Learn X in Y Minutes

This is what my solution looks like (could be a lot cleaner, but first time writing Befunge!) https://raw.githubusercontent.com/jjjjjjjjjjjjjjjjjjjj/adven...

    FORTH ?KNOW IF
        HONK!
    ELSE
        FORTH LEARN!
    THEN

Icon by Ralph Griswold et al, at U of AZ. Some innovative language features.

Pike. Supposed to be fast. Roxen web server written in Pike.

ElastiC (not a typo, IIRC).

Has checked these out some years ago.

Donno current status.

For lots more, check Wikipedia list of programming languages.

I also recommend Klong. Very different, but worth the challenge.

I'm cheating a bit by putting the languages I know at the end, but it's still a really fun challenge. Doesn't really help that it's exam week though

because they aren't Ivy League educated and world renowned professors who make millions working for Google. Those books prey on desperate people looking for a chance to break into one of the few industries left that provide a decent living

In part, perhaps it's from the educational system which curiously enough isn't geared particularly well toward learning. It used to be geared toward the needs of teaching (which is not the same as learning), but lately it's been geared toward passing standardized tests. Someone going through such a system might be excused for thinking that the way you learn something is by cramming facts until you can repeat them once and then forgetting the whole thing because that test isn't coming back.

1. If I'm going for a full stack interview soon, having a quick look/update would provide a good refresh before digging in deeper.

2. Someone wants to compare between different aspects/features of different languages, some quick learning would definitely provide a good sense of differences.

Most jobs forces people to do things as quickly as possible, and that results in trying to learn things quickly. I see nothing wrong as this is being part of adapting to the environment.

Like mym1990 pointed out, no one likes to be new/bad at something, or maybe that's just me.

Even if it is the main tool for the main goal, we still want to get there soon. And in this case, 'there' includes being able to get to levels of deeper mastery, so accelerated learning of the basics with minimal wheel-spinning helps.

OTOH, if it is a pleasurable hobby or pass-time, then sure linger for a decade with all the trivia, and enjoy the heck out of it!

So basically, it’s best thought of as a tool to help intermediate level programmers parachute into foreign territory with some idea of where they’re going.

There are tremendous differences between programming technologies. Because the word “language” can distract you here.

What you say in French and German and English will be pretty much the same.

But many programming “languages” practically have very different runtimes, idioms, guarantees, caveats. For example in some all your data is immutable. Or take a look at the concurrency model of Elixir/Erlang/Go “processes” vs Java Threads).

Erlang has a preemptive scheduler for those “processes”. Try doing that in vanilla JS.

It’s not just syntax. Syntax is the surface difference but it doesn’t end there.

This is not to nitpick the posted website which is a great first step but it won’t tell you the whole story.

Another example is closures. Some languages don’t have them at all. Some languages allow modifying closed over variables. Some treat them as immutable constants (but still accessible to read).

Those are huge semantic differences with profound implications to how you approach problems and write code.

When comparing Programming technologies always think in terms of: how does it represent data, how does it move/share data between entities, how does it handle errors, what guarantees does it have.

Finally an inseparable part of any programming technology is the standard library, and nowadays the whole third party ecosystem of packages.

When thinking about what is different about say Python and Erlang I’d argue the least significant of that is syntax.

You won’t build machine learning models in Erlang and you won’t build highly-available, fault-tolerant, billion-user chat applications in Python.

And trust me not because of how the for loop looks.

What makes a good Python programme makes a terrible/impossible C or Rust programme. It might not be hard to write Scala code like you might Java and have it run, but you're doing things distinctly wrong.

That's the sort of language-y stuff that's hard to teach in Y minutes imho.

Like, once you write a few functions you sort of just intuitively know the O runtime of the algorithm. Once you store a few things in memory, you intuitively know the O space of the storage. And when it breaks, you look for somewhere that you introduced n^2 and fix it.

Unless you're optimizing search algorithms, it almost never matters in practice. Even that double nested loop won't matter until you have a big dataset.

Proceeding further in the Haskell-land might help even more, since Haskell is essentially typed lambda calculus.