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The book’s title contains “Functional Programming” and majority of the content might not be interesting for non-FP programmers but there are still a couple of tasty bites applicable to object-oriented programming. In this post I’d like to show you how to harden type safety using only a couple of handy techniques, described in the first chapters of the book. Let’s start with defining the problem. G
Project Loom is a proposal to add fibers and continuations as a native JVM construct. With a JDK release every 6 months, we’ll probably see it released (or some part of it) sooner rather than later. Fibers are light-weight threads, which can be created in large quantities, without worrying about exhausting system resources. Fibers are going to change how we write concurrent programs in Java. Does
Edited 2019–02–07 19:00 UTC— added note to the *> section. Functional programming in Scala, due to various syntactic and semantic idiosyncrasies of the language, can be more difficult to get into than it otherwise should. Specifically, there are some features of, and “proper ways to do stuff”, within the core FP libraries that are obvious once you know of them — yet are not so trivial to discover
“Dependency Injection is just passing parameters”, “Spring is necessary to do Dependency Injection properly”, “Dependency Injection is a way to escape from functional programming”: these are just some of the quotes circulating about Dependency Injection. As for a technical pattern, it seems quite controversial. Is there any substance in Dependency Injection (DI)? Is this something you should be us
Following Martin Odersky’s keynote at ScalaDays, which laid out plans for Scala 3, and John de Goes’s keynote during Scalapeño on the future of Scala, there has been quite a lot of debate in the Scala community. Apart from the keynotes itself, there’s a significant amount of threads on twitter, Slack communities, as well as reddit (e.g. 1, 2). That is the question!All of these are very interesting
There’s a couple of hot development areas in the Scala ecosystem, and the competition between the various side-effect wrappers is one of the most interesting. We have the bifunctor IO from Scalaz 8 (which is now a standalone project, ZIO), we have cats-effect and its IO, which is a simpler version of Monix’s Task, and finally we have the good old Akka actors. Some people say that the IO/Task wrapp
It’s over a month since Scalar 2018; all of the videos are available, and we’re slowly starting to think about the next one (which will probably take place on the 5th & 6th of April 2019). But, something’s missing … yes, the whiteboard voting results! Due to an unfortunate splot of events, we didn’t take pictures of the whiteboards on day 2. But the participants are our best backup. Thanks to Jaku
The Akka Streams library is proven to be very useful in implementing systems focused on data processing. However, if you use it without prior knowledge or insufficient care you may encounter some really weird behavior. At SoftwareMill we’ve been using Akka Streams in many projects. During this time we’ve come across multiple quirks related to this library. After you gain more experience, most of t
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