OlegYch

val compileTimes = inputKey[Unit]("Get compilation time for each folder")
compileTimes / aggregate := false,
compileTimes := {
  import complete.DefaultParsers._
  //  val ((depth, _), filter) = (NatBasic ~ " " ~ StringBasic).parsed
  val (depth, filter) = spaceDelimited("depth filter").parsed match {
    case Seq(depth, filter) => (depth.toInt, filter)
    case _ => sys.error("expected depth and filter arguments, eg '2 /'")
  }
  val s = state.value

bpholt

#!/usr/bin/env bash
set -o errexit -o nounset -o pipefail
IFS=$'\n\t'
RED='\033[1;31m'
NC='\033[0m' # No Color
readonly RED NC

function log_error () {
  echo -e "$1" > /dev/stderr
}

djspiewak

Understanding Comparative Benchmarks

I'm going to do something that I don't normally do, which is to say I'm going to talk about comparative benchmarks. In general, I try to confine performance discussion to absolute metrics as much as possible, or comparisons to other well-defined neutral reference points. This is precisely why Cats Effect's readme mentions a comparison to a fixed thread pool, rather doing comparisons with other asynchronous runtimes like Akka or ZIO. Comparisons in general devolve very quickly into emotional marketing.

But, just once, today we're going to talk about the emotional marketing. In particular, we're going to look at Cats Effect 3 and ZIO 2. Now, for context, as of this writing ZIO 2 has released their first milestone; they have not released a final 2.0 version. This implies straight off the bat that we're comparing apples to oranges a bit, since Cats Effect 3 has been out and in production for months. However, there has been a post going around which cites various compar

Baccata

//> using dep "com.typesafe:config:1.4.3"
//> using dep "com.github.pureconfig::pureconfig:0.17.6"
//> using scala "2.13.14"

import com.typesafe.config._
import pureconfig.generic.semiauto._
import pureconfig.ConfigReader
import pureconfig.ConfigSource

import java.{util => ju}