why would you start to learn a new obscure language for which no AI assistance is available?
Soon to be "why learn anything that isn't already in the AI model, you'll have to research it on your own".
Wasn't that a theme from the paper "Foundation", where someone was telling everyone else that all is already known and you just have to find the book it's written? And wasn't that the mark of the end of the Great Empire?
Re:Great question... (Score:4, Interesting)
Now apparently there's a substantial portion of the programming population that can't learn any language without AI assist.
I mean... (Score:1)
Perl is awesome. It doesn't hurt that they finally got their finger out of their eye and are moving forward.
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YES! Perl really shot themselves in the foot with serious consequences... Although Roku has interesting ideas and abilities it was almost an insurmountable task which made the whole situation so much worse. It would have been better as a different language from the start... and likely would have died early since a lot of talented Perl people were spent on Roku being a massive upgrade of Perl.
It's still too technical and hacky for large projects; which means that you need a team of people who are all on the
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Good point.
Just for fun yesterday I took some Java code I wrote, about 10 lines and converted it to Perl. It ended up being 1 line and easier to understand than Java. I've found the same thing with PHP--meaning Perl was shorter and easier to understand than PHP.
I was thinking about a website I worked on 30 years ago. The Perl code is still working without modification (Perl 4 to 5.38). The supporting languages have had to be modified over the years to keep going. Gotta love Perl.
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shorter and easier to understand than PHP.
To be fair so is Dostoevsky.
It is all AI driven (Score:2)
The fact is if you want to do nearly anything in AI these days at the programming level you end up using Python for it. All the API clients are supported that way.
Before taking my current gig which is of course all about AI I barely touched Python. Now it is pretty much all I do. The work is more interesting than the language even though it is an excellent language in many ways.
AI is the killer app for pytPon.
Re: (Score:2)
In the modern world, we don't choose languages based on language features. We choose them based on available libraries. Forth [wikipedia.org] is the best language, but it doesn't have NumPy bindings.
Seems unlikely (Score:1)
It seems unlikely that any language could truly "surge" in popularity in a way that matters for professionals. Sure, it could suddenly become more popular for introductory courses, web searches, new projects, etc; but the bazillions of lines of existing code in other languages are not going to suddenly change, and large code bases like the Linux kernel, Firefox, etc. are what we interact with most in our daily lives.
Re: Seems unlikely (Score:4, Insightful)
I'm doing meteorological data analysis. Want to bet what language I'm doing it in? Python. Because that's where the libraries are for the dataset I'm playing with.
Are there other libraries in other languages? Maybe. Are they anywhere near as popular? Significant doubts abound.
It's much easier to pick the same tooling as the core data you're going to use is built around. Thankfully in my case extracting the data is about all I need from Python.
Python is heavily used in data analysis, particularly from research or academic fields. Its resurgence with AI is unsurprising to me based on that.
Re: (Score:2)
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The point of a specification is to explain what "it works" means. Usually it's for when the user or recipient of the thing is different from the developer, but if the problem to be solved is complex enough then even a one-person spec can be helpful in figuring out edge cases.
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Perl? (Score:2)
The end times must be upon us.
Though, I will say it was useful when I set up my companyâ(TM)s first duct-tape-and-zip-tie CDN back in the late 90s for software downloads. All I was given was access to three distributed sun boxes that I could stash our binaries on, and run cgi scripts on Apache. I was able to redirect our paying customers to these servers and still have reasonable (but not perfect) confidence the files were hard to get for non paying customers. It used a simple token passing scheme.
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I wrote the chip implementation flow (front to back; synthesis, DFT, place-and-route, physical verification, etc.) that is used by my employer in Perl.
First iteration was circa ~2012, and it is still used everyday to this day (albeit with a LOT of updates over the years)
Screw Python and that whitespace nonsense
Was not TIOBE based on search frequency? (Score:3)
Perl is what Java wanted to be (Score:3)
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Agreed. I ran an email security company for 19 years and our product was mostly written in Perl. I use the product to this day.
Perl is still my go-to language for either quick scripts or bigger projects that don't need the speed of C or some other compiled languages.
Re: (Score:1)
I use it too... thanks, it's great!
Re: Perl is what Java wanted to be (Score:2)
Perl on Windows isn't anything at all like Perl on a Unix which isn't anything at all like Perl on VMS because it doesn't even try to abstract basic OS functions like the simplest filesystem operations. Java does, try.. for most basic OS functions. OS agnosticism was not a goal of Perl and it isn't and it most definitely was for Java and it debatably is at least for a wide swath of OS functions.
