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Functional Programming in Kotlin by Tutorials

First Edition · Android 12 · Kotlin 1.6 · IntelliJ IDEA 2022

Section I: Functional Programming Fundamentals

Section 1: 8 chapters
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Appendix

Section 4: 13 chapters
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16. Handling Side Effects
Written by Massimo Carli

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In Chapter 15, “Managing State”, you implemented the State<S, T> data type and gave it the superpowers of a functor, applicative and monad. You learned that State<S, T> describes the context of some state of type S that changes based on some transformations you apply every time you interact with the value of type T in it. Making the State<S, T> a monad means you can compose different functions of type (A) -> State<S, B>. The State<S, B> data type is just a way to encapsulate a StateTransformer<S, T>. This means you can compose functions of type (A) -> StateTransformer<S, B> that’s basically a function of type (A) -> (S) -> Pair<S, B>. If you use uncurry, this is equivalent to a function of type Pair<A, S> -> Pair<S, B>.

Now, think about what an impure function is. It’s a function whose body is an expression that is not referentially transparent because, when executed, it changes the state of the world outside the function body. This means it has a side effect, which breaks composition. But if a side effect is a change in the state of the world, the question now is: Can you somehow represent the state of the world as the type S you use in a State<S, T> and encapsulate the side effect as a simple transformation? In other words, if you define the type World as representing the current state of the world, can you use State<World, T> as a data type that encapsulates any possible side effects?

The answer to this question is yes, and the specific data type is IO<T>.

In this chapter, you’ll learn:

  • How to implement Hello World in a pure, functional way.

  • What the IO<T> data type is.

  • How to use IO<T> to compose functions with side effects.

  • What monad comprehension is.

  • How to use IO<T> in a practical example.

  • How to use suspendable functions to solve basically the same problem IO<T> wants to solve.

This is an essential chapter, and now it’s time to do some magic! :]

From State<S, T> to IO<T>

Hello World is probably the most popular application to implement when learning a new language. This is mainly because it’s very simple and allows you to see how to execute some of the fundamental tasks in common between all applications, like compilation, execution, debugging and so on.

The app you’ll implement here is a little bit different because it’ll allow you to read a name from the standard input and then print a greeting message. Open Greetings.kt in the material for this chapter, and write the following code:

fun main() {
  print("What's your name? ") // 1
  val name = Scanner(System.`in`).nextLine() // 2
  print("Hello $name\n") // 3
}

In this code, you:

  1. Print a message asking the user their name.
  2. Use Scanner to read the name you type as input and save it to name.
  3. Use name to format and print a greeting message.

Feel free to run it, and, after entering your name, you’ll get an output like the one in Figure 16.1:

Figure 16.1: Running the greetings app
Figure 16.1: Running the greetings app

Note: When you run the app, just put the cursor after the input message to insert your name, as shown in Figure 16.1. Then, type your name and press Enter.

The previous code works very well, but the expression in main is anything but pure. Using Scanner, you read the name from the standard input. Using print, you display the result on the standard output. They’re both side effects: interaction with the rest of the world. So, how can you create the previous program but handle side effects in a pure and functional way?

The introduction of this chapter already gave you a hint. What if you think of the external world as a giant state you change when you read the name and write the greeting message?

You can follow this idea starting with the definition of a type you call World. Add the following in the World.kt file:

typealias World = Unit

Here, you define World as a simple alias for the Unit type. At this point, how you define the World type doesn’t really matter. You’ll see later if how you define World really matters or not. In the same file, add the following:

typealias SideEffect = (World) -> World

This is interesting because you’re defining a SideEffect as any function from an initial state of the World to, probably, a different state of the same World. But here, something strange is happening. If you have a function of type SideEffect able to capture the whole World in input and return a different version of it, you’ve essentially eliminated the concept of a side effect because everything happens in the context of that function. In this case, all the functions would be pure.

