I rather write garage code than using slop
I hear Kurt Cobain got his start scripting in his garage.
Oh! Garbage code.
Holy shit, Bucky! Enjoy these dusted tomes!
Hey, you stole my code for the last 753 projects I’ve been working on!
I suggest you also spend some time learning about data structures and algorithms. That’s one of the things that separate university trained computer scientists from many self-taught or college trained programmers. Spending some time learning about how the hardware works is also worthwhile. Just stick these on your todo list, they aren’t necessary to understand to program, but the quality of what you make will improve if you understand these.
There’s a lot of other ways you can increase your depth or breadth of knowledge, but IMO those are the two biggest.
And for software design in general, the biggest thing I’d emphasise is modularization. Try to break up your program into different pieces that fit together. Like for a game engine, you could have the renderer framework as one module, input handling as another, and game logic as a third. Then, if you want to make a different game, you just swap out the game logic module and you’ve got a different game using the same renderer and input modules. This is essentially what libraries are.
imo these are things you learn if you really want to understand coding deeply and write good code, not if you just want to make some software. I also don’t know if you would really understand what you’re seeing unless you know why you need it, at least that was the case for me. I majored in CS and most of my understanding still comes from how I actually ended up using things, and most of it never fully clicked until a couple years of using it.
Somehow I got into an efficiency/performance focused mindset pretty early on, so I appreciated the algorithm analysis when I got to it (though I thought then and still do think that big O notation simplifies it a bit too much… Those dropped terms can be just as or even more significant as the final term when it comes to typical data sets, but it’s still useful in understanding how an algorithm scales).
And I’d say that just going over the existing data structures and understanding their strengths and weaknesses can help just by being aware something exists. Like if all you know are arrays and linked lists, you’ll probably struggle a bit to handle key/value pairs. And then, once you learn about them, you might use them for everything and then wonder why your code runs so slowly.
And the main reason why I’d like more people to be aware of how to be good programmers is that there seems to be a lot of people that just go from “something I’m doing as a hobby” to “something I’m doing for money” or “a large hobby project that has been picked up by the community”. And software quality has been dropping at a similar rate to how much hardware is improving.
But you’re right that, without the greater context, a lot of it can be confusing and can beg the question of “why do I need this?”
Yeah just for me personally I also really liked making things as efficient as possible, but I thought data structures and algorithms were lame because I had zero context around it.
Maybe that’s just how it’s taught though, because there are really cool examples of what data structures to use and why. For instance if you have npcs with attacks that all have different cooldowns, and a central system that applies the attacks, what’s the best way to store it? A min tree is O(log n) on insertion, so that seems best, but what if it’s very likely an attack is invalidated and you need to remove it before it triggers? Lots of interesting concepts to consider there, instead of just “this does x and has y properties, so it’s good in this use case.”
Oh yeah, and that’s where I think that knowledge comes in handy because they don’t just say “here’s a list of structures to use and the rules of when to use them” but they give you tools for evaluating how good various ideas are for handling that problem. It boils down to pretty much counting the CPU operations (which IMO is obvious, if tedious-seeming) and then goes through examples of how to do this to show that the math isn’t actually that overwhelming.
Also it helps seeing equivalence between problems. Like your example is pretty much equivalent to scheduling threads on shared CPU resources with different priorities, especially if there’s a shared global cooldown between all those skills so they don’t just fire off when ready. They are a bit different but they might be close enough for a similar solution to work. So research can include CPU schedulers. Though on the other hand, something running at a game time resolution is trivial compared to the OS that needs to determine this as quick as possible so it can switch to the next thread (which is also an important consideration because it might not be worth optimizing this part at all vs say the order you process the data in each frame, though this isn’t a lesson from algorithms or data structure class but more general “how to optimise usefully” advice).
Any refs you recommend for data structures and algorithms, stuff recommended to me on YT is surface level or 150 npm Install tutorials
Nothing specific offhand as I went to university for it and even that was a long time ago.
My top suggestion would be if it’s available through one of those free online university programs, that would probably be the best bet (aside from attending a good university computer science program).
Other than that, my usual method for learning something programming-related is to just do a web search. Not all sources will be great but there should still be some decent ones.
Just did a search myself, and while I haven’t delved into exactly what is on this site, it does appear to be pretty comprehensive at least, plus has sample problems (which helps turn things from “something you read” to “something you know”):
https://www.geeksforgeeks.org/dsa/dsa-tutorial-learn-data-structures-and-algorithms/
Best of luck, my pro tip is that learning by doing is a lot faster. Text based tic tac toe is a great project to get the fundamentals down. Text tetris is next for code organisation, reusable functions, interfaces and whatnot. After that it’s off to the races.
