this post was submitted on 04 Aug 2023
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For various reasons.
Different languages take different approaches and models to do stuff. Thus making each one better or worse for different challenges.
For example, python is easy and quick to get up and running. Bug it's slow and unsuited for low level programming (like OSes, drivers, and embedded stuff). On the other hand, C is very fast and very low level, allowing you to make both high performance programs and low level stuff, but it's a nightmare to use and you will run into all sorts of problems that an easier language, like python would avoid. All of this is mostly due to python being interpreted (instead of compiled) and c having manual memory management.
But they might also take a different approach at computation, like for functional languages (opposed to imperative languages) which try to solve problems in a more "mathematical" and declarative way, instead of defining a sequence of instructions. Or, even more, logic programming languages, in which you define a series of logical statements and the language tries to find solution and draw conclusions from them.
And some languages are designed around some particular concept that they think is beneficial and worth exploring, maybe taken from various other languages and put together, like rust which is designed around the RAII design pattern and takes large inspiration from functional languages, while still being and imperative procedural language (like C, so not object oriented). Or java which was designed to be a portanle but performante object oriented language, with support for low powered embedded system, full of features but simpler than c++, etc... all stuff that now is nothing special, but remember that java us very old. Or kotlin which tries to be java (they are interoperable), but modern and better and more "pure" or "consistent". Or c++ that started as an object oriented superset of c, but then started adding every single feature of every other imperative language, and never giving up on older stuff, to the point of becoming very hard to use correctly while making it very easy to screw yourself in the most intricate ways.
And of course there are domain specific languages (opposed to general purpose languages). Which aren't even necessarily Turing complete. They are designed for one purpose only, and they do that better than general purpose languages. For example AWK for text processing, or SQL for databases, or matlab for scientific calculations, or TeX for typesetting, or GLSL for shaders, or coq for theorem proving. And here imagination truly is the limit.
So, the point is, every language is more suited then other for some kind of work. And when people stumble across some problem that is hard to tackle and come up with some approach to solve it, or when they grow fed up with the issues of some older languages, they often like to make a new language around that. And some times this leads to entirely new paradigms which are worth exploring.
P.s.: I like languages:)
How do you know which language to use? And how do you know if you should stick to a language that you already know or if you should learn a new one?
Sorry if this is a dumb question I only just finished my first year of being a comp sci major
It's not a dumb question. The answer is "it depends", it's mostly a choice. The general rule is that when yo start a project, you choose the language that you think will help you the most, whether that is because you already know the language, or because you have to work with stuff that already use that language, or because the language is better at doing that.
Regarding whether to stick to a language or learn a new one, in general your CS teachers will tell you (and they are correct) that you should not "learn to program in a language" but just "learn to program" and then apply that knowledge to whatever language you need. So, you should always learn languages that are different from the ones you already know in order to learn new paradigms, and then when you need a specific language, just learn the details about it. BUT, even if this way you will be able to use most languages, you will not be "good" at most, so you should also have some languages that you know really well and are experienced in. And for that you should choose the ones that are more useful to you (or maybe useful for your job) or the ones that you like.
Generally the most supported language on the tool/platform you want to target is the best one. Like SQL on databases, JS/ES in browsers, python in data science related stuff, etc. If multiple are heavily supported then just pick the one that's the most comfortable.