Scala - Dependent Types

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Dependent types in Scala for types to depend on values. Dependent types are used in encoding invariants and relationships directly in the type system. So, it will have greater type safety and reduce runtime errors.

Dependent Types

Dependent type is a type that depends on a value. This type can change based on the value it is associated with. So, you can have more precise type definitions. Dependent types are used in functional programming and type-safe libraries.

In simpler terms, the type of a variable (or function) depends on a value. So, it creates strong link between the type system and the actual values in the program. Hence it guarantees and reduces the risk of errors.

Example

Following is the example which shows you how to trait Container with a type member T and a value value -

trait Container {
  type T
  def value: T
}

def getValue(c: Container): c.T = c.value

val intContainer = new Container {
  type T = Int
  val value: Int = 42
}

val stringContainer = new Container {
  type T = String
  val value: String = "Hello, Scala!"
}

val intValue: intContainer.T = getValue(intContainer)
val stringValue: stringContainer.T = getValue(stringContainer)

println(intValue) 
println(stringValue)

Save the above program in Demo.scala. Use the following commands to compile and execute this program.

Command

> scalac Demo.scala
> scala Demo

Output

Here, Container has a type member T that depends on the specific instance. The getValue function returns a value of type c.T, which is dependent on the Container instance passed to it.

This will produce the following result -

42
Hello, Scala!

Dependent Function Types

Dependent function types are function types whose result type depends on parameters of function. These are used to define functions where the return type varies based on the input value.

Example

Following is the example which shows you how to use depended function types -

trait Entry { type Key; val key: Key }

def extractKey(e: Entry): e.Key = e.key

val extractor: (e: Entry) => e.Key = extractKey

class StringEntry extends Entry {
  type Key = String
  val key: String = "Scala"
}

class IntEntry extends Entry {
  type Key = Int
  val key: Int = 42
}

val stringEntry = new StringEntry
val intEntry = new IntEntry

println(extractor(stringEntry)) 
println(extractor(intEntry))

Save the above program in Demo.scala. Use the following commands to compile and execute this program.

Command

> scalac Demo.scala
> scala Demo

Output

Here, extractKey is a dependent function. Because its return type e.Key depends on the input parameter e.

This will produce the following result -

Scala
42

Typed Key-Value Datastore

You can use dependent types to create type-safe key-value datastores, where each key has an associated value type.

Example

Following is the example which shows you how to use it in typed key-value datastore -

import scala.collection.mutable

abstract class Key(val name: String) {
  type ValueType
}

trait Encoder[T] { def encode(t: T): Array[Byte] }
trait Decoder[T] { def decode(d: Array[Byte]): T }

object Codec {
  implicit val stringEncoder: Encoder[String] = _.getBytes
  implicit val stringDecoder: Decoder[String] = new String(_)
  implicit val doubleEncoder: Encoder[Double] = d => java.nio.ByteBuffer.allocate(8).putDouble(d).array()
  implicit val doubleDecoder: Decoder[Double] = d => java.nio.ByteBuffer.wrap(d).getDouble
}

class Database {
  private val db = mutable.Map.empty[String, Array[Byte]]

  def set(key: Key)(value: key.ValueType)(implicit enc: Encoder[key.ValueType]): Unit = 
    db.update(key.name, enc.encode(value))

  def get(key: Key)(implicit dec: Decoder[key.ValueType]): Option[key.ValueType] = 
    db.get(key.name).map(dec.decode)
}

object Database {
  def key[T](name: String): Key { type ValueType = T } = new Key(name) { type ValueType = T }
}

object Demo {
  def main(args: Array[String]): Unit = {
    val db = new Database
    import Codec._

    val k1 = Database.key[String]("key1")
    val k2 = Database.key[Double]("key2")

    db.set(k1)("One")
    db.set(k2)(1.0)
    println(db.get(k1))
    println(db.get(k2))
  }
}

Save the above program in Demo.scala. Use the following commands to compile and execute this program.

Command

> scalac Demo.scala
> scala Demo

Output

Above code defines a key-value datastore with path-dependent types for the value types of keys. This ensures type safety by associating each key with a specific value type.

This will produce the following result -

Some(One)
Some(1.0)

Parental Award and Punishment Discipline

Following is the example which shows you how parents can reward any child but can only punish their own children.

Example

case class Parent(name: String) {
  class Child

  def child = new this.Child

  def punish(c: this.Child): Unit = 
    println(s"$name is punishing ${c}")

  def reward(c: Parent#Child): Unit = 
    println(s"$name is rewarding ${c}")
}

object Demo {
  def main(args: Array[String]): Unit = {
    val john = Parent("John")
    val scarlet = Parent("Scarlet")

    john.punish(john.child)
    // john.punish(scarlet.child) // Compile time error
    john.reward(scarlet.child)
  }
}

Save the above program in Demo.scala. Use the following commands to compile and execute this program.

Command

> scalac Demo.scala
> scala Demo

Output

The above code uses path-dependent types to ensure that a parent can only punish their own children but can reward any child.

This will produce the following result -

John is punishing Parent$Child@<hashcode>
John is rewarding Parent$Child@<hashcode>

Dependent Types Summary

  • Types can depend on values in dependent types. So, these have greater type safety and flexibility.
  • You can use dependent types in trait and class definitions for specific type constraints.
  • Dependent types are used for encoding invariants and relationships directly in the type system.
  • Dependent types can reduce the need for explicit type annotations.
  • You can use dependent types in function definitions, class definitions, and trait definitions for more precise relationships.
  • It can reduce code redundancy and improve code maintainability by encoding more logic into the type system.
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