On prem beats the heck out of github post Microsoft though... At least you know how to get it working again when someone breaks it. These days with github you expect a weekly 500, a rainbow unicorn error, build failures due to unavailable errors, etc. Last I checked the third party tracker github services were barely pushing one 9 of reliability.
"Chinese repos" is a very charitable interpretation of the Google drive links they used to distribute the os. It seemed like it was on the free plan too, it often didn't work because it tripped the maximum downloads per month limit.
As nice as it looks, I have a lot of trouble believing the "we have magic money, it's free because that's good for business" logic.
PDFgear is free of charge, and we don’t generate income through any hidden means. We Do NOT misuse or sell user data and we Do Not display ads. Here’s how we keep operations running:
We’ve secured investment to cover operational costs, including team expenses and technology like the ChatGPT API. We’re also experienced in optimizing technology usage to manage costs more effectively.
> even a 1 minute compile time is dwarfed by the time it takes to write and reason about code, run tests, work with version control, etc.
You are far from the embedded world if you think 1 minute here or there is long. I have been involved with many projects that take hours to build, usually caused by hardware generation (fpga hdl builds) or poor cross compiling support (custom/complex toolchain requirements). These days I can keep most of the custom shenanigans in the 1hr ballpark by throwing more compute at a very heavy emulator (to fully emulate the architecture) but that's still pretty painful. One day I'll find a way to use the zig toolchain for cross compiles but it gets thrown off by some of the c macro or custom resource embedding nonsense.
Edit: missed some context on lazy first read so ignore the snark above.
I've used them as a quick way to get rootless configured base images. Not sure if official repos provide those now, but it used to be a big hassle to get things like postgres images running without root in their containers. Although I often had to read through their dockerfiles to figure out the uid setup, where configs live, etc because they were not consistent between the various bitnami images.
If you really want the 80 col experience, I think that was the fortran 77 default. You'd even get compiler errors if you try to exceed it. Of course there were flags to increase the line length limit but don't tell your colleagues.
F# has been a third class citizen for a long time... Last I heard the entire f# team was ~10 people. Pretty sure "find references" still doesn't work across c# and f# (if you call a c# method from f# or vise versa). That also means symbol renames don't work correctly.
Side note, if you're a lazygit fan, consider using gitui as an alternative. Feature wise they're pretty similar but gitui is much faster and I find it easier to use.
I wish setup.py was actually on the way out, but sadly, it's the only straightforward way to handle packages that use cython or interop. In these cases, libraries use setup.py to compile the dll/so/dylib at install time. Naturally this is a bit of nightmare fuel since installing gets arbitrary code execution privileges but there's no real standard for privileges in python package installs.
I guess they abandoned the python superset idea? I followed them for a bit when they first publicly launched and they said "don't worry, we'll be a real python superset soon" and the biggest omission was no support for classes. A few years later, it looks to be missing the same set of python features but added a lot of their own custom language features.
That costs money to maintain, even if it's just a few bucks a month. I've seen plenty of Chinese companies using mega/gdrive/etc just because it's free. I used to think it was just cheapness, but depending on the company it can be a huge hassle to set up recurring small bill items. At my current company for example, it's much easier to pay $5-10k once than pay $5/mo.
The tol palettes are the best looking colorblind friendly palettes to me. Most of the others get complaints from non colorblind users about looking bad/desaturated.
It sounds like you're trying to use these llms as oracles, which is going to cause you a lot of frustration. I've found almost all of them now excel at imitating a junior dev or a drunk PhD student. For example the other day I was looking at acoustic sensor data and I ran it down the trail of "what are some ways to look for repeating patterns like xyz" and 10 minutes later I had a mostly working proof of concept for a 2nd order spectrogram that reasonably dealt with spectral leakage and a half working mel spectrum fingerprint idea. Those are all things I was thinking about myself, so I was able to guide it to a mostly working prototype in very little time. But doing it myself from zero would've taken at least a couple of hours.
But truthfully 90% of work related programming is not problem solving, it's implementing business logic. And dealing with poor, ever changing customer specs. Which an llm will not help with.
I'll just pitch in as someone who's worked with several 40+ year old codebases and 3+ year old perl, the perl code is significantly harder to maintain. The language lends itself to unreadable levels of terseness and abuse of regex. Unless you use perl every day, the amount of time trying to understand the syntax vs the code logic is skewed too heavily towards obscure syntax. Even the oldest fortran/c is much easier to work with.
Except maybe arithmetic gotos designed to minimize the number of functions. Those are straight evil and I'm glad no modern language supports them.
In the real world, for web things, people use django or fastapi. I'd suggest picking a project with lots of stackoverflow questions and poking around their docs to see which makes you the most comfortable. Personally I tend to favor litestar these days since it has good docs and issues don't sit around for years waiting on one dude to merge prs (fastapi) and it's a lot nicer than django (and I hate django docs).
Flask/quart are painful to work with due to horrible documentation in my experience, but they're popular too. Quart is just an async rewrite of flask by the same owners.
For papers sometimes you need to hit a page count to make your sponsor/advisor/conference happy. I've been told "this is a great paper but can you pad it out to 12pgs?", maybe that happened here as well.
Nodejs/js runtimes in general get a lot of development effort to make the runtimes fast from Google et al. It's the default web language so there's a ton of effort put into optimizing the runtime. Python on the other hand is mostly a hacker/data science language that interops well with c, so there's not much incentive to make the base runtime fast. The rare times a company cares about python interpreter speed, they've built their own runtime for python instead.
I don't honestly think anyone can remember bash array syntax if they take a 2 week break. It's the kind of arcane nonsense that LLMs are perfect for. The only downside is if the fancy autocomplete model messes it up, we're gonna be in bad shape when Steve retires cause half the internet will be an ouroboros of ai generated garbage.