

Scala example source code file (FunctorUsage.scala)
The FunctorUsage.scala Scala example source codepackage scalaz package example import std.option._ import std.list._ import std.map._ import std.anyVal._ import std.string._ import std.tuple._ import syntax.equal._ import scalaz.concurrent.Task import syntax.functor._ /** * A Functor is a ubiquitous typeclass involving type constructors of * kind * → *, which is another way of saying types that have a * single type variable. Examples might be Option, List, Future. * * The Functor category involves a single operation, named `map`: * * def map[A, B](fa: F[A])(f: A => B): F[B] * * This method takes a Function from A => B and turns an F[A] into an F[B] */ object FunctorUsage extends App { val len: String => Int = _.length // // map // // Option is a functor which always returns a Some with the function // applied when the Option value is a Some. assert(Functor[Option].map(Some("adsf"))(len) === Some(4)) // When the Option is a None, it always returns None assert(Functor[Option].map(None)(len) === None) // List is a functor which applies the function to each element of // the list. assert(Functor[List].map(List("qwer", "adsfg"))(len) === List(4,5)) // // lift // // We can use the Funtor to "lift" a function to operate on the Functor type: val lenOption: Option[String] => Option[Int] = Functor[Option].lift(len) assert(lenOption(Some("abcd")) === Some(4)) // // strength // // Functors in scalaz all come equipped with tensorial strenth! does // that sound exciting? It's not that exciting, it means that we get // two additional derived functions which allow us to turn the // contained values into tuples: assert(Functor[List].strengthL("a", List(1,2,3)) === List("a" > 1, "a" > 2, "a" > 3)) assert(Functor[List].strengthR(List(1,2,3), "a") === List(1 > "a", 2 > "a", 3 > "a")) // there is syntax for the strength functions assert(List(1,2,3).strengthL("a") === List("a" > 1, "a" > 2, "a" > 3)) assert(List(1,2,3).strengthR("a") === List(1 > "a", 2 > "a", 3 > "a")) // // fproduct // // Functor provides a fproduct function which pairs a value with the // result of applying a function to that value. val source = List("a", "aa", "b", "ccccc") val result = Map("a" > 1, "aa" > 2, "b" > 1, "ccccc" > 5) assert(source.fproduct(len).toMap === result) // // void // // We can "void" a functor, which will change any F[A] into a F[Unit] assert(Functor[Option].void(Some(1)) === Some(())) // You might wonder why such a thing would ever be useful, it will // become useful when we have functors that control sideeffects // here's a bit of a contrived example to show where we might want // to void a functor. // pretend this is our database var database = Map("abc" → 1, "aaa" → 2, "qqq" → 3) // Return a Task which removes items from our database and returns the number of items deleted def del(f: String => Boolean): Task[Int] = Task.delay { val (count, db) = database.foldRight(0 → List.empty[(String,Int)]) { case ((k,_),(d,r)) if f(k) => (d+1, r) case (i,(d,r)) => (d, i::r) } database = db.toMap count } // This is a task which will delete two of the three items in our database, val delTask = del(_.startsWith("a")) // it hasn't run yet assert(database.size === 3) // but perhaps we don't care about the number of items that were // deleted, we really just want to execute the sideeffects, and get // a Task[Unit] val voidTask: Task[Unit] = Functor[Task].void(delTask) // There is syntax for void. val voidTask2: Task[Unit] = delTask.void // Running the task returns a Unit. assert(voidTask.unsafePerformSync === (())) // And now our database is smaller assert(database.size === 1) // // Composition // // Functors compose! Given any Functor F[_] and any Functor G[_] we // can compose the two Functors to create a new Functor on F[G[_]]: val listOpt = Functor[List] compose Functor[Option] assert(listOpt.map(List(Some(1), None, Some(3)))(_ + 1) === List(Some(2), None, Some(4))) } Other Scala examples (source code examples)Here is a short list of links related to this Scala FunctorUsage.scala source code file: 
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