ericfrederich

... And the tax code written in Python

My first thought was this must have something to do with the development momentum around the PS5 but that apparently runs FreeBSD not OpenBSD.

So NVidia Shield Pro has been sold out everywhere for months and now used ones are selling for $500.

The price was $200, now there was news of a price increase to $300. This does seem to be the case, but does a price increase of something that's sold out even mean anything? Not sure if NVidia even confirmed they're still producing it.

The NVidia Shield Pro was the go-to device which supported all the codecs. Notably the ones that Apple TV didn't support was uncompressed Dolby Atmos if I remember correctly.

Any idea if this new Apple TV 4K supports uncompressed audio for 4k Blu-Ray rips (i.e. remux's) for Plex or JellyFin?

I thought that Coolify had centralized auth.

Yeah, I've been using git for nearly 20 years. I still rely on `git gui`. It's my crutch. I know you can do all of that in a terminal, but staging different hunks (or individual lines) is super easy.

Glad they got a touchscreen but would really like to see a convertible/2-in-1

> How is C meaningfully more accessible than rust

In an ecosystem where the primary implementation of the language is in C and nearly all native extensions are written in C do you really not know the answer to that?

I don't see any meaningful speedup. The 10x claims are not reproducible. He's also comparing it to the much older style of requirements.txt projects and not a poetry project with a lockfile.

I detailed this in another comment but pip (via requirements.txt): 8.1s, poetry: 3.7s, uv: 2.1s.

Not even 10x against pip and certainly not against poetry.

The 10x performance wasn't mentioned in the article at all except the title.

I watched the video and he does mention it going from 30s to 3s when switching from a requirements.txt approach to a uv based approach. No comparison was done against poetry.

I am unable to reproduce these results.

I just copied his dependencies from the pyproject.toml file into a new poetry project. I ran `poetry install` from within Docker (to avoid using my local cache) `docker run --rm -it -v `pwd`:/work python:3.13 /bin/bash` and it took 3.7s

I did the same with an empty repo and a requirements.txt file and it took 8.1s.

I also did through `uv` and it took 2.1s.

Better performance?, sure. A lot better performence?, I can't say that with the numbers I got. 10x performance?... absolutely not.

Also, this isn't a major part of anybody's workflow. Docker builds happen typically on release. Maybe when running tests during CI/CD after the majority of work has been done locally.

Correct. There better be a damn good reason to add another language to the ecosystem other than it's that particular developer's new favorite language.

Is there anything being done in uv that couldn't be done in Python?

Yes, it's a mess (New: now with Rust!)