Freek, a freaky simple Free to combine your DSL seamlessly
Latest commit e4d7699 Jan 29, 2017 @mandubian mandubian committed on GitHub Merge pull request #30 from elongeau/master
Add highlighting to scala code in README
Failed to load latest commit information.
project Upgrade to cats 0.8.1 Nov 10, 2016
src broken test with latest cats Dec 15, 2016
.gitignore Upgrade to cats 0.8.1 Nov 10, 2016
LICENSE pushed to bintray May 17, 2016 Add highlighting to scala code Jan 29, 2017
build.sbt bumping 0.6.7: cats 0.9.0 Jan 27, 2017

Freek, a freaky simple Free to combine your DSL seamlessly

Pere Villega wrote a really cool introduction to Freek & Free before I could even move a finger and it's a really good one even if it was relying on previous version of the API but the ideas are still the same :D

Thanks a lot Pere

Current Version

All versions are published to bintray


  • first scala 2.12 support
  • cross-compiling 2.11.8 & 2.12
  • depends on cats 0.8.0


  • added Freekit/Freekito helpers to reduce .freek boilerplate in basic cases
  • added transpile to flatten Free programs combining Free programs
  • added :&&: operator to combine group of interpreters


  • renamed FX to DSL and NilDSL to NilDSL to represent better the fact that freek is more general than effects and about manipulating any DSL.
  • renamed helped Program to DSL.Make
  • renamed CoproductK to CopK
  • renamed .onionP[O] to .onion[O]
  • introduced peelRight2 & peelRight2 & onionT2 & onionT3
  • removed unneeded specific OnionT implicit converters
  • build for cats-0.4.1/0.6.1/0.7.0


  • introduced new model for CoproductK to improve compile-time globally (from O(n) to O(log2(n)))
  • introduced Program[F <: FX] to help scalac infer the output CoproductK when using the new optimized model
  • result type of a program based on freek[PRG] is no more PRG.Cop but PRG.Cop based on new DSL.Make[PRG]
  • optimized implicit order


  • introduced CoproductK.AppendK to make it robust to combine programs containing sub-programs


  • beta re-introducing operator :||: to combine programs to programs... WIP


  • evaluating .freeko[PRG, O] which is equivalent to .freek[PRG].onionT[O]
  • renamed dropRight -> peelRight and prepend -> wrap


  • replaced type PRG[A] = (Log :|: KVS :|: File :|: NilDSL).Cop[A] by type PRG = Log :|: KVS :|: File :|: NilDSL to simplify the whole API
  • introduced OnionT manipulations .dropRight, .prepend


  • replaces Freenion by OnionT which generalized the Onion embedding to any structure of type TC[_[_], _] and not just Free
  • provides new interpret function solving order/redundancy issues with DSL vs interpreters
  • renames Interpreter combining operator :|: into :&: because combining interpreters is about a product between them, not a sum of them

Freek: a freaky simple Free to combine your DSL seamlessly

Freek is just a few helpers & tricks to make it straightforward to manipulate Free & DSL without hiding it's a Free.

This project has developed for ProjectSeptember which has kindly accepted that we opensource it under Apache2 License to make it as open & free as possible... Contributions & comments are welcome...

Freek out-of-the-box

Use it in your project

# in build.sbt

scalaVersion := "2.12.0" // (or 2.11.8)

resolvers += Resolver.bintrayRepo("projectseptemberinc", "maven")

scalacOptions := Seq("-Ypartial-unification") //if running 2.12

libraryDependencies ++= Seq(
  "com.projectseptember"            %% "freek"                        % "0.6.5"
, "org.spire-math"                  %% "kind-projector"               % "0.7.1"
, "com.milessabin"                  %% "si2712fix-plugin"             % "1.2.0"
# in plugins.sbt
addSbtPlugin("me.lessis" % "bintray-sbt" % "0.3.0")

KindProjector plugin isn't required but it makes higher-kinded types so nicer that I can't do anything else than advising to use it.

si2712fix-plugin is required or you'll have weird compiling errors... Scalac 2.11 is not powerful enough to unify types in a correct as we would expect for Freek. But Scala 2.12 will be better as si2712fix has been merged into it thanks to Miles Sabin fantastic work.

Don't worry using this plugin seriously because it does it's job just at compile-time helping scalac to infer types in the right but it won't have any impact on runtime so no worry in any case.