The Perl runtime is not relocatable, or hasn't been historically, and the one you're using isn't with like 99.99%
O Really (Score:2)
And here was me last night looking at my shelf of O'Reilly Perl books and wondering whether I'll ever refer to them again. I don't suppose with AI "help" available at the click of a mouse that there's much of a second hand market for them.
Python is the Eternal September of programming (Score:3)
That so many different specialisms can make use of it for data analysis without calling in a programmer, it seems to that it's largely succeeded at bringing programming to more people than ever.
I do worry that domination may lead to a broader stagnation, and a Pythonication of existing languages - C# feels like it's going down this route.
While I'm posting where Python experts may lurk; is there an 'enjoyable and effective' way of developing 'attractive' multiplatform UIs with Python yet, or does anyone know of anything being actively worked on?
IMO the better question to ask is (Score:3)
which qualities should a programming language / platform have so that it can benefit more from LLM-based tools?
I asked ChatGPT and here is how it ranked TIOBE's top 20:
Top tier -- AI-friendly (9 - 10/10)
These languages get the biggest immediate productivity boost from AI: large corpora, great tooling/IDEs, REPLs or declarative style, and stable ecosystems.
* Python (TIOBE #1) -- huge training corpus, ML ecosystem, REPL + notebooks -> excellent NL-> code and copilots.
* JavaScript (TIOBE #6) -- massive web ecosystem, short idiomatic snippets that LLMs do well at.
* C# (TIOBE #5) -- Roslyn + mature tooling give strong static-analysis signals for safe code generation and refactors.
* SQL (TIOBE #12) -- declarative queries map exceptionally well from natural language; high precision generation.
Strong tier -- Very good fit (7 - 8.9/10)
Large ecosystems and/or excellent tooling -- AI helps a lot, but either low-level detail or domain specifics require caution.
* Java (TIOBE #4) -- huge corpus + static typing reliable refactors, test generation; boilerplate can be an issue.
* C++ (TIOBE #2) -- massive codebase; templates and patterns help, but low-level UB and build/ABI complexity reduce autonomous use.
* C (TIOBE #3) -- plentiful examples, but pointer/UB and platform specifics make fully automatic changes risky.
* Go (TIOBE #8) -- simple, opinionated style and gofmt = AI produces readable, idiomatic code reliably.
* Rust (TIOBE #18) -- excellent compiler diagnostics let AI produce correct-by-construction fixes; steeper semantics but very promising.
Mid tier -- Useful but with caveats (5.5 - 6.9/10)
AI helps productivity (snippets, prototyping, migration), but domain-specific tooling, legacy idioms, or small corpora limit scope.
* Visual Basic (TIOBE #7) -- large legacy base and lots of examples; useful for migrations and automation but inconsistent modern tooling.
* Perl (TIOBE #9) -- expressive one-liners & CPAN help, but varied idioms make safe generation harder.
* Delphi / Object Pascal (TIOBE #10) -- legacy GUIs and embedded uses -- AI aids porting and snippets.
* PHP (TIOBE #15) -- huge web examples/frameworks; dynamic quirks can trip up blind generation.
* R (TIOBE #14) -- great for data tasks; AI helps plotting/analysis code but less so for large engineering systems.
* MATLAB (TIOBE #16) -- numeric/algorithm prototyping benefits from AI, smaller ecosystem for broader tooling.
Lower tier -- Niche / harder for LLMs (3.5 - 5.4/10)
Specialized domains, niche audiences, or small indexed corpora reduce immediate AI impact.
* Fortran (TIOBE #11) -- legacy scientific code -- good for modernization tasks but limited general tooling.
* Ada (TIOBE #13) -- safety-critical focus and niche community; compiler checks help, but corpus is small.
* Kotlin (TIOBE #19) -- modern language with good IDEs, but smaller training footprint vs the biggest languages.
* Scratch (TIOBE #17) -- educational/block language: AI can create lesson content, but not much production automation.
Legacy / very low-benefit tier (0 - 3.0/10)
Very context-sensitive, architecture-specific or educational-only languages where generic LLM assistance is least useful.
* Assembly language (TIOBE #20) -- highly architecture- and context-specific; AI can suggest patterns but needs deep hardware context.
would you agree with the LLM's "logic"?
TIOBE is complete nonsense (Score:2)
I'm perpetually mystified how TIOBE is considered to be in any way reputable.
It's just searching for "$LANGUAGE programming" in various engines and applying magic fudge factors.
It's not an indicator of jobs, or activity, or much of anything else really. This is especially obvious with things like Visual Basic showing up weirdly close to the top, and having large spikes, as if there were times when VB suddenly got a huge influx in demand.
VB never even transitioned to 64 bits, it's that old. VB.NET i suppose
This popularity contest is tiring... (Score:2)