To prove that you can modify the initial program as the composition of the function, you use:

  • readName, which reads the name from the standard input.
  • printString, which prints a String to the standard output.

readName’s type is (World) -> Pair<String, World> because it receives the World in input and provides the String for the name and a new version of the World in output. Add the following code to Greetings.kt:

val readName: (World) -> Pair<String, World> = { w: World ->
  Scanner(System.`in`).nextLine() to World
}

printString‘s type is a little more interesting. It’s (String, World) -> World because it receives the String to print and the current World in input, returning the new state for the World. In this case, you have two input parameters, but you can apply curry, getting the type (String) -> (World) -> World. With the previous definition of SideEffect, you can say that the type of printString is (String) -> SideEffect. In this way, you make the definition more explicit. Then, add the following code to the same Greetings.kt file:

val printString: (String) -> SideEffect = { str: String ->
  { a: World ->
    print(str) to World
  }
}

Note: As you’ll see later, a type like (String) -> SideEffect says something crucial. It says that printString doesn’t execute a side effect but returns a description of it. This is the main reason it’s a pure function now.

Now, test each of the previous functions by running the following code:

fun main() {
  // ...
  readName(World) pipe ::println // 1
  printString("Hello Max \n")(World) pipe ::println  // 2
}

In this code, you invoke:

  1. readName, passing the current state of the World, printing in output the name you read from the standard input.
  2. printString with a name, and then the function of type (World) -> World with the current state of the World.

After you insert the name in input, you’ll get the output in Figure 16.2:

Figure 16.2: Testing readName and printString
Figure 16.2: Testing readName and printString

In the image, you can see:

  1. An example of a String input.
  2. The output of readName, which is a Pair<String, Unit> of the String in input and the new state of the World you previously defined using Unit.
  3. The output you get using print in printString.
  4. The output of printString, which is again a Unit representing the new state of the World.

This is very interesting, but what you achieved now isn’t actually what you need. You need a way to compose readName and printString as pure functions and get an app that works like the initial one.

Pure greetings

To accomplish your goal, you basically need to create askNameAndPrintGreetings, whose type is (World) -> World. The final state of the world is the one where you asked for a name and printed a greeting message.

fun askNameAndPrintGreetings(): (World) -> World = // 1
  { w0: World -> // 2
    val w1 = printString("What's your name? ")(w0) // 3
    val (name, w2) = readName(w1) // 4
    printString("Hello $name! \n")(w2) // 5
  }
fun main() {
  askNameAndPrintGreetings()(World) pipe ::println
}
Figure 16.3: Running askNameAndPrintGreetings
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Hiding the world

In Chapter 15, “Managing State”, you implemented the State<S, T> monad as a data type encapsulating a StateTransformer<S, T> you defined like this:

typealias StateTransformer<S, T> = (S) -> Pair<T, S>
typealias WorldT<T> = (World) -> Pair<T, World>
val readNameT: WorldT<String> = readName
val printStringT: (String) -> WorldT<Unit> = { str: String ->
  { w: World ->
    Unit to printString(str)(w)
  }
}
infix fun <A, B> WorldT<A>.myOp( // 1
  fn: (A) -> WorldT<B> // 2
): WorldT<B> = TODO() // 3
   WorldT<A> // 1
-> (A) -> WorldT<B> // 2
-> WorldT<B> // 3
   (World) -> Pair<A, World> // 1
-> (A) -> (World) -> Pair<B, World> // 2
-> (World) -> Pair<B, World> // 3
   (World) -> Pair<A, World> // 1
-> (Pair<A, World>) -> Pair<B, World> // 2
-> (World) -> Pair<B, World> // 3
infix fun <A, B> WorldT<A>.myOp(
  fn: (A) -> WorldT<B>
): WorldT<B> = this compose fn.uncurryP()  
fun <T1, T2, R> ((T1) -> (T2) -> R).uncurryP():
    Fun<Pair<T1, T2>, R> = { p: Pair<T1, T2> ->
  this(p.first)(p.second)
}

A hidden greeting

The first implementation of askNameAndPrintGreetings you created forced you to carry the world on at each step.