Combine your DSL(s) with operator :|: (OR)

Imagine you have the following DSL(s):

sealed trait Log[A]
case class LogMsg(level: LogLevel, msg: String) extends Log[Unit]
object Log {
  def debug(msg: String) = LogMsg(DebugLevel, msg)
  def info(msg: String) = LogMsg(InfoLevel, msg)

sealed trait KVS[A]
object KVS {
  final case class Get(key: String) extends KVS[String]
  final case class Put(key: String, value: String) extends KVS[Unit]

sealed trait FileIO[A]
object FileIO {
  final case class GetFile(name: String) extends FileIO[File]
  final case class DeleteFile(name: String) extends FileIO[Unit]

You want to build a program that manipulates the 3 DSL together. So this program will use Log or KVS or File which is a Sum/Coproduct of the 3 DSL.

To represent the DSL summing them all, Freek provides you with the following notation:

type PRG = Log :|: KVS :|: File :|: NilDSL
val PRG = DSL.Make[PRG]

Please note:

  • NilDSL is required at the end of the coproduct and represents the non-existing DSL
  • Some will complain on the ugly symbol :|: but in Scala, there is no other elegant way to combine types (words can't be used in this case)...
  • val PRG = DSL.Make[PRG] is the way to instantiate a value that represents your PRG type. It might seem artificial and actually it is completely: it is just required to convince scalac that it can infer the right coproduct combining all your DSL and this inferred Coproduct is represented PRG.Cop that will be used in all this tutorial.

.freek[PRG] to lift all operations in for-comprehension

Now, you want to write a program based on your DSL using Free Monads because it's an efficient way to describe your business logic without supposing how it will be executed.

So, you're going to use your DSL[_] lifted into Free monads Free[DSL[_], A] using a classic monadic flow i.e. for-comprehension.

In a for-comprehension, to compile successfully, every line should have the same type. Thus, you need to lift all Free[DSL[_], A] to the combined Free type Free[PRG.Cop, A] where PRG.Cop is the sum of all the DSL used in your program.

In a summary, you need a conversion DSL[A] => Free[DSL, A] => Free[PRG.Cop, A].

This can be done in a trivial way using .freek[PRG] in your for-comprehension.

type PRG = Log :|: KVS :|: File :|: NilDSL
val PRG = DSL.Make[PRG]

// Here the type is shown for doc but you can omit it, Scala can infer things
def program(id: String): Free[PRG.Cop, File] = 
  for {
    _     <- Log.debug(s"Searching for value id: $id").freek[PRG]
    name  <- KVS.Get(id).freek[PRG]
    file  <- File.Get(name).freek[PRG]
    _     <- Log.debug(s"Found file:$file").freek[PRG]
  } yield (file)
  • Every line is lifted by .freek[PRG] to Free[PRG.Cop, A]: PRG.Cop builds the real hidden Sum/Coproduct type combining all your DSL. It is a specialized implementation of Shapeless Coproduct for higher-kinded structures called CopK because Shapeless representation doesn't allow to manipulate F[_] as we need it.
  • Just remind that PRG alone is a facility to combine DSL and the real type combining all DSL is PRG.Cop.
  • The whole for-comprehension describes a program
  • The result type is Free[PRG.Cop, ?].

Some people will think about a implicit conversion to avoid having to write freek[PRG] but believe my own experience, inference in for-comprehension isn't so logical in Scala and as soon as you manipulate more complex programs, implicit conversion makes inference break with hardly understandable errors.

Combine interpreters using operator :&: (AND)

Previous program just describes your sequence of operations but it doesn't suppose how it will be executed: it's just a data representation of your program, a description of your computation.

Now, you need to interpret this description into an effectful execution and this is done with interpreters in Freek. Interpreters in Freek are nothing else than classic Natural Transformation (aka FunctionK) F[_] ~> G[_] with some helpers to manipulate multiple combined DSL(s) defined above seamlessly.

Let's suppose we use an async execution context based on Scala Future not to be too fancy.

Define your interpreters per DSL

val LogInterpreter = new (Log ~> Future) {
  def apply[A](a: Log[A]) = a match {
    case Log.LogMsg(lvl, msg) =>
      Future(println(s"$lvl $msg"))

val FileInterpreter = new (File ~> Future) {
  def apply[A](a: DB[A]) = a match {
    case File.Get(name) =>
      Future {

    case File.Delete(name) =>
      Future {

val KVSInterpreter = new (KVS ~> Future) {
  val storage = ...

  def apply[A](a: DB[A]) = a match {
    case KVS.Get(id) =>
      Future {
    case KVS.Put(id, value) =>
      Future {
        storage.put(id, value)

Combine interpreters into a big interpreter with :&:

Executing your program means you are able to interpret DSL Log and KVS and File into an effectful computation.

