Sebastian Voss sebastianvoss

## column-def.jsx
{
    field: "fieldname",
    width: 130,
    editable: true,
    renderEditCell: (params) => renderCell({ ...params, onPaste }),
}

## di-in-fp.md

      
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                gvolpe
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                Dependency Injection in Functional Programming
              
          
    Dependency Injection in Functional Programming

There exist several DI frameworks / libraries in the Scala ecosystem. But the more functional code you write the more you'll realize there's no need to use any of them.
A few of the most claimed benefits are the following:

Dependency Injection.
Life cycle management.
Dependency graph rewriting.


## StreamFirstChunk.scala
import cats.effect._
import cats.implicits._
import fs2._

object Reconstitute {

   // Simplest method I can find at the current moment
   def tryFetch1[F[_]: Sync, A](s: Stream[F, A]): F[Stream[F, A]] =
    s.pull.uncons
      .flatMap {

## fluent-filebeat-comparison.md

      
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                StevenACoffman
                / fluent-filebeat-comparison.md
            
            
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                Fluentd Fluent-bit FileBeat memory and cpu resources
              
          
    Fluent-bit rocks

A short survey of log collection options and why you picked the wrong one. 😜
Who am I? Where am I from?

I'm Steve Coffman and I work at Ithaka. We do JStor (academic journals) and other stuff. How big is it?


Number
what it means


101,332,633
unique visitors in 2017


## example.md

      
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                mpilquist
                / example.md
            
            
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                Properly scheduling effect evaluation in FS2
              
          
    TL;DR - Use fs2.time.sleep_[Task](delay) ++ Stream.eval(effect) instead of Stream.eval(effect.schedule(delay)).
FS2 never interrupts evaluation of an effect. This can lead to surprising behavior when using the schedule method on Task. Consider this test driver:
def testInterruption[A](effect: Stream[Task, A]): Stream[Task, A] = {
  val logStart = Stream.eval_(Task.delay(println("Started: " + System.currentTimeMillis)))
  val logFinished = Stream.eval_(Task.delay(println("Finished: " + System.currentTimeMillis)))
  val interruptSoonAfterStart =
 Stream.eval(async.signalOf[Task,Boolean](false)).flatMap { cancellationSignal =&gt;

  
## Applied-FP-with-Scala.md

      
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                jdegoes
                / Applied-FP-with-Scala.md
            
            
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    Applied Functional Programming with Scala - Notes

Copyright © 2016-2018 Fantasyland Institute of Learning. All rights reserved.
1. Mastering Functions

A function is a mapping from one set, called a domain, to another set, called the codomain. A function associates every element in the domain with exactly one element in the codomain. In Scala, both domain and codomain are types.
val square : Int => Int = x => x * x

  
## App.scala
package ch.netzwerg

import cats.data.Xor
import io.circe._
import io.circe.generic.auto._
import io.circe.parser._
import org.scalajs.dom.document

import scala.scalajs.js
	{
	field: "fieldname",
	width: 130,
	editable: true,
	renderEditCell: (params) => renderCell({ ...params, onPaste }),
	}
	import cats.effect._
	import cats.implicits._
	import fs2._

	object Reconstitute {

	// Simplest method I can find at the current moment
	def tryFetch1[F[_]: Sync, A](s: Stream[F, A]): F[Stream[F, A]] =
	s.pull.uncons
	.flatMap {
	package ch.netzwerg

	import cats.data.Xor
	import io.circe._
	import io.circe.generic.auto._
	import io.circe.parser._
	import org.scalajs.dom.document

	import scala.scalajs.js