I’ve been mostly a poetry guy but have tested out uv a bit lately. Two main advantages I see are being able to install Python (I relied on pyenv before) and it’s waaay faster at solving/installing dependencies.

In VS code these should work through the Remote-Containers flow, just like they do through Remote-SSH.

Hmm, I just re-read the blog post and GitHub where I thought I read that and I think I was mistaken…

Poetry support is on their roadmap!

It’s not a dealbreaker for me but I feel your pain. Getting everything organized in Gitlab is a pleasure.

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I read it as sarcasm

I personally also put Pydantic on the S tier.

Also, I use (geo)pandas on a regular basis and when it comes to geometric operations Shapely is an amazing library.

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You could package it and install with pipx

I’ve had a particularly difficult time with CUDA/Pytorch in WSL. Also with Windows not reclaiming memory…

But don’t get me wrong, WSL has helped a lot when I’ve needed to use Windows at work.

In my experience:

• No lockfile, and using the third party conda-lock is clunky
• Painfully slow solver, although the libmamba solver came to the rescue
• Conda-forge can lag behind pypi by weeks, depending on the package

Interesting, but if I have to use Windows then I would consider Conda depending on my dependency situation.

I don’t particularly like Conda, or Windows, but what I like even less is manually finding wheels for my project. For something like GDAL, I wouldn’t even try on Windows without Conda. I think it’s also easy for a beginner to get up and running with this setup.

My preferred setup is pyenv on Linux with poetry :)

As a 4 day tech worker, 1 day community gardener, I can vouch for the therapeutic nature!

At the old job I was using IronPython (2.7) to write Grasshopper plug-ins in the Rhino CAD software. Luckily, it was mostly responsible for kicking off Python3 and Go subprocesses.

Now, the worst I’m stuck with is 3.8 for one of our repos using PyTorch.

Kinda comes across as someone complaining about how their company implemented agile. The only thing I can relate to is long sprints around the holidays, which I don’t see as an issue.

I’ve only worked for 20-30 person companies so maybe it’s a corpo thing? The post reads like a list of red flags that would have me looking for a new job pronto.

Seems to be more a problem of shitty management than agile vs waterfall.

This will completely depend on how and what is being distributed.

For example, I used to work on an app where assets (3D models, images, etc) were appropriately diff’d during updates but the binaries were not.

Been using the flatpak, works great!

I did a small project with MircoPython on a Pi Pico. I had a very positive experience !