LOADING
Do you like it when compiler generates the boring code for you? Fast, mundane, boring-but-error-prone code? Do you need to implement such a code generator yourself? Have you found out that Shapeless/Mirrors bend your brain a bit too much?
Do you like it when compiler generates the boring code for you? Fast, mundane, boring-but-error-prone code? Do you need to implement such a code generator yourself? Have you found out that Shapeless/Mirrors bend your brain a bit too much?
Congratulations! You might have a valid use case for writing a macro! Plain-old code with some plain old, vals, defs and if-elses. So, we’re opening up an IDE, looking at the API and… oh, no. It’s so low-level. And error prone. And everyone needs to copy-paste the same utilities… which are handling like 50% of the cases, and for the remaining 50% politely asking you to rewrite your code to something actually supported.
Oh, and if your users are both on Scala 2 and Scala 3 you have to write everything twice. You’d better have some tests written to keep them aligned!At this point, you might reconsider using macros: maybe generate some files as managed source, or get back to Shapeless/Mirrors, or just write the boring and error-prone code by hand?
But it doesn’t have to be this way. We can have a standard library for macros that makes simple things simple, and hard things (at least) possible. And we can design it in such a way, that most of the code could be shared between Scala 2 and 3.
And this talk will show you how.
This talk presents McCCT, a new concurrency testing tool developed at KTH by the speakers in the context of an ongoing research project.
Writing client-facing APIs involves mundane tasks, whether it be REST, GraphQL, or gRPC. In this talk, I will pick two repetitive tasks during API development and demonstrate how we can utilize Scala to automate the most boring parts.
Scala Fibers, Java Virtual Threads, and Kotlin Coroutines - this talk shows how this elegant solution manifests at three different abstraction levels.
So, is there a modern solution for web apps that is powerful, simple, and blazingly fast in both CI and the browser? A solution that lets you write in your favorite backend language and is fun? The answer is Datastar!
In this talk, I’ll guide you through the crossroads where Scala intersects with AI, some applications aimed at boosting developer productivity, others focused on integrating your code with LLMs.
In my talk I will argue that we can do much better by relying in a systematic way on types and capabilities.