fun askNameAndPrintGreetings(): (World) -> World =
  { w0: World ->
    val w1 = printString("What's your name? ")(w0)
    val (name, w2) = readName(w1)
    printString("Hello $name! \n")(w2)
  }
fun askNameAndPrintGreetingsT(): WorldT<Unit> = // 1
  printStringT("What's your name? ") myOp { _ -> // 2
    readNameT myOp { name -> // 3
      printStringT("Hello $name! \n") // 4
    }
  }
fun main() {
  askNameAndPrintGreetingsT()(World) pipe ::println
}
Figure 16.4: Running askNameAndPrintGreetings
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The IO<T> monad

So far, you’ve worked with WorldT<T>, which is an abstraction representing a World transformation. This World transformation is basically a side effect. It’s not so different from StateTransformer<S, T> when you replace S with the type World.

The IO<T> data type

In the lib sub-package in this chapter’s material, you find all the files related to the State<S, T> monad. In State.kt, you find the following definition:

data class State<S, T>(
  val st: StateTransformer<S, T>
)
data class IO<T>(val wt: WorldT<T>)

Implementing lift

As you know, lift is the function that allows you to get, in this case, an IO<T> from a WorldT<T>. Depending on the context, you might find the same function with a name like return or pure. Anyway, following the same approach you saw in the previous section, you implement it by replacing the existing code in IO.kt with the following:

data class IO<T>(val wt: WorldT<T>) {

  companion object { // 1
    @JvmStatic
    fun <S, T> lift(
      value: T // 2
    ): IO<T> = // 3
      IO { w -> value to w } // 4
  }
}
operator fun <T> IO<T>.invoke(w: World) = wt(w)

IO<T> as a functor

The next step is to give IO<T> the power of a functor and provide an implementation of map. This is usually very easy, and this case is no different. Open IO.kt, and add the following code:

fun <A, B> IO<A>.map(
  fn: Fun<A, B>
): IO<B> =
  IO { w0 ->
    val (a, w1) = this(w0) // Or wt(w0)
    fn(a) to w1
  }

IO<T> as an applicative functor

Applicative functors are useful when you want to apply functions with multiple parameters. In the same IO.kt, add the following code:

fun <T, R> IO<T>.ap(
  fn: IO<(T) -> R>
): IO<R> =
  IO { w0: World ->
    val (t, w1) = this(w0)
    val (fnValue, w2) = fn(w1)
    fnValue(t) to w2
  }
infix fun <A, B> IO<(A) -> B>.appl(a: IO<A>) = a.ap(this)

IO<T> as a monad

Finally, you want to give IO<T> the superpower of a monad, adding the implementation of flatMap like this to IO.kt:

fun <A, B> IO<A>.flatMap(
  fn: (A) -> IO<B>
): IO<B> =
  IO { w0: World ->
    val (a, w1) = this(w0)
    fn(a)(w1)
  }
infix fun <A, B> WorldT<A>.myOp(
  fn: (A) -> WorldT<B>
): WorldT<B> = this compose fn.uncurryP()

Monadic greetings

In the previous sections, you implemented askNameAndPrintGreetingsT like this:

fun askNameAndPrintGreetingsT(): WorldT<Unit> =
  printStringT("What's your name? ") myOp { _ ->
    readNameT myOp { name ->
      printStringT("Hello $name! \n")
    }
  }
val readName: (World) -> Pair<String, World> = { w: World ->
  Scanner(System.`in`).nextLine() to World
}

val readNameT: WorldT<String> = readName

val printStringT: (String) -> WorldT<Unit> = { str: String ->
  { w: World ->
    Unit to printString(str)(w)
  }
}
val readNameM: IO<String> = IO(readNameT) // 1

val printStringM: (String) -> IO<Unit> =
  printStringT compose ::IO // 2
fun <T> IO<T>.bind(): T = this(World).first
fun askNameAndPrintGreetingsIO() : () -> Unit = { // 1
  printStringM("What's your name? ").bind() // 2
  val name = readNameM.bind() // 3
  printStringM("Hello $name! \n").bind() // 4
}
fun main() {
  askNameAndPrintGreetingsIO().invoke()
}
Figure 16.5: Running a monadic greeting
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The meaning of IO<T>

The greeting example you’ve implemented so far is a great example of a practical use of IO<T>. However, in Chapter 14, “Error Handling With Functional Programming”, you learned that sometimes things go wrong. For instance, you implemented readNameM like:

val readNameM: IO<String> = IO(readNameT)
val readNameT: WorldT<String> = readName

val readName: (World) -> Pair<String, World> = { w: World ->
  Scanner(System.`in`).nextLine() to World
}
val safeReadName: (World) -> Pair<Result<String>, World> =
  { w: World -> // 1
    try {
      Result.success(Scanner(System.`in`).nextLine()) to World
    } catch (rte: RuntimeException) {
      Result.failure<String>(rte) to World
    }
  }

val safeReadNameError: (World) -> Pair<Result<String>, World> =
  { w: World -> // 2
    Result.failure<String>(
      RuntimeException("Something went wrong!")
    ) to World
  }

val safeReadNameT: WorldT<Result<String>> = safeReadName // 3
val safePrintStringT: (String) -> WorldT<Result<Unit>> =
  { str: String ->
    { w: World ->
      Result.success(Unit) to printString(str)(w)
    }
  }
val safeReadNameM: IO<Result<String>> = IO(safeReadNameT) // 1

val safePrintStringM: (String) -> IO<Result<Unit>> =
  safePrintStringT compose ::IO // 2
fun safeAskNameAndPrintGreetingsIO(): () -> Result<Unit> = { // 1
  safePrintStringM("What's your name? ").bind() // 2
    .flatMap { _ -> safeReadNameM.bind() } // 3
    .flatMap { name ->
      safePrintStringM("Hello $name!\n").bind() // 4
    }
}
fun main() {
  safeAskNameAndPrintGreetingsIO().invoke().fold(
    onSuccess = { _ ->
      // All good
    },
    onFailure = { ex ->
      println("Error: $ex")
    }
  )
}
Figure 16.6: Running a monadic greeting with result
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val safeReadNameT: WorldT<Result<String>> = safeReadNameError
Figure 16.7: Running a monadic greeting with error
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suspend fun readStringCo(): String = // 1
  Scanner(System.`in`).nextLine()

suspend fun printStringCo(str: String) = // 2
  print(str)

@DelicateCoroutinesApi
fun main() {
  runBlocking { // 3
    printStringCo("What's your name? ") // 4
    val name = async { readStringCo() }.await() // 5
    printStringCo("Hello $name!\n") // 6
  }
}

Key points

  • A pure function doesn’t have any side effects.
  • A side effect represents a change in the state of the world.
  • The State<S, T> data type allows you to handle state transitions in a transparent and pure way.
  • You can think of the state of the world as a specific type S in State<S, T> and consider StateTransformer<S, T> as a way to describe a transformation of the world.
  • A transformation of the world is another way to define a side effect.
  • Functions with IO operations are impure by definition.
  • You can think of the IO<T> data type as a special case of State<S, T>, where S is the state of the world. In this way, all functions are pure.
  • You can easily give IO<T> the superpowers of a functor, applicative functor and monad.
  • The IO<T> data type is a way to decouple a side effect from its description.
  • IO<T> contains the description of a side effect but doesn’t immediately execute it.
  • In Kotlin, a suspendable function allows you to achieve the same result as IO<T> in a more idiomatic and simple way.

Where to go from here?

Congratulations! With this chapter, you took another crucial step in the study of the main concepts of functional programming with Kotlin. State management with the IO<T> monad is one of the most challenging topics forcing you to think functionally. In the last part of the chapter, you saw how the IO<T> monad can be easily replaced with the use of coroutines. In the following chapter, you’ll see even more about this topic and implement some more magic! :]

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