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Mainecoon is a small library built to facilitate transforming and composing tagless final encoded algebras.


Mainecoon is available on scala 2.11, 2.12, and scalajs. The macro annotations are developed using scalameta, so there are a few dependencies to add in your build.sbt.

  ("org.scalameta" % "paradise" % "3.0.0-M9").cross(CrossVersion.full))

libraryDependencies += 
  "com.kailuowang" %% "mainecoon-macros" % latestVersion  //latest version indicated in the badge above

Note that org.scalameta.paradise is a fork of org.scalamacros.paradise. So if you already have the org.scalamacros.paradise dependency, you might need to replace it.

Auto-transforming tagless final interpreters

Say we have a typical tagless encoded algebra ExpressionAlg[F[_]]

import mainecoon._

trait ExpressionAlg[F[_]] {
  def num(i: String): F[Float]
  def divide(dividend: Float, divisor: Float): F[Float]

With Mainecoon you can transform this interpreter using Cats' FunctionK. I.e, you can transform an ExpressionAlg[F] to a ExpressionAlg[G] using a FunctionK[F, G], a.k.a. F ~> G.

For example, if you have an interpreter of ExpressionAlg[Try]

import util.Try

object tryExpression extends ExpressionAlg[Try] {
  def num(i: String) = Try(i.toFloat)
  def divide(dividend: Float, divisor: Float) = Try(dividend / divisor)

You can transform it to an interpreter of ExpressionAlg[Option]

import mainecoon.implicits._
import cats.implicits._
import cats._

val fk : Try ~> Option = λ[Try ~> Option](_.toOption)

// res0: ExpressionAlg[Option]

Note that the Try ~> Option is implemented using kind projector's polymorphic lambda syntax.

Obviously FunctorK instance is only possible when the effect type F[_] appears only in the covariant position (i.e. the return types). For algebras with effect type also appearing in the contravariant position (i.e. argument types), mainecoon provides a InvariantK type class and an autoInvariantK annotation to automatically generate instances.

@autoFunctorK also add an auto implicit derivation, so that if you have an implicit ExpressionAlg[F] and an implicit F ~> G, you can automatically have a ExpressionAlg[G]. It works like this

import ExpressionAlg.autoDerive._

implicitly[ExpressionAlg[Option]]  //implicitly derived from a `ExpressionAlg[Try]` and a `Try ~> Option`

This auto derivation can be turned off using an annotation argument: @autoFunctorK(autoDerivation = false).

Quick example: make stack safe with Free

With mainecoon, you can lift your algebra interpreters to use Free to achieve stack safety.

For example, say you have an interpreter using Try

@finalAlg @autoFunctorK
trait Increment[F[_]] {
  def plusOne(i: Int): F[Int]

implicit object incTry extends Increment[Try] {
  def plusOne(i: Int) = Try(i + 1)

def program[F[_]: Monad: Increment](i: Int): F[Int] = for {
  j <- Increment[F].plusOne(i)
  z <- if (j < 10000) program[F](j) else Monad[F].pure(j)
} yield z

Obviously, this program is not stack safe.

//throws java.lang.StackOverflowError

Now lets use auto derivation to lift the interpreter with Try into an interpreter with Free

import cats.free.Free
import cats.arrow.FunctionK
import Increment.autoDerive._

implicit def toFree[F[_]]: F ~> Free[F, ?] = λ[F ~> Free[F, ?]](t => Free.liftF(t))

program[Free[Try, ?]](0).foldMap(FunctionK.id)
// res9: scala.util.Try[Int] = Success(10000)

Again the magic here is that mainecoon auto derive an Increment[Free[Try, ?]] when there is an implicit Try ~> Free[Try, ?] and a Increment[Try] in scope. This auto derivation can be turned off using an annotation argument: @autoFunctorK(autoDerivation = false).

Horizontal composition with @autoCartesianK

You can use the CartesianK type class to create a new interpreter that runs both interpreters and return the result as a cats.Tuple2K. The @autoCartesianK attribute add an instance of CartesianK to the companion object. Example:

trait ExpressionAlg[F[_]] {
  def num(i: String): F[Float]
  def divide(dividend: Float, divisor: Float): F[Float]

val prod = tryExpression.productK(optionExpression)
// res11: cats.data.Tuple2K[Option,scala.util.Try,Float] = Tuple2K(Some(2.0),Success(2.0))

If you want to combine more than 2 interpreters, the @autoProductNK attribute add a series of product{n}K (n = 3..9) methods to the companion object. Unlike productK living in the CartesianK type class, currently we don't have a type class for these product{n}K operations yet.

@autoFunctor and @autoInvariant

Mainecoon also provides two annotations that can generate cats.Functor and cats.Invariant instance for your trait.

For documentation/FAQ/guides, go to kailuowang.com/mainecoon.


Any contribution is more than welcome. Also feel free to report bugs, request features using github issues or gitter.

Discussion around mainecoon is encouraged in the Gitter channel as well as on Github issue and PR pages.

We adopted the Typelevel Code of Conduct. People are expected to follow it when discussing mainecoon on the Github page, Gitter channel, or other venues.


Copyright (C) 2017 Kailuo Wang http://kailuowang.com


Mainecoon is licensed under the Apache License 2.0