Functional Error Handling in Kotlin: Part 2 - Result and Either

Riccardo Cardin

Riccardo Cardin

28 min read  • 

kotlin fp type-syst...

Share on:

Introduction

In this series first part, we introduced some of the available strategies to handle errors in a functional fashion using Kotlin and the Arrow library. In this second part, we’ll continue our journey by looking at the Result and Either data types and how to use them to handle errors in a functional way.

For the project’s setup, please refer to the first part of this series, in which we set up Maven and the needed dependencies.

Without further ado, let’s get started!

The Domain

We’ll use extensively the domain model we introduced in the last article. We want to create an application that manages a job board. The main types of the domain are:

data class Job(val id: JobId, val company: Company, val role: Role, val salary: Salary)

@JvmInline
value class JobId(val value: Long)

@JvmInline
value class Company(val name: String)

@JvmInline
value class Role(val name: String)

@JvmInline
value class Salary(val value: Double) {
    operator fun compareTo(other: Salary): Int = value.compareTo(other.value)
}

Moreover, we’ll simulate a database of jobs using a Map<JobId, Job>:

val JOBS_DATABASE: Map<JobId, Job> = mapOf(
    JobId(1) to Job(
        JobId(1),
        Company("Apple, Inc."),
        Role("Software Engineer"),
        Salary(70_000.00),
    ),
    JobId(2) to Job(
        JobId(2),
        Company("Microsoft"),
        Role("Software Engineer"),
        Salary(80_000.00),
    ),
    JobId(3) to Job(
        JobId(3),
        Company("Google"),
        Role("Software Engineer"),
        Salary(90_000.00),
    ),
)

A Jobs module will handle the integration with the database:

interface Jobs

Now that we have defined the domain model and the module that will contain the algebra to access it, it’s time to start implementing the different approaches to handle errors in a functional way.

The Result Type: Lifting the Try-Catch Approach to a Higher Level

Nullable types and the Option type we’ve seen so far are great for handling errors in a functional way. They don’t store the cause of the error. In other words, they don’t tell us why the error happened.

We can represent an error using different approaches. The first is reusing the Throwable type and all its exception subtypes. The Kotlin programming language has the Result<A> type for that since version 1.3, which models the result of an operation that may succeed with an instance of A or may result in an exception. It’s similar to the Try<A> type we’ve seen in the Scala programming language.

Despite what you may guess, the Result<A> type is not defined as a sealed class. It’s a value class without any subclass:

// Kotlin SDK
@JvmInline
public value class Result<out T> @PublishedApi internal constructor(
    @PublishedApi
    internal val value: Any?
) : Serializable

If you’re asking, the @PublishedApi marks the internal constructor and the value as accessible from public extension inline functions but not from anywhere else. Here, the trick to represent success and failure results as values of the value attribute, which has the type Any? and not T?. In case of success, the value attribute will contain the value of type T, while in case of failure, it will contain an instance of the Result.Failure class, defined as follows:

// Kotlin SDK
internal class Failure(
        @JvmField
        val exception: Throwable
    ) : Serializable

Now that we introduced a bit of internals let’s see how we can create instances of the Result<A> type. Kotlin defines two different smart constructors for that:

val appleJob: Result<Job> = Result.success(
    Job(
        JobId(2),
        Company("Apple, Inc."),
        Role("Software Engineer"),
        Salary(70_000.00),
    ),
)

val notFoundJob: Result<Job> = Result.failure(NoSuchElementException("Job not found"))

Unfortunately, we’ve no fancy extension functions defined on the Result<A> type, so we can’t write anything similar to job.toResult(). C’est la vie. It’s not that hard to define such an extension function:

fun <T> T.toResult(): Result<T> =
    if (this is Throwable) Result.failure(this) else Result.success(this)

val result = 42.toResult()

How can we use it now that we know how to build a Result? First of all, let’s create the version of our Jobs module that uses the Result type:

interface Jobs {

    fun findById(id: JobId): Result<Job?>
}

class LiveJobs : Jobs {

    override fun findById(id: JobId): Result<Job?> = try {
        Result.success(JOBS_DATABASE[id])
    } catch (e: Exception) {
        Result.failure(e)
    }
}

We decided to handle only unexpected errors with the Result type by catching exceptions, not the case in which the job is not found.

The findById function is implemented using the try-catch approach. However, using the Result type together with a try-catch block is so common, that the Kotlin SDK defines a runCatching function that does exactly that:

// Kotlin SDK
public inline fun <R> runCatching(block: () -> R): Result<R> {
    return try {
        Result.success(block())
    } catch (e: Throwable) {
        Result.failure(e)
    }
}

Using the runCatching function, we can rewrite the findById function as follows:

override fun findById(id: JobId): Result<Job?> = runCatching {
    JOBS_DATABASE[id]
}

The runCatching function is also defined as an extension function on the Any type, so we can use it on any object:

override fun findById(id: JobId): Result<Job?> = id.runCatching {
    JOBS_DATABASE[this]
}

Once we have a Result, we can use it differently. The first is to check if the result is a success or failure. We can use the isSuccess and isFailure properties. To show them, as we made for other types, we can create our JobsService using the new flavor of the Jobs module, and develop a simple printOptionJob method, which prints different messages depending on the result of the findById function:

class JobService(private val jobs: Jobs) {

    fun printOptionJob(jobId: JobId) {
        val maybeJob: Result<Job?> = jobs.findById(jobId)
        if (maybeJob.isSuccess) {
            maybeJob.getOrNull()?.apply { println("Job found: $this") } ?: println("Job not found for id $jobId")
        } else {
            println("Something went wrong: ${maybeJob.exceptionOrNull()}")
        }
    }
}

The above code also introduces some of the extractor methods defined on the Result type:

  • getOrNull returns the value of the Result or null otherwise.
  • getOrThrow returns the value of the Result or the throw of the exception contained in the Result.Failure instance.
  • getOrDefault returns the value of the Result or a given default value if the Result is a failure.
  • getOrElse returns the value of the Result, or the result of a given lambda, onFailure: (exception: Throwable) -> R if the Result is a failure.

Conversely, the method exceptionOrNull returns