

Jokes aside, you create a custom Dockerfile and copy a statically compiled shell binary.
Jokes aside, you create a custom Dockerfile and copy a statically compiled shell binary.
I’m not loosely coupled at all, sir, I am married!
Synology supports docker containers. Just run jellyfin.
You need to get over the bloat of virtual environments. It’s the same as node_modules and it’s completely necessary if you want more than a single python project to live on your machine.
I personally use poetry as my dependency manager and build tool. It’s not perfect but it’s a lot better than pipenv or just rawdogging pip like a maniac. uv is the new hotness, but I haven’t tried it so can’t vouch. People seem to like it though.
JavaScript is also an interpreted language with tons of build tools. The reason to have one for python is mainly about packaging and code distribution, so same as JavaScript. If you want to distribute a program you probably don’t want to just point people to a GitHub repo, and if you want to publish a package on pypi it needs to be bundled correctly.
For ecosystem there isn’t much I can do for you, it completely depends on what you’ll be working on. Baseline you want pydantic
for parsing objects, assuming some APIs will be involved. You want black
for code formatting, flake8
for linting, pytest
for testing. If you’re gonna write your own APIs you can’t go wrong with fastapi
, which works great with pydantic. For nice console stuff there’s click
for building cli apps and rich
and textual
for console output and live console apps respectively.
People are actively trying to replace flake8 and black with feature compatible stuff written in rust but again I haven’t tried those so can’t vouch.
Coming from react you’re gonna need to pretty quickly switch gears to thinking more object oriented. You’re gonna be annoyed at how you can’t just quickly declare a deeply nested interface, that’s just how it is. The biggest change other than object oriented thinking will probably be decorators. Typescript had them experimentally and only for classes, python has them for classes and functions natively. They’re a bit tricky to wrap your mind around when you want to write your own, but not too bad. A lot of Google hits will be outdated on this front. Google specifically “decorators ParamSpec” to see how to make them properly.
Good luck in your new job, you’ll be grand!
Definitely those used to be pain points, but they do exist now so type erasure after decorator application isn’t a problem anymore, which used to be another huge one for me.
The discussion around how unpopular it was in other languages seems like such an obvious side track to me. Typing in general went out of fashion and then made a comeback when it was opt-in, why wouldn’t the same apply to exceptions? Of course I’m not wanting warnings in every func call because of a potential MemoryCorruptionError, but if a library has some set of known exceptions as a de facto part of its interface then that’s currently completely unknown to me and my static type checker.
One kinda bad example is playwright. Almost all playwright functions have the chance to raise a TimeoutError, but even if you know this you’ll probably shoot yourself in the foot at least once because it’s not the built-in TimeoutError, oh no, it’s a custom implementation from the library. If you try to simply try...except TimeoutError:
, the exception will blow right by you and crash your script, you’ve got to import the correct TimeoutError.
If it was properly typed then pyright would be able to warn you that you still need to catch the other kind of TimeoutError.
It’s a bad example because like I said almost all playwright functions can raise this error so you’d get a lot of warnings, but it also demonstrates well the hidden interface problem we have right now, and it’s the most recent one that screwed me, so it’s the one I remember off the top of my head.
Yeah, they’re useful when developing, which is why it’s so frustrating when libraries don’t implement types. I’m developing and I’m trying to use a tool that supposedly fits a use case I have, but the tool didn’t come with instructions so it’s practically useless to me. I could open the tool up and look at its guts to figure it out but are you kidding me no, I’m not going back to the stone age for your tool.
All documentation is optional and ignored at runtime, that doesn’t mean you shouldn’t do it. If your library doesn’t have type hints I’m just not gonna use it, I don’t have the time to figure out what you accept or return.
My biggest pet peeve is the complete inability to annotate a set of known exceptions that a function raises in a machine readable way. The discussion about it is quite heated.
I code both typescript and python professionally, and python is almost as much of a mess, just a different kind of mess. The package manager ecosystem is all over the place, nobody is agreeing on a build system, and the type system is still unable to represent fairly simple concepts when it comes to function typing. Also tons of libraries just ignore types altogether. I love it, but as a competitor to JavaScript in the messiness department it’s not a good horse.
Don’t know why you were down dooted, that’s absolutely true and exactly how I feel, and how everyone I’ve talked to about copilot feels.
Have you tried kitty? It’s seriously nice if you can live with the occasional “oh no I sshed to a server that doesn’t have the correct terminfo files and now none of the normal terminal navigation features work”
This doesn’t really install it, though, you can’t update or permanently edit and config, set up users, or anything like that. I would guess OP wants something more like booting the ISO in a VM, allocating a thumb drive to that VM, and then installing a full system to it with a boot loader.
If I may ask, why do we want to enable tearing now? There are pages and pages across the wikis on how to fix tearing…
Again The issue on the repo. The developers recommend just using the app feature of the browsers to get similar functionality without the security concerns.
If you look at the repo, the very first line in the readme links to an issue that briefly explains why you should care.
Unmaintained software comes in two categories:
Nativefier falls in the second category and the second clause. Don’t use it.
I’m using 555 open with hyprland. No issues and I can finally suspend and resume, using the NVreg_PreserveVideoMemoryAllocations=1
module param after being unable to all year.
Imo stick to amd. I was like you, I thought the Nvidia card would be an upgrade and I thought the rumors of how bad Nvidia was had to be at least a little exaggerated, but honestly it’s a constant pita. Aside from the suspend issue I’ve had random minor system upgrades cause kernel panics and fry my boot more than once this year. That bug is still unresolved btw, their response time leaves much to be desired.
Having dockerized ollama just work is nice, but it’s not worth it, and they seem to be close to a working vulkan based runner for that anyway.
I do have nightly off-site backups, that’s true. Still, having the git repo be on the same machine doesn’t seem right to me.
That would fill the same role as watchtower I guess? I’ve previously tried to have a look at having portainer manage the docker compose stack that it’s running inside but at least back then it seemed to be a dead end and not really what portainer is meant to do. I’m not interested in moving away from docker compose at this time.
I’d be a bit concerned with having the git repo also be hosted on the machine itself. If the drives break it’s all gone. I could of course have two remotes but then pushing changes still becomes a multi step procedure.
Not always, for example this laptop has external monitors wired to the dGPU. https://wiki.archlinux.org/title/Lenovo_ThinkPad_X1_Extreme