scastie VS Play

From personal experience Scala also works. It's 100% possible to learn monads using https://scastie.scala-lang.org/ as a scratch pad.

Instead I typically use https://scastie.scala-lang.org, or an ammonite script, or just create a new file that extends App in my test directory. The thing that worksheets do better is that you can import things from your project (like the little app in the test dir) but they also show runtime values (like repl or scastie). However I've just never gotten them to actually work.

I strongly recommend you play around with the local Scala REPL. I have Scala 2.13 on my main dev computer and Scala 3 on my other computer. The local REPL will let you know when things are deprecated and give you hints as to what you should use instead. Scastie https://scastie.scala-lang.org/ can also be a big help.

Operationally, as you might expect from a language borne from academia, Scala tooling can be problematic and compilation can be slow--particularly if you are not yet using Scala 3, which only recently emerged and is very slowly percolating through the ecosystem (Remember the Python 2 to Python 3 transition?). But type inference, a vast standard library, and the time-tested reliability of the JVM make you very productive once you get the hang of them. Performance varies with the JVM you're running, but regardless you do have to contend with the size of compiled objects and the latency of garbage collection at runtime. When you want to experiment, you can skip the ceremony of writing a class or test and instead use a command-line REPL, an online REPL called Scastie you can share, or an outstanding third-party command-line REPL called Ammonite. Dependency management is achieved with SBT typically but also more general JVM build tools like Gradle and Maven.

I am using https://scastie.scala-lang.org/ which does compile server side in Scala. The UI is a bit hard to handle tho.

https://github.com/scalacenter/scastie#how-do-i-embed-scastie

My major complain here is that, as far as being a web framework there is precious little information here about the framework. How does this framework scale with multiple requests? What concurrency strategy is it using (threads, processes, actors, etc?). Is this opinionated (it doesn't seem so but it also doesn't say it isn't either). How does this work with popular libraries x,y,z. The full docs have a little bit more information, but not a ton. But mostly there are some cute toy examples and "built in python" and thats about it.

Lets compare this with for example play https://www.playframework.com/ I know from this that it built on Akka, its stateless, aims for predictable resource consumption, has non-blocking io, etc. There is a ton of really important information on what does this web framework actually do that is really important when you are making a choice of a framework.

I have no idea how good this framework is, but besides a few toy examples, I can't see anything that makes me thing "wow this is great I need to use this".

A web application framework for Java/Scala: https://www.playframework.com/

Scala 3 migration isn't as simple as migrating other apps, you can track the work at https://github.com/playframework/playframework/issues/11260

And there are frameworks you can use to make development easier, like Play. And Java has plenty of choices for dependency injection frameworks.

However do note, Play should be perfectly usable as well, and it's still maintained by the community: https://github.com/playframework/playframework/issues/11649

In university I learned a bit of Java, so maybe I could use it professionally I guess?. There were many options to choose from. DropWizard, Spark, Play Framework. But the more documented one in the internet I found was Springboot, besides there were some courses in spanish and some friends that knew something about Springboot, so I give it a chance.

For a backend web server I use Play - https://www.playframework.com/ which I find to be the easiest one as a backend web server. For learning/using spark I found this course from coursera to be very useful. https://www.coursera.org/learn/scala-spark-big-data