So you need an interpreter which is the product of KVSInterpreter and LogInterpreter and FileInterpreter.

In Freek, you can combine your interpreters using operator :&: (AND)

val interpreter = KVSInterpreter :&: LogInterpreter :&: FileInterpreter

Remark that:

  • there is no equivalent to NilDSL at the end of sequence (because not types but values)
  • interpreter is actually of type Interpreter which is just a wrapper around a C ~> R where C[_] <: CopK[_]. If you want to access the underlying NaturalTransformation/FunctionK PRG ~> Future, just call interpreter.nat.

Execute your program using interpret

program is just a Free[PRG.Cop, A], right?

So you could use simply foldMap/compile with your interpreter.nat.

But Freek provides a smarter function called interpret that makes the order of DSL vs interpreters not relevant as it will be shown further in this documentation.

val fut = program.interpret(interpreter) // this returns a Future[Unit]

Combine programs together with same operator :|: (SUPER-OR)

The big interest of Free programs is that you can call a Free program inside a Free program. In this case, logically, you need to combine the DSL of both programs into one single DSL and lift all your Free to this bigger DSL.

Introduce new DSL & program

// New DSL
object DB {

  sealed trait DSL[A]
  case class FindById(id: String) extends DSL[Entity]


// the new program
object DBService {
  import DB._

  type PRG = Log.DSL :|: DB.DSL :|: NilDSL
  val PRG = DSL.Make[PRG]

  /** the program */
  // Here the type is indicated for doc but you can omit it, Scala can infer things
  def findById(id: String): Free[PRG.Cop, Entity] =
    for {
      _    <- Log.debug("Searching for entity id:"+id).freek[PRG]
      res  <- FindById(id).freek[PRG]
      _    <- Log.debug("Search result:"+res).freek[PRG]
    } yield (res)

Combine programs

To prepend one or more DSL to an existing combination of DSL into a new program, use the operator :|: also (in the same semantics as +: for Seq):

  type PRG = Log :|: KVS :|: File :|: DBService.PRG
  val PRG = DSL.Make[PRG]

  // Here the type is indicated for doc but you can omit it, Scala can infer things
  def program2(id: String): Free[PRG.Cop, File] = 
    for {
      _     <- Log.debug(s"Searching for value id: $id").freek[PRG]
      name  <- KVS.Get(id).freek[PRG]
      e     <- DB.findById(id).expand[PRG]
      file  <- File.Get(e.file).freek[PRG]
      _     <- Log.debug(s"Found file:$file").freek[PRG]
    } yield (file)

Please note:

  • there is no NilDSL at the end because it's brought by DBService.PRG
  • :|: also appends a list of DSL at the end
  • the use of the expand function instead of freek for the findById operation, the expand function allows the use of a program defined with a smaller DSL in one with a bigger DSL

What about DSL redundancy & order?

You have remarked that Log is redundant in PRG &DBService.PRG` so it might be an issue when declaring your sequence of interpreters. You might also wonder what happens if you don't respect order of DSL in the sequence of interpreters.

If you were using classic foldMap/compile to execute your Free program, you would have to respect the exact order and redundancy of interpreters vs DSL which is a pain.

This is where Freek interpret really becomes interesting as it is order & redundancy-agnostic.

So, for previous combined programs, you can just do:

val interpreter2 = DBInterpreter :&: KVSInterpreter :&: LogInterpreter :&: FileInterpreter

val fut2 = program2.interpret(interpreter2) // this returns a Future[Unit]

Manipulate Stack of result types

Ok till now we have focused on the DSL side F of Free[F[_], A]. We have nice tools to combine different DSL and interpret them. But what about the result type?

In previous samples, we had simple return types in our DSL but this return type often represents the results of operations in your business logic including error types.

Let's define this kind of DSL:

sealed trait Foo[A]
final case class Foo1(s: String) extends Foo[Option[Int]]
final case class Foo2(i: Int) extends Foo[Xor[String, Int]]
final case object Foo3 extends Foo[Unit]
final case class Foo4(i: Int) extends Foo[Xor[String, Option[Int]]]

sealed trait Bar[A]
final case class Bar1(s: String) extends Bar[Option[String]]
final case class Bar2(i: Int) extends Bar[Xor[String, String]]

Here you see some return type Option[Int] or Xor[String, Int].

