Hmm, I just re-read the blog post and GitHub where I thought I read that and I think I was mistaken…
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!
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
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I run Debian with gnome, headless and raspi and love it.
Used Ubuntu for years, also had a good time and still respect the project even though it deviated from my needs.
Sometimes I’ll boot up something new just to poke around but I’m happy sticking with Debian for the time being.
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:
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 :)
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 !
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.