Intro

shapeless is a library for type class and dependent type-based programming in Scala. I first became interested in it when I watched a presentation by Dave Gurnell called The Type Astronaut’s Guide to Shapeless.

In the video, he discusses treating Scala case classes generically, as lists parameterized by the type of each of its members.

Let’s say you wanted to store both a String and an Int in a list, you could use use the most recent ancestor type as the generic type of a List[Any]. Another way to represent it would be to use a List[Either[String, Int]], but this doesn’t scale for an arbitrary number of types. Instead, what you might do, is represent the list using a nested 2-tuple. An example:

case object SENTINEL

val str = "String"
val sym = 'symbol
val i: Int = 0
val d: Double = 0.1

(str, (sym, (i, (d, SENTINEL))))

The expression has the type

(String, (Symbol, (Int, (Double, SENTINEL.type))))

Shapless basically does this, but defines a :: class (similar to how Seq is defined) and a HNil object to denote the end of the list. It also provides macro-based methods to convert case classes to this representation, and a host of other useful features.

Although I found this presentation very interesting, I didn’t have much of an interest in taking my understanding further until I encountered the project julienrf/play-json-derived-codecs.

If you have ever used Play Framework, you have probably used the its json implementation. One of the nice things you can do, is to automatically create a JSON formatter (play.api.libs.json.Format) for a case class at compile time. Play uses a macro to do this.

import play.api.libs.Json

case class Employee(name: String)

object Employee {
  lazy val employeeJsonFormat = Json.format[Employee]
}

// Then you convert an employee to a JSON-string like:

Json.toJson(Employee("Bob")).toString
res: { "name": "Bob" }

// And read an employee from a JSON-string like:

Json.parse("""{ "name": "Bob" }""").validate[Employee]
res: JsSuccess(Employee("Bob"), _)

It’s really convenient until you want to create a Format for all the case classes which extend a sealed trait.

For example, you may define a Drawing like below, defining a Group recursively as a Drawing which contains other Drawings.

sealed trait Drawing
case class Circle(radius: Int) extends Drawing
case class Rectangle(width: Int, height: Int) extends Drawing
case class Group(drawings: Seq[Drawing]) extends Drawing

Implementing a Format for this is more tedious than you would expect. It is something like:

sealed trait Drawing
object Drawing {
  implicit lazy val drawingFormat = new Format[Drawing] {
    override def writes(o: Drawing): JsValue = o match {
      case a: Circle => Json.toJson(a)
      case a: Rectangle => Json.toJson(a)
      case a: Group => Json.toJson(a)
    }
    override def reads(json: JsValue): JsResult[Drawing] =
      Circle.circleFormat.reads(json).orElse(
        Rectangle.rectangleFormat.reads(json).orElse(
          Group.groupFormat.reads(json)))
  }
}
case class Circle(radius: Int) extends Drawing
object Circle {
  implicit lazy val circleFormat = Json.format[Circle]
}
case class Rectangle(width: Int, height: Int) extends Drawing
object Rectangle {
  implicit lazy val rectangleFormat = Json.format[Rectangle]
}
case class Group(drawings: Seq[Drawing]) extends Drawing
object Group {
  implicit lazy val groupFormat = Json.format[Group]
}

Ignoring the problem that we do not encode type information anywhere in the JSON, this is all tedious, repetitive boilerplate. There must be a better way!

Enter play-json-derived-codecs, which you use as you’d expect:

sealed trait Drawing
object Drawing {
  implicit val drawingFormat = julienrf.json.derived.formats[Drawing]
}
case class Circle(radius: Int) extends Drawing
case class Rectangle(width: Int, height: Int) extends Drawing
case class Group(drawings: Seq[Drawing]) extends Drawing

That’s it! What is this black magic?

How it works

Although the code to implement play-json-derived-codecs is really short, I had to read a whole book to figure out how it works. Dave Gurnell actually worked on a whole book on Shapeless called The Type Astronaut’s Guide to Shapeless.