In general, you want to write programs like:

for {
  i <- Foo1("5").freek[PRG]                    // => here result is Option[String]
  _ <- Bar2(i).freek[PRG]                      // => here result is Xor[String, String]
} yield (())

But you see clearly that i is an Option and types on both lines aren't the same.

If you try to solve those naively in your program, you'll end with something like that:

for {
  optI <- Foo1("5").freek[PRG]                    // => here result is Option[String]
  _    <- optI match {
            case Some(i) => Bar2(i).freek[PRG]    // => here result is Xor[String, String]
            case None => ...                      // => What to return here???
} yield (())

It's ugly and still needs to unify Xor[String, String] and Option[String] in a common type.

The natural approach is to stack your complex return types to be able to manage all cases (order matters naturally):

Xor[String, Option[String]] or Option[Xor[String, String]]

// orders matters naturally and depends on your business rules

As you may know, the classic approach to this is to use MonadTransformers (OptionT & XorT) which work well with Freek but Freek also provides new typesafe facilities called Onion & OnionT to make it a bit more trivial.

Onion, stack of monads/traverses

Onion is just a way to manipulate a stack of monadic & traversable structures like:

type Stack[A] = F[G[H[I[A]]]] (where F/G/H/I must be monads & traversables to allow all features provided by Onion)

You can represent it using Onion facilty:

// Build your Onion like that
type O = F :&: G :&: H :&: I :&: Bulb

// then you could get the Stack again (but in general you don't need it)
type Stack[A] = O#Layers[A]

Bulb is just the terminator of the Onion stack (like NilDSL for combination of DSL)

Let's go back to our original program now and try type unification on every line:

for {
  i   <- Foo1("5").freek[PRG] // => here result is Option[String]
  s   <- Bar2(i).freek[PRG]   // => here result is Xor[String, String]
} yield (())

So, in the for-comprehension, we need to unify types on every line:

Free[PRG.Cop, Option[A]]
// and
Free[PRG.Cop, Xor[String, A]]

// into
Free[PRG.Cop, Xor[String, Option[A]]]

// which is
type O = Xor[String, ?] :&: Option :&: Bulb
Free[PRG.Cop, O#Layers]

As you can expect, that's not enough, you need something more to do what we want.

OnionT, the missing link

For Option, the Monad Transformer is called OptionT For Xor, the Monad Transformer is called XorT

For Onion, Freek provides OnionT[TC[_[_], _], F[_], O <: Onion, A]...

Freaky, isn't it? Don't worry, you don't have to see it most of the time like monad transformers :D

Let's say loud that OnionT is not a Monad Transformer: is an Onion stack of monadic & traversable layers embedded as result type of a monad TC[F[_], ?] (like Free[F[_], ?]).

Finally, if you are able to lift all your Free[PRG.Cop, Option[A] or Xor[String, A]] to OnionT[Free, PRG.Cop, O, A], victory! ... And you can do it with .onionT[O]

Let's give an example of it:

type PRG = Bar :|: Foo :|: Log.DSL :|: NilDSL
type O = Xor[String, ?] :&: Option :&: Bulb

// Here the type is indicated for doc but you can omit it, Scala can infer things
val prg: OnionT[Free, PRG.Cop, O, Int] = for {
  i     <- Foo1("5").freek[PRG].onionT[O]
  i2    <- Foo2(i).freek[PRG].onionT[O]
  _     <-"toto " + i).freek[PRG].onionT[O]
  _     <- Foo3.freek[PRG].onionT[O]
  s     <- Bar1(i2.toString).freek[PRG].onionT[O]
  i3    <- Foo4(i2).freek[PRG].onionT[O]
} yield (i3)

Remark that .oniontT[O] is used in all cases to lift to OnionT[Free, PRG, O, A]

Execute an OnionT with .value

prg has type OnionT[Free, PRG.Cop, O, A] but you want to execute it as a Free Monad, not this weird OnionT-stuff.

It's as simple as you would do with Monad Transformers: access the underlying Free with .value

val fut = prg.value.interpret(interpreters)

.freeko[PRG, O] for the very lazy

Ok, writing .freek[PRG].onionT[O] on each line is boring, right?

