The case for unapply

Scala’s unapply method is often left unconsidered although it presents an elegant way to solve some specific problems.

The situation we’re going to look at in this article is when we need to add constructors (that can possibly failed to a class).

First let’s take a concrete example with a simple value class:

final case class Id(value: Int) extends AnyVal
Continue reading “The case for unapply”

A lazy future

This blog is a follow up from the previous one and builds up on our small effect experiment. As good as our abstraction goes it still wraps a plain Scala Future which is eager. Meaning that as soon as you create a Future it starts executing on the provided ExecutionContext.

Our effect wrapper F suffers the exact same issue as it just wraps a Future.

final case class F[+E, +A](value: Future[Either[E, A]]) extends AnyVal

Why is that a problem? Simply because it makes it harder to reason about the code.

Continue reading “A lazy future”

The problem with EitherT

If you’ve used Scala Future in a real application you probably realised that having a failed Future wrapping any Throwable isn’t the most efficient way to handle errors in your application.

I used Scala Future in this example but it applies equally to cats effects. Any type like IO[A] suffers the same issue in that regard as it doesn’t provide an error channel other than Throwable.

It’s basically the same issue as the undocumented Java RuntimeException. The only way to know what exceptions are thrown is to look at the implementation (when it’s possible).

Continue reading “The problem with EitherT”

Dealing with errors

As a programmer we don’t really like to deal with errors. We like to focus on the happy path – the one that provides value – and deal with the errors later because … well, we have to do it!

However dealing with failures is crucial if we don’t want our program to stop on the first error it encounters.

But still we don’t want to mix the “clean” code of the happy path with the “dirty” error handling code. And in fact this is what exceptions were suppose to bring: A clean happy path in a try statement and the error handling code in a catch statement. You know everything clean and separated.

In Scala we have a rich type-system which gives us more options to handle errors. But before we start let’s be clear by what we mean by errors. Continue reading “Dealing with errors”

Leveraging the type system to avoid mistakes

We all know we should write tests to make sure our system behaves as it is supposed to.

Surely tests are necessary to ensure correctness of our programs but they only depend on what the programmer is willing to test (or can think of testing).

What I mean is that there will always be gaps in the test coverage, like uncovered corner cases or improbable combinations of events, …

In Scala we have a powerful type system that we can use to help us avoid some mistakes.

Why would you bother writing a test to make sure a function handle some corner cases correctly when you can use the type system to make sure such cases won’t ever happen. Continue reading “Leveraging the type system to avoid mistakes”

Load-Balancing strategies

A load-balancing strategy is a strategy allowing to spread the load (e.g. HTTP requests) over a fleet of instances providing some functionality. If you’re like me you probably think of a sort of load-balancer (e.g. Nginx, AWS ELB, …) in front of several nodes (e.g. EC2 instances, docker containers, …). This is, indeed, a very common pattern but there are other alternatives with different pros and cons. Continue reading “Load-Balancing strategies”

Back-pressure in Grpc-akkastream

Grpc-akkastream, the akka-stream implementation built on top of GRPC looks good on the surface but if you look under the hood there is one problem: it doesn’t provide any support for back-pressure.

Akka-streams (as any reactive-stream implementation) provides a way for back-pressure and GRPC (at least the Java version) also has an API that support back-pressure. Let’s see how we can wire everything together and provide a truly reactive akka-stream implementation for GRPC! Continue reading “Back-pressure in Grpc-akkastream”

Making sense of SBT

SBT is probably the most popular (as in “most used”) build tool for Scala yet people (including me) experienced a hard time figuring out why it doesn’t perform as they expect.

Originally known as the “Simple Build Tool” it has later been renamed to “Scala Build Tool” (maybe to acknowledge the fact that it was not so simple?)

Part of the reason is that it’s not really intuitive. True, there is documentation available but how many developers don’t bother reading it (at least until the effort overcomes the pain of using SBT) plus it’s much easier to copy/paste code snippets without completely understanding what they do.

That being said SBT is not magic, so let’s try to understand how it works so that next time we’re not reduced to copy/paste cryptic code snippets until it works. Continue reading “Making sense of SBT”