This book is invaluable to understanding how things work, and explains almost exactly how Shapeless is used in play-json-derived-codecs. In case you’d rather not read the book yourself, continue reading to discover how it works.

A Format is actually a combination of a Reads and a Writes. For the sake of brevity, I will describe how the Writes works, as creating a Reads is similar.

The first important thing to know about the way Play’s JSON library works is that to write a value as a JsValue, we must have an implicit Writes for that type available. Some examples follow.

It is simple to create a Writes for a case class that uses only simple types because Writes for all of these simple types have already been defined.

case class Employee(name: String)
object Employee {
  implicit val writes = Json.writes[Employee]
}

And creating a Writes[Hierarchy] is simple once we have defined a Writes[Employee]. We’d get an error about a missing Writes[Employee] if we hadn’t defined it above.

case class Hierarchy(supervisor: Employee, employee: Employee)
object Hierarchy {
  implicit val writes = Json.writes[Hierarchy]
}

This is important to know because we can see Writes are usually built recusively. Here is our strategy to build something which creates Writes for sealed traits and their subclasses.

Convert a case class to its generic representation
Convert a generic representation (HList) to a JsValue
Somehow handle the relationship between traits and subclasses

Generic

To convert a case class to its generic representation, we use the LabelledGeneric class. This will encode not only the types of each parameter but their names as well, which is required to create JsObjects.

import shapeless._
case class Employee(name: String, age: Int)

LabelledGeneric[Employee].to(Employee("Jamie", 1))
res: String with labelled.KeyTag[Symbol with tag.Tagged[name], String] :: Int with labelled.KeyTag[Symbol with tag.Tagged[age], Int] :: HNil = "Jamie" :: 1 :: HNil

Calling LabelledGeneric[Employee].to, we get back an HList whose first value is "Jamie", a String tagged with the field name “name”. It is followed by the value 1, which is an Int tagged with the field name “age”.

Let’s see if we can create an OWrites for something like this. Below, an OWrites is like a Writes but always writes things as a JsObject instead of any JsValue.

When we encounter an HNil, we will return an empty object.

implicit def writeHNil = OWrites[HNil] { _ => Json.obj() }

HNil is the base case. For the other cases, we need to process the HList as a head and tail.

implicit def owriteHList[Key, Head, Tail] = {

  val writesHead: Writes[Head] = ???
  val writesTail: OWrites[Tail] = ???
  val name = ???

  Writes[FieldType[Key, Head] :: Tail] {
    case head :: tail =>
      Json.obj(name -> writesHead.writes(head)) ++
        writesTail.writes(tail)
  }
}

And this is the definition of FieldType from Shapeless:

type FieldType[K, +V] = V with KeyTag[K, V]

Hopefully this definition is straightforward, but we are missing various writes and the field name. How do we get these? We can get them through implicit parameters that shapeless will provide. Using shapeless, the code above becomes:

implicit def owriteHList[Key <: Symbol, Head, Tail <: HList](implicit
  fieldType: Witness.Aux[Key],
  writesHead: Lazy[Writes[Head]],
  writesTail: Lazy[OWrites[Tail]]) = {

  val name = fieldType.value.name

  OWrites[FieldType[Key, Head] :: Tail] {
    case head :: tail =>
      Json.obj(name -> writesHead.value.writes(head)) ++
        writesTail.value.writes(tail)
  }
}

Witness is a class which allows us to retrieve the field names used in a LabelledGeneric’s KeyTags. Lazy is a class which makes it easier for the compiler to work with recursively-defined implicits.

We can use it right now if we are willing to convert Employees to HLists manually.

Json.toJson(
  LabelledGeneric[Employee].to(
    Employee("Jamie", 1))).toString
res: String = "{\"name\":\"Jamie\",\"age\":1}"

But why do that when we can do it automatically?

implicit def owritesGeneric[A, AsHListRep](implicit
  gen: LabelledGeneric.Aux[A, AsHListRep],
  owritesHList: Lazy[OWrites[AsHListRep]]
  ) = OWrites[A]{ a =>

  owritesHList.value.writes(gen.to(a))
}

We went right to the finalrimplementation, but hopefully it makes sense given the previous one. First, we need a way to convert an Employee to its HList representation. To do this, we need a LabelledGeneric. Then, we need an OWrites for HLists. We just created that!