Freek provides a shortcut called freeko that combines both calls in one single.

freeko is still in evaluation as it requires some type crafting so if you see weird cases, don't hesitate to report

Here is your program with freeko:

type PRG = Bar :|: Foo :|: Log.DSL :|: NilDSL
type O = Xor[String, ?] :&: Option :&: Bulb

// Here the type is indicated for doc but you can omit it, Scala can infer things
val prg: OnionT[Free, PRG.Cop, O, Int] = for {
  i     <- Foo1("5").freeko[PRG, O]
  i2    <- Foo2(i).freeko[PRG, O]
  _     <-"toto " + i).freeko[PRG, O]
  _     <- Foo3.freeko[PRG, O]
  s     <- Bar1(i2.toString).freeko[PRG, O]
  i3    <- Foo4(i2).freeko[PRG, O]
} yield (i3)

Ok, that's enough simplifications...

Combine sub-programs together with :||:

Finally, you can combine existing programs together and also define local programs.

Debasish Gosh asked me how I would define local programs & re-use them in bigger programs.

Let's take his classic example from his great book Functional and Reactive Domain Modeling that is clearly related to Freek domain.

Define local programs
// Repository DSL
sealed trait Repo[A]
case class Query(no: String) extends Repo[Xor[String, Account]]
case class Store(account: Account) extends Repo[Xor[String, Account]]
case class Delete(no: String) extends Repo[Xor[String, Unit]]

// Repository local program
object Repo {
  type PRG = Repo :|: Log :|: NilDSL
  val PRG = DSL.Make[PRG]

  type O = Xor[String, ?] :&: Bulb

  // here you can define a local program re-usable in other programs
  def update(no: String, f: Account => Account) = for {
    a <-  Query(no).freeko[PRG, O]
    _ <-  Store(f(a)).freeko[PRG, O]
  } yield (())

sealed trait Foo[A]

// Foo can use Repo sub-program
object Foo {
  type PRG = Foo :|: Log.DSL :|: Repo.PRG

  def subFoo(...): Free[PRG.Cop, ...] = ...

sealed trait Bar[A]

// Bar can use Repo sub-program too
object Bar {
  type PRG = Bar :|: Log.DSL :|: Repo.PRG
  val PRG = DSL.Make[PRG]

  def subBar(...): Free[PRG.Cop, ...] = ...

You can see that NilDSL isn't used in Bar.PRG and Foo.PRG because :|: prepends an element DSL to a (coproduct) sequence of DSL and Repo.PRG is already a (coproduct) sequence of DSL.

Combine programs with :||:
type O = List :&: Xor[String, ?] :&: Option :&: Bulb

// Combine all programs using :||:
type PRG = Log.DSL :|: Bar.PRG :||: Foo.PRG
val PRG = DSL.Make[PRG]

// Here the type is indicated for doc but you can omit it
val prg: OnionT[Free, PRG.Cop, O, Int] = for {
  ...   <- Foo.subFoo(...).freeko[PRG, O]
  ...   <- Bar.subBar(...).freeko[PRG, O]
  _     <- Repo.update(.).freeko[PRG, O]
} yield (...)

To make the difference between :|: and :||:, please remind the following:

  • :|: is like operator +: for Scala Seq, it prepends an element DSL to a (coproduct) sequence of DSL.

  • :||: is like operator ++ for Scala Seq, it appends 2 (coproduct) sequences of DSL.

Combine group of interpreters with :&&:

val fooInterpreters = barInterpreter :&: logInterpreter :|: repoInterpreter
val barInterpreters = fooInterpreter :&: logInterpreter :|: repoInterpreter

val interpreters = fooInterpreters :&&: barInterpreters
  • :&&: is like operator ++ for Scala Seq, it appends 2 sequences of interpreters.

Unstack results with .peelRight / .peelRight2 / .peelRight3

Sometimes, you have a Free returning an Onion Xor[String, ?] :&: Option :&: Bulb but you want to manipulate the hidden Option[A] in your program and not A.

You can do that using .dropRight that will unstack Option from the onion Xor[String, ?] :&: Option :&: Bulb and return a (Xor[String, ?] :&: Bulb)#Layers[Option[A]]. Then you have access to Option[A] but naturally, you have to lift all lines of the program to the same level.

