Mine is that the useState hook is an actual plague on the entire React ecosystem. Regardless of your opinions of React, if you wanna use something then use it right.
If you don’t prematurely optimize your code you’ll never optimize your code.
I know people are advised against premature optimization because it risks you wasting time on something that ends up unused.
But let’s be honest, once you get something into a working state will you ever be afforded the time to go back to it? Even if you are, are you really gonna choose to uproot code and do a refactor on it and potentially everything relying on it?
Rather than waiting until your hacks and workarounds run out and you absolutely have to do a refactor, I would prefer spending more time upfront to make sure it is efficient and flexible before moving on.
Async/await turns the concepts from the [CSP] (https://en.wikipedia.org/wiki/Communicating_sequential_processes) that are useful into an overcomplicated mess in every language that implements it, and golang is a prime example of how clear and intuitive an implementation aligned with CSP can be without requiring arcane typing and language infrastructure that comes with async/await approaches.
The
unlesskeyword is an abominationx = "I disagree." y = false puts x unless yI miss it when writing python.
I’ve talked about it before, but I really hate PDFs. Specifically the things PDFs are used for. If you aren’t planning to print something and will only ever look at it on a screen, HTML is better. It’s so frustrating when you’re going to a website, you know, a thing that serves content in HTML, and then some piece of information is in a PDF.
My masochistic tendencies brought me back to say:
One reason python is a great language is that most LLMs are particularly good with it
I just got out of an interview where they pretty much told me they will ask me to vibe coded the tool they’re working on. LLMs do not make your code faster, and you are not more productive using it. I will never change my mind. We coded for 70+ years without it. You’re gonna end up with some subtle hard to reproduce bugs that are intermittently reproducible, and code that is nearly unmaintainable, and nobody knows what it does or how it works.
Good luck with that.
I like local LLMs. I got to try one recently and it felt different using open ones than corporate ones.
This is the only way I would ever use one. Local, open, more ethically trained.
Object oriented programming is dogshit.
How about overrated instead of dogshit?
The overlap between those circles is not insignificant.
Linux should be forked at a pre-ai date.
This is gonna make me sound crazy, but always pass functions when possible, and use case statements for how the passed-in functions are applied.
As a simple example, imagine you want to take the average of a set of numbers. Instead of doing sum(numbers)/len(numbers), do:
Quotient_reduce(sum, lambda x,y: x+1, numbers)
then, inside the definition of quotient_reduce,
Def quotient_reduce(accumulate_by, normalize_by, list):
If accumulate_by==sum and normalize_by==(lambda x,y:x+1):
return [some efficient implementation of average]Else:
Return reduce(accumulate_by, list)/reduce(normalize_by, list)I know it must look insane, but it generalizes normalization, mean, geometric mean, etc, and on the outside there’s no taste of the horrible concrete implementation!
Apologies about formatting, I’m on my phone.
Okay, I do think this makes you sound crazy.
I’m putting my question first before I rant about this cause I think I got way more into this response than is warranted.
What problem does this design of just creating bespoke functions have that your design solves?
def mean(numbers): return efficient calculation def normalization(numbers): return efficient calculation def geometric_mean(numbers): return efficient calculationRant starts here:
With your design, every time someone wants an average of a set of numbers, you’re reimplementing the actual logic. Then if someone forgets the +1 and writes:
quotient_reduce(sum, lambda x,y: x, numbers)A bug is introduced that’s hard to spot in a review, won’t give an error, and is hard to write tests for. Turning the lambda to an enum meant to be passed around would solve a some of the accidental bugs, but keeps the interaction with the function more complicated.
I really just don’t understand why you wouldn’t just write each efficient implementation as it’s own function and call it directly.
It has to do with how you decompose problems. In the example I gave, I was trying to point out that arithmetic average, geometric average, and normalization are related problems. Consider applying this technique to something more complicated than averages: pathfinding. You could create a dozen different efficient functions, each with different considerations, but the core of the algorithm will always be the same. You can write pathfind_land(src, dest), pathfind_sea(src, dest), pathfind_air(src,dest), pathfind_sea_and_land(src,dest) etc. but it’s obviously better to write it as pathfind(src,dest, is_traversable) and select the most efficient implementation inside the function. It also allows you to use a not-optimized implementation automatically if you haven’t made an efficient implementation.
The entire modern web tech stack should be thrown in a dumpster, ignited with gasoline, and blown up with a nuke for good measure.
Rust is a fusion of the worst parts from Javascript and c++.
HTML/TeX/etc are real programming languages that just happen to be declarative as opposed to imperative.
Rust is the easiest programming language to learn.
Granted, I’m autistic, but still. I found it far more intuitive than JavaScript or Python.
Bonus: HTML and JavaScript are evil and I hate webpages that use it. Thats pretty much all of them, to be fair, but markdown websites do exist and I love them
You should not be using AI at all. https://survey.stackoverflow.co/2026/ai
