Matt Hughes matthughes

** Adapted from an answer in the FS2 gitter channel by Fabio Labella: https://gitter.im/functional-streams-for-scala/fs2?at=5e962ebb6823cb38acd12ebd

What is Stream.compile and what does it do? Is it actually compiling something? Optimizing the streaming somehow?

At its core, Stream[I, O].compile is nothing more than a namespace for related methods that return the same type wrapper, I. It's not compiling anything or doing any optimization. For example, all the methods on (s: Stream[IO, Int]).compile generally have the return type IO.

In FP there is a technique of design through algebras (speaking here in the most general sense, even more general than tagless final) and it basically works like this:

you have some type, for example Option
some introduction forms (ways of getting "into" the algebra, e.g., Option.empty, Option.some; this is often referred to as "lifting" into a type)

	#!/usr/bin/env ruby

	# Read from stdin rather than file.
	file_data = $stdin.read

	# Upper case title
	re = /^#* .+/
	file_data.gsub!(re) { \|match\| "#{match.upcase}"}

	# Mutate todos

	//> using scala "3.1.2"
	//> using lib "co.fs2::fs2-core:3.2.7"
	//> using lib "co.fs2::fs2-io:3.2.7"
	//> using lib "org.http4s::http4s-core:0.23.11"
	//> using lib "org.http4s::http4s-dsl:0.23.11"
	//> using lib "org.http4s::http4s-ember-client:0.23.11"

	import fs2.Stream
	import cats.effect._
	import cats.syntax.all._

	➜ metals git:(master) pwd [I]
	/Users/mhughe008/OpenSource/metals
	➜ metals git:(master) git info \| head [I]

	## Remote URLs:

	origin https://github.com/scalameta/metals.git (fetch)
	origin https://github.com/scalameta/metals.git (push)

	## Remote Branches:

	Java System Properties:
	#Wed Oct 23 18:42:54 EDT 2019
	gopherProxySet=false
	awt.toolkit=sun.lwawt.macosx.LWCToolkit
	java.specification.version=11
	sun.cpu.isalist=
	sun.jnu.encoding=UTF-8
	java.class.path=/usr/local/Cellar/bloop/1.3.4/bin/blp-coursier
	java.vm.vendor=AdoptOpenJDK
	coursier.mainJar=/usr/local/Cellar/bloop/1.3.4/bin/blp-coursier

	[info] + and.scala.&.example at line 19: describe(1): OK, proved property.
	[info] + and.scala.&.example at line 15: describe(-1): OK, proved property.
	[info] + and.scala.&.example at line 21: describe(2): OK, proved property.
	[info] + and.scala.&.example at line 17: describe(0): OK, proved property.
	[info] ResponseGeneratorSpec
	[info] haveHeaders should
	[info] + work on value equality (377 ms)
	[info] Total for specification ResponseGeneratorSpec
	[info] Finished in 384 ms
	[info] 1 example, 0 failure, 0 error

	object PaulRetry {
	import scalaz.stream.{ async, Process }
	import scalaz.concurrent.Task
	import scala.concurrent.duration._
	implicit val scheduler = scalaz.stream.DefaultScheduler

	/**
	* Try running the process `p`, retrying in the event of failure.
	* Example: `retry(Process.awakeEvery(2 minutes))(p)` will wait
	* 2 minutes after each failure before trying again, indefinitely.

	trait RetryCombinators {

	// Taken from Paul's gist: https://gist.github.com/pchiusano/7894696
	/**
	* Try running the process `p`, retrying in the event of failure.
	* Example: `retry(time.awakeEvery(2 minutes))(p)` will wait
	* 2 minutes after each failure before trying again, indefinitely.
	* Using `retry(Process.awakeEvery(2 minutes).take(5))(p)` will do
	* the same, but only retry a total of five times before raising
	* the latest error.

	<?xml version="1.0" encoding="UTF-8"?>
	<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
	<plist version="1.0">
	<dict>
	<key>bundleUUID</key>
	<string>452017E8-0065-49EF-AB9D-7849B27D9367</string>
	<key>fileTypes</key>
	<array>
	<string>scala</string>
	</array>

	implicit def AgentCodecJson: CodecJson[Agent] =
	CodecJson(
	(agent: Agent) => jString(agent match {
	case Agent.System => "System"
	case Agent.User(name) => name
	}),

	c => c.focus.string.map {
	_ match {
	case "System" => Agent.System