For example, you could do the following:

val prg: OnionT[Free, PRG.Cop, Xor[String, ?] :&: Bulb, Option[A]] = for {
  iOpt  <-  Foo1("5").freek[PRG].onionT[O].peelRight
  i2    <-  iOpt match {
              case Some(i) => Foo2(i).freek[PRG].onionT[O].peelRight
              case None => Foo2(0).freek[PRG].onionT[O].peelRight
  • If you need to peel 2 layers, use .peelRight2

  • If you need to peel 3 layers, use .peelRight3

there is also a .wrap[F[_]] that can wrap the existing Onion in F[_]

Difference between .onionT and .onion

  • When you have a Free[PRG.Cop, F[A]] and want to lift info OnionT[Free, PRG.Cop, O, A] and Onion O contains F[_], then use Free[PRG.Cop, F[A]].onionT[O]

  • When you have a Free[PRG.Cop, F[A]] into OnionT[Free, PRG.Cop, O, F[A]] (Onion O can contain F[_]), then use Free[PRG.Cop, F[A]].onion[O]

.onionT1 / .onionT2 / .onionT3

Instead of Foo2(i).freek[PRG].onionT[O].peelRight, you can write Foo2(i).freek[PRG].onionT1[O]

Instead of Foo2(i).freek[PRG].onionT[O].peelRight2, you can write Foo2(i).freek[PRG].onionT2[O]

Instead of Foo2(i).freek[PRG].onionT[O].peelRight3, you can write Foo2(i).freek[PRG].onionT3[O]

Bored adding .free[PRG] on each line? Use Freekit trick

type PRG = Foo1 :|: Foo2 :|: Log :|: NilDSL
val PRG = DSL.Make[PRG]

// remark that you pass the value PRG here
object M extends Freekit(PRG) {
  val prg = for {
    aOpt <- Foo1.Bar1(7)
    _    <- Log.Info(s"aOpt:$aOpt")
    a    <- aOpt match {
      case Some(a)  =>  for {
                          a <- Foo2.Bar21(a)
                          _ <- Log.Info(s"a1:$a")
                        } yield (a)
      case None     =>  for {
                          a <- Foo2.Bar22
                          _ <- Log.Info(s"a2:$a")
                        } yield (a)
  } yield (a)

This works in basic cases & naturally as soon as you have embedded for-comprehension, scalac inference makes it less efficient.

Bored adding .free[PRG].onionT[O] on each line? Use Freekito trick

type PRG = Foo1 :|: Foo2 :|: Log :|: NilDSL
val PRG = DSL.Make[PRG]

// remark that you pass the value PRG here
object MO extends Freekito(PRG) {
  // you need to create this type O to reify the Onion
  type O = Option :&: Bulb 

  val prg = for {
    a    <- Foo1.Bar1(7)
    _    <- Log.Info(s"a:$a")
    a    <- Foo2.Bar21(a)
  } yield (a)

This works in basic cases & naturally as soon as you have embedded for-comprehension, scalac inference makes it less efficient.

Reminding motivations

At ProjectSeptember, we love typesafe & functional programming.

We also like the concept of Free Monad which decouples completely the description of your program from its execution.

Free has a cost in terms of performance & short-term structures allocation but in our domain, IO is much more the bottleneck than these aspects so we can use those concepts without remorse.

We also believe current implementations can be improved progressively using theoretical and even more brutal tools like compiler plugin/optimizations. So we want to push those concepts further and further.

In Cats & Scalaz, Free[F[_], A] representation has already been optimized into a right associated structure and now embeds Coyoneda trick removing the dependency on Functor. Now we can use any DSL F[_] in a Free[F, A].

Free is a generic way to manipulate DSL and convert them into computations and thus can be used to represent some sort of effects combination. But in this context, there are more specialized & interesting approaches in Scala world:

  • Emm : A very clever idea to represent stack of effects and a nice implementation (from which a few ideas have been stolen for freek). It's interesting because it can use existing structures but it has many implicits meaning it has a cost at compile-time and a few questioning about its pure Monadic nature (TBD)...

  • Scala Eff: a more theoretical and deeply interesting implementation based on Freer Monads, more extensible effects's paper by Oleg Kiselyov & friends. It's the next-gen of effects management but it also requires more aware developers certainly... Next step of evangelization ;)... Please note that Eric has recently introduced a model in Eff that got inspired by our latest compile-time optimized CopK model: that's the power of OSS ;)

  • Idris Eff port: this is my personal toy... In Idris, it's (almost) nice, in Scala, it's almost a monster and more an experiment showing it could work. But it's the next-gen + 1/2/3/4 IMHO so let's be patient and make it grow...

But for now, Free concept starts to enter in mind of people so we want to use it as is (with a few enhancements).

Tribute to SI2712 patch

SI2712 recent patch released by @milessabin has changed a lot the way we can build type-intensive libraries because we aren't limited by this terrible issue.

That PR has been merged in Scala 2.12 and it changes things a lot...

Without it, Freek would be much uglier & less fun to use.

Thanks @milessabin again!

Deeper sample can be found in AppSpec

By the way, all of that is also called