We’ve basically just replicated exactly what Json.writes[Employee] will do, but in a more complicated way. Why? Remember that we want to be able to automatically create a Writes for a sealed trait and its implementations.

Shapeless represents a sealed trait and its implementors as a Coproduct.

Recall our definition of a Drawing:

sealed trait Drawing
case class Circle(radius: Int) extends Drawing
case class Rectangle(width: Int, height: Int) extends Drawing
case class Group(drawings: Seq[Drawing]) extends Drawing

We can get a LabelledGeneric representation of a Rectangle:

LabelledGeneric[Drawing].to(Rectangle(1,2))
res: Circle with KeyTag[Symbol with tag.Tagged[Circle], Circle] :+: Group with KeyTag[Symbol with tag.Tagged[Group], Group] :+: Rectangle with KeyTag[Symbol with tag.Tagged[Rectangle], Rectangle] :+: CNil = Inr(Inr(Inl(Rectangle(1, 2))))

So we just need an OWrites for a Coproduct. We will recursively write the list until we reach an Inl, at which point we know we have the value we need, and can write that, along with type information.

implicit def owriteCoproduct[Key, Left, Right](implicit
  owritesLeft: OWrites[Left],
  owritesRight: OWrites[Right]) = {

  val typeName = ???
  OWrites[FieldType[Key, Left] :+: Right]{
    case Inl(left) => owritesLeft.writes(left
      ) ++ Json.obj("type" -> typeName)
    case Inr(right) => owritesRight.writes(right)
  }
}

And here is the code with all of the shapeless boilerplate added in.

implicit def owriteCoproduct[
  Key <: Symbol, Left, Right <: Coproduct](implicit
  fieldType: Witness.Aux[Key],
  owritesLeft: Lazy[OWrites[Left]],
  owritesRight: Lazy[OWrites[Right]]) = {

  val typeName = fieldType.value.name
  OWrites[FieldType[Key, Left] :+: Right]{
    case Inl(left) => Json.obj("type" -> fieldType.value.name
      ) ++ owritesLeft.value.writes(left)
    case Inr(right) => owritesRight.value.writes(right)
  }
}

We also need to define the base case, a OWrites[CNil]. Since we shouldn’t ever have a CNil, we throw an exception if we reach it.

implicit def owriteCnil = OWrites[CNil] { _ =>
  throw new Exception("shouldn't happen") }

Having done that, we can now write a Rectangle:

Json.toJson(Rectangle(1,2)).toString
res: String = "{\"width\":1,\"height\":2,\"type\":\"Rectangle\"}"

And a Group:

Json.toJson(Group(Seq(
  Rectangle(1,2), Circle(9)))).toString
res: String = "{\"drawings\":[{\"type\":\"Rectangle\",\"width\":1,\"height\":2},{\"type\":\"Circle\",\"radius\":9}]}"

We are pretty much done here. You’ll notice that play-json-derived-codecs is a little more complicated. Mostly, this is because it allows you to specify NameAdapters which control naming of case class fields, and a TypeTagOWrites which allows you to customize how the type parameter is manifested in the JSON.

Conclusion

Above, we were introduced to the dependent type and generic programming Scala library Shapeless. We learned about how Play Framework represents JSON, and how we can use Writes to write types to JsValues. Finally, we learned how to use Shapeless to automatically create Writes for sealed traits and their subclasses, just like julienrf/play-json-derived-codecs does.

Here’s a Scalafiddle showing the code that we worked on above. Press the Run button to see the results.

Polyglot

Implementing Play Json Writers using Scala's Shapeless

Intro

How it works

Generic

Conclusion