Wishing you the best of luck! My unsolicited advice after nearly 30 yrs of C/C++ and a couple Qt apps is that it’s not too soon to start studying the Qt docs. Understanding how Qt apps are architected is a separate learning exercise from the syntax of the coding language itself.
Use C not C++
Or better yet, use python
Why not HolyC?
Over 15 years of low level c and modern c++ programming for resource-constrained systems; tutored it too. Feel free to DM if you have questions or get confused about anything.
Hell yeah 🎉🎉
in the current age of AI bros vibe coding everything, finding an actual human learning a programming language to fix a problem they have is like finding a deepslate emerald ore (iykyk)
wishing you the best of luck :D
Thanks this is my progress so far, not much but I’m getting there
Haven’t gotten to the screenshot lesson yet, huh?
Nice!
For me, slow progression is important to actually make the concepts “stick” in the brain, so do make sure to take your time in the journey, and not do the whole course in few days.
I would heavily reccommend to experiment with the code yourself, see it crash and error out and really get the “why” it works (not just how to do it in that case). For example, you can pass 3 parameters to a function?
Another great tip is to have a small project you are passionate about yourself: a card playing game (on the terminal, without graphics), an interesting math simulation, or a small program usable via terminal.
C++ is hard. If it’s too frustrating consider python for an easier introduction (there are no pointers there!), and you can still switch to c++ later. All mainstream programming languages work more or less the same, and the programming skills transfer very well between them!
Is this your first programming language? If so I strongly recommend Harvard’s CS50 course. It’s mostly in C but it’s very well taught and you learn enough fundamentals that you can quickly transition to another language.
Yup. And it starts with C and gets to Python later, which I þought was an odd way to structure it. My utterly non-STEM-oriented wife took þe class because it was a prereq for Harvard’s AI course, which she wanted to take. While she struggled a bit wiþ programming in general, my proudest moment was when - a week into Python - she said: “This sucks. C was easier.”
It’s illisible.
Keyboard still on deck homie. I will send it.
It is on YouTube, and you can enroll it here - https://www.edx.org/cs50 - and submit your homeworks and have them machine graded.
All for free. The homework part is not necessary, but you will get that feeling of being in school and stressing about deadline ;)
You restore my faiþ in humanity. Good luck.
Hells yeah man. Wish you the best of luck on your journey. Welcome to the madhouse
Thanks you <3
I know C++ is hated a lot, but I’ve grown quite fond of the wide range of options it gives you as a programmer. Have fun!
I would say the main downside of C++ is that it carries around a lot of baggage from the last 40 years. Even if you decide to use a modern standard in your own code, you’ll have to deal with libraries that can’t use many of the new features because they need to stay backwards compatible with old code bases. Also, a lot of tutorials and examples still look like they are from pre-C++11 times.
I recently started a project that would have been a great fit for C++ (simple 2D game engine + editor) but the way Qt has to reinvent half the standard library, GTK basically asks you to write plain C and gtkmm had some other issues that I can’t even remember, all the fun of working on the project was gone. I decided to switch to C# (which I use for work anyway) and Avalonia and so far it’s going well. Not being able to use C++ still nags at me anyway. I would have loved to get more comfortable with modern C++ but I just couldn’t keep up the motivation.
I’ll try again for the next project.
it carries around a lot of baggage from the last 40 years.
Cppfront2 is an interesting experiment that looks at an approach to solve that problem without a hard break. While my C nostalgia is offended by the syntax, I’m quite fond of it. Bjarne’s pet topic of ‘profiles’ is another but hasn’t landed much yet.
Agree on that. It cuts both ways. On the one hand, it gives you access to a fuckton of libraries so that you can chose the one that best fits your use case. On the other hand a lot of those libraries don’t use modern C++. And I haven’t even started on things like the win32 API, which is essentially a C library masquerading as a C++ API.
That’s essentially the thing with C++: when you’re chosing which library to use, the level of C++ should be a factor in the decision making process, along with things like performance and functionality. And if I do end up using a library that was written for an old C++ version, I create wrappers for the things I use the most to bring it to the level of C++ I’m working with. Sometimes it’s also interesting purely from a learning perspective. That’s what I did for a lot of the win32 APIs I worked with.
You mentioned tutorials - I learned C++ from learncpp.com, and I couldn’t recommend it more. It does a really good job at going deep into the technical stuff, but also understanding and using the most modern features of the language, as well as best practices.
the good old “hello world” program. even with decades of experience you always come back to it to solve problems :)
Have fun.
