Comment by tannhaeuser
13 hours ago
Do people use python for new projects apart from ML stuff which hasn't moved to all-native yet?
My experience with Python is a really bad one for professional work: it's chaotic and slow, and has by far the worst versioning and packaging story of any mainstream language, yet its proponents keep praising it in denial.
I guess Python is an ok target for agentic coding, but my god do look Claude's commit messages pretentious, with code bases quickly heading into absolute unmaintainability. At least it had found gross JS injection vectors in a Django app that really shouldn't have made it through a code review, architecture level as they were, but oh well. A mature Django app is also not a nice dev experience IMO, with tons of implicit behavior all over the place encoded in a mix of magic filenames, database naming conventions, and URL routing quickly descending into regexp hacks.
> My experience with Python is a really bad one for professional work: it's chaotic and slow, and has by far the worst versioning and packaging story of any mainstream language, yet its proponents keep praising it in denial.
Some people just don't have the experience you do, "its proponent keep praising it in denial", can we have a better level of debate, come on now.
It's the classic worse is better.
The slowest of all dynamic scripting languages. Breaking ABI's and API's left and right all the time. Not able to implement basic performance optims. Their infrastructure (pip) getting worse and worse, getting everyone to install private venv's for every app, leading to missing security updates, because updates just break everything.
People just love trouble.
I'm split on Django--it's ok but I don't love it.
I don't think it's chaotic. I won't deny it's somewhat slow however usually anything performance sensitive gets shoved in a native code extension anyway.
As for packaging, I haven't had any problems with poetry or uv. The only time I ever had issues was with Windows in corporate environments where wheels were unavailable and it was also basically impossible to get the right toolchain installed for native code. However, not being able to install a compiler is not really a Python problem
Claude Code has a setting to change the git template so it doesn't attribute itself or you can also commit manually.
Half or more of the scientific research community live and breathe Python. Granted, it's Python 3.12, as 3.13 broke most of the C API, and everything COBOL and Fortran just about ground to a halt. But new projects are spun up constantly.
3.13 broke most of the C API
3.14 broke GC
I guess these kinds of priorities are exactly why Python is not my favorite programming language and why you have tens of Python versions installed on any machine. Not to talk about the Python 2 -> 3 drama that was also about fetishising syntax and pureness over pragmatism, installed base, and respect for existing code.
Python is the new Matlab and Mathematica combined.
Not anywhere near Mathematica, but a good replacement for Matlab. From a daily user of all those.
2 replies →
> apart from ML stuff
More and more applications need to use ML these days. So Python use will only grow.
I find the cult of python is hard to shift from some people. They just can't see it.