@CliffsEsport @Viss Well, for me, python is the easiest to implement and pick up to build things. The main upside and downside of python is the availability of libraries. (able to find libraries for many things). That's an upside, BUT, the downside, is the supply chain for python libraries is ALSO not very well vetted, and there are most certainly bits of malware or Bitcoin mining or other crap you do NOT want on your systems that show up...
As a basic language (without loading libraries, willy nilly), it's probably the best. (Disclaimer: that's the tech stack I am using most now)
@CliffsEsport @Viss I previously developed in:
php
perl
Java
c++
(various variants of c++, including Microsoft's Visual C++)
c
assembly
pascal
basic
🤪
Depending on your specialty/interest:
Couldn't hurt to give you a foundation of understanding for how programming operates and works. File & logic handling, errors, logging, networking, etc.
There are useful tool 'challenges' to build your own toolkit. Stuff that you will likely use anyhow, that can get you started.
@ai6yr @jackryder @CliffsEsport @Viss I once wrote an open source Java editor, when (1) the libraries were young and small and (2) we actually had hopes of cross-platform applications. It was popular enough now that I see the AI can give me a summary of it, but I won't bore you guys with the name.
Now fish shell is my jam. Haha.
@ai6yr @jackryder @CliffsEsport @Viss The best part about fish is the interactive use. It has predictive completion. So if you type certain things regularly it will predict for you and a right arrow will accept it.
It seems spooky sometimes how often it knows what I'm trying to do, but I guess I'm trying to do things I usually try to do.
Fish shell scripting is a little bit clearer than bash but perhaps also less powerful. So it's a trade-off. Clarity for power.
@ai6yr @jackryder @CliffsEsport @Viss yikes. The AI says that my old editor can be associated with certain University curricula!
Those poor kids.
tl;dr - no. It is turtles all the way down.
Honestly the hardest choices are the ones that don't move us forward. Picking a random language and diving into it will serve you equally well. There is a literal tidal wave of languages available, each designed to solve a set of problems the author felt needed to be solved.
Personally? I tend to apply the language to the problem. If you are playing with web tools, stick to web-friendly environments.
Find the environments that interest you, and then look at what moves them. Becoming an expert in JavaScript is not as useful to Data Scientists, but the mechanics are similar enough to work off of.
If you are building towards a team, quite literally look at their githubs and figure out the languages they seem to focus in. Those are likely popular in the social group you are trying to work in.
@CliffsEsport @ai6yr @Viss Oh, well then that's perfect.
Grab one of the languages listed above and find a project to build in it. Start small but meaningful to you.
Example: You have mentioned homelab and understanding CS and C. Create a repo and build something for your homelab using one of the C-languages.
Web tool: C#
CLI: C
CLI: C++
Keep the tool simple and productive. Work through the hows and the why's of the stuff you are typing in.