alt Hacker NewsOne obvious reason is Python's extreme readability, it has often been described as being as close to executable pseudo-code as one can get.
If you're using an LLM to write code I think the rules would be
1. Use a language you know really well so you can read it easily, and add to it as needed.
2. Use a language that has a large training set so the LLM can be most efficient.
3. Use a language that is easy to read.
If your language has a small training set or you don't intend to do much addition or you don't really know any language that well or are restricted from using choice 1 for some reason, 2 and 3 move up, and python has a large training set and it is easy to read.
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Python is amazing for scripting.
Python is terrible for writing big systems.
Projects whose V1 is written in Go/Rust/C++ don't normally go out and re-write V2 in Python.
The reverse is really common.
Even many famous Python packages are now Python wrappers.
I never really understood what exactly is so readable about python. I've been developing in Python for 8 years now, and before that I was a C# developer, and I don't find Python to be that more readable.
Sure there's less ceremony, and yes, you can have your project going with just a single file, but other than that...?
My preferences are always Go first and Python if there are specific libraries that make my life easier.
Go is a simple target for LLMs as the language has changed very little and with the Jetbrains go-modern-guidelines[0] skill the LLM can use the handful of recent additions effectively
And with Python there are things like ruff and pydantic that can enforce contracts in the code.
I think this is where D language make an excellent alternative to Python for AI assisted coding [1].
1) It's a very consistent language even if you compared to the other popular languages namely Python, Rust, C++ and Go. Try to perform doubly linked list with them and compare them all [1].
2) It's probably the most "Pythonic" among the compiled language according to Walter.
3) It utilizes GC by default, you can also manage your own memory and you can hybrid.
4) It compiled fast and run fast, heck it even has built-in REPL eco-system.
5) Regarding the small training set, with recent self-distillation fine-tuning approach it should be good enough, D (actually D2 version) has been around for more than a decade [2].
[1] Looking for a Simple Doubly Linked List Implementation:
https://forum.dlang.org/thread/[email protected]...
[2] Awesome D:
> 2. Use a language that has a large training set so the LLM can be most efficient.
I seriously doubt this is really the case. From my experience coding agents just love writing bad python code. It always needs explicit instructions for example to use uv instead of raw dogging pip. There is a lot of python code out there because it is being taught as a beginner language and because of that there is necessarily a lot python code written by beginners. That's my explanation at least for bad LLM generated python code.
No, I think the argument from the article is pretty good. Use a language that has a lot of guard rails built in.
> One obvious reason is Python's extreme readability, it has often been described as being as close to executable pseudo-code as one can get.
But it's LLMs that read it not humans. At least that's the trend
> Use a language that has a large training set so the LLM can be most efficient.
It's pretty efficient with Rust.
I would assume it's important to know what's in that training set too
Because I get reliable generation out of "niche" languages already
Is it code with lots of SQL injections used in a different domain to your own?
It's maybe not good to conflate quantity with quality
c llm code is more readable as it probably trained on better code
Disagree, it's verbose, but it's full of needleslly verbose stuffs, use many _ for everything and the rest, and other opaque conventions. Not that any other dev ecosystem is free of any of these issues, but Python just don't shine much on them. If anything in term of script language, Ruby provides a far more solid ground for compact and readable exposure of ideas through something close to prosaic expression.
So in short, use Javascript /s
I think that pseudocode aspect is what makes it hard/frustrating to read for me.
I'm more of a c++/TS/etc user, so I miss braces a lot. I think a basic Python script sure it's easy to read through, but a large project starts to get quite ugh.
I am very jealous of Python's numerous built-ins though. I was looking for a JS sum function the other day and was surprised to see node.js still doesn't have a built in + you still cannot reference operator functions.
Python is locally readable. Reasoning about larger systems in Python is where things get really hard, because you have to describe how many small individually readable things interact with each other in a very limited vocabulary.