ryan-williams

Monoid

A monoid has two components:

id (or empty)

"make an instance from nothing"

• 0 (Unit => Int)
• "" (Unit => String)
• Nil (Unit => List[_])

ChristopherDavenport

Cats Anchored

cats-time

Cats Instances for Java Time

cats-scalacheck

Cats Instances for Scalacheck

kubukoz

Why you prefer cats instead of zio? TF? It’s looks like zio ecosystem more widely and zio 2.0 has better performance What do you think?

Great question!

Performance-wise, it really depends on what you're doing. The problem with benchmarks (including the ones posted for ZIO and Cats Effect) is that they apply only to abstract situations, which are often nothing like what you see in real applications. A great write-up on this problem by Daniel Spiewak here, he wrote it better than I ever could: https://gist.github.com/djspiewak/f4cfc08e0827088f17032e0e9099d292

Also, this is not an app meant for production - I don't care that much about performance under load because there will be no load. And individual operations will often be bounded by I/O anyway, so the efficiency of the underlying runtime is likely not going to make a noticeable difference in use. Then again, both the client and server are JVM apps, so even the start-up penalty of the client will slow us down than picking even the least efficient e

s5bug

// Author: Aly Cerruti
// Please follow along in Scastie, so you can see the output of statements:
//   https://scastie.scala-lang.org/CLmK5tLuRd6rxXuEnba0rQ

// A Category
trait Category[
  // A collection of objects
  Obj <: AnyKind,
  // A constraint on those objects (Scala lacks dependent typing, so i.e. `Val = [A] =>> Monoid[A]` makes the category of Monoids)
  Val[_ <: Obj],

djspiewak

What follows are some of my (very) rough thoughts on what we can and should do with respect to CPS transformation in Scala at the language level. I'll try to start with some motivation behind my thinking, as well as some rambling observations on the nature of the problem space, but don't expect too much coherence here. :-)

The Problem

Async programming is hard.

Okay let's actually be more specific than that. High-performance I/O is hard. Signal multiplexing is a powerful technique for achieving high(er) performance I/O, particularly network I/O, but the tradeoff is that, in order to utilize it, the user-space programming model must allow for suspension and resumption of sequential continuations (often called "fibers" or "coroutines"). Achieving this type of programming model without significant tradeoffs in usability is what is exceptionally hard.

If that wasn't bad enough though, these problems are inextricably conflated with another set of problem spaces which are, themselves, very difficult. In