this post was submitted on 12 Feb 2026
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libre

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A comm dedicated to the fight for free software with an anti-capitalist perspective.

The struggle for libre computing cannot be disentangled from other forms of socialist reform. One must be willing to reject proprietary software as fiercely as they would reject capitalism. Luckily, we are not alone.

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[–] aanes_appreciator@hexbear.net 4 points 2 weeks ago (2 children)

python being the home for AI is the cherry on the shit cake. Every time I'm forced to interact with python my mental faculties are degraded beyond repair

[–] someone@hexbear.net 1 points 2 weeks ago

I've spent too many decades with C and its cousins to wrap my brain around Python. These days I'm pretty much just using Go, with a little C++ for microcontroller-powered projects.

[–] invalidusernamelol@hexbear.net 1 points 2 weeks ago (1 children)

If you read the thread, there's a large amount of pushback. Overall I'd say the community is neutral on AI with most people actively hating it when people use it for actually submitting PRs or drafting PEPs.

Also I don't think the language itself has much to do with AI since they still don't allow core devs to use AI.

[–] aanes_appreciator@hexbear.net 2 points 2 weeks ago (1 children)

it's more that I loathe that Python has boomed in popularity off the back of AI because I've grown to find it more annoying to hse than anything else.

A lot of the reason for AI being so heavily coupled with Python probably comes from Tensorflow when Google was starting to push AI for image classification stuff years ago. And that was more to do with Python being popular for mathematical programming and visualization over closed-source crap like R.

[–] invalidusernamelol@hexbear.net 1 points 2 weeks ago

I just really like it as a glue language. It's super easy to build tooling in it that's easy for users and developers to use. I will say, without the addition and rapid expansion of the typing system it would be really awful to use.

Never had a slicker auto-documentation experience than with Python code that's properly hinted. Those hints are also specifically part of the code too. They aren't resolved at runtime any more either, which means you can use them to store doc/build code that runs separately from your main code.

My best experience with this was using annotations (in a similar way to pydantic) to model out a complicated schema. Wrote something that traversed the dataspace and generated hinted code, then I implemented the hint classes and was able to use them to rebuild the original schema. With the nice side effect that the objects could now be used to lint and interaction with the database and implement all the program logic.

I dunno, I hear a lot of people complaining, but the Python data model is just really slick to use in all my experience and I always find myself coming back to it the second I have to build an API that has to touch more than one thing.