whats long, brown, and sticky? a stick.
what’s long, blue, and sticky? a blue stick.
ive found kids live this due to the misdirection and then doubling down on it.
whats long, brown, and sticky? a stick.
what’s long, blue, and sticky? a blue stick.
ive found kids live this due to the misdirection and then doubling down on it.
it meant to be yes. unfortunately having more stuff baked in can lead to more issues than good on some systems. kde neon is meant to be kubuntu with more stuff baked in but ime it causes more issues than good.
I totally get it. in terms of ease of use and setup, if you ever do give it another go, try fedora. I had similar gaming issues with multiple Linux distros, gave fedora a go, and everything worked pretty much right out of the box, I was super impressed. ymmv ofc but keep it in mind for the future!
beautiful post, thank you!! I’ve been using the same traveling USB for ages at this point and will probably upgrade soon, this research is super useful
mine in PA. most of them are sent to a name I don’t know anyone by…
a kilo of cocaine would probably run ya like 50k depending on where you are lol
idk how weird this is in terms of everything else in this thread, but peanut butter and pickles on toast is great
only time I ever bought gift cards was when I worked at restaurant. each Christmas theyd give us employees 20% off gift cards. id buy a bunch of them (usually like 500$ worth). then when a customer paid in cash, I’d pay with my gift card, and pocket the change. I always told the customer what I was doing and made sure it was ok with them, it was a chain so most people were just kinda thrilled they could help me beat the system.
pretty certain their just confused why someone would say there’s not a niche for a chat client. chat clients always have, and always will exist.
the hero we need
indeed. completely different writing style than the rest of OPs posts/comments as well
interesting. I actually haven’t had any throughput issues yet but if I do I will definitely keep that in mind
I run jellyfin on bare metal because it makes it easier to debug imo, but I do use docker for caddy and some other little applications (like a tomcat instance for example)
my servers run alpine! it’s incredibly stable even for hobbiest use
why is the password ******* lol
I used to do that but the more I get into os programming the more I’ve found myself scrapping entire 1000+ line files and rewriting the entire thing 🙃
and I think “it’s a miracle I get anything done” is a very common thought in most programmers heads lol
I prefer to argue on the internet via my phone, which I can type pretty fast on thanks to the swipe to type.
and yeah programming simply doesn’t require fast typing, I tend to diagram everything out on my whiteboard before even opening my ide. I just have to write tons and tons of code since I’m in a few low level programming classes
I’m a programmer. I write hundreds of lines of code a day (of varying levels of quality ofc). I also fix technology (phones, laptops, desktops. tablets, etc). I’m probably one of the most “tech-savvy” people I know. I very rarely type faster than 70 wpm. it’s just not necessary for what most of us are doing.
don’t get discouraged. sorting algorithms occur frequently in interviews, and yes you use them a decent amount (especially in languages without built in sorts like c) but they are one of the harder things to visualize in terms of how they work. I’d say avoid anything recursive for now until you can get selection and insertion down pat. check out geeksforgeeks articles on them, but also don’t be afraid to Google willy nilly, you’ll find the resource that makes it click eventually.
in terms of efficiency, it does become a little more difficult to grasp without some math background. big o is known as asymptomatic notation, and describes how a function grows. for example, if you graph f1(x)=15log(x) and f2(x)=x, you’ll notice that if x is bigger than 19, then f2(x) always has a higher output value than f1(x). in computer science terms, we’d say f1 is O(log(n)), meaning it has logarithmic growth, and f2 is O(n), or linear growth. the formal definition of big o is that f(x) is O(g(x)), if and only if (sometimes abbreviated as iff) there exists constants N and C such that |f(x)| <= C|g(x)| for all x>N. in our example, we can say that C = 1, and N>19, so that fulfills definition as |15log(x)| <= 1|x| whenever x>19. therefore, f1(x) is O(f2(x)). apologies for just throwing numbers at you, (or if you’ve heard all this before) but having even just the most basic grasp of the math is gonna help a lot. again, in terms of best resources, geeksforgeeks is always great and googling can help you find thousands of more resources. trust that you are not the first person to have trouble with these and most people before you have asked online about it as well.
I also highly reccomend grabbing a copy of discrete mathematics and it’s applications by Kenneth Rosen to dig farther into the math. there’s a few other types of asymptomatic notation such os big omega and big theta, even little o, that I didn’t mention here but are useful for comparing functions in slightly different ways. it’s a big book but it starts at the bottom and is generally pretty well written and well laid out.
feel free to dm me if you have questions, I’m always down to talk math and comp sci.
edit: in our example, we could also pick c =19 and n = 1, or probably a few other combinations as well. as long as it fills the definition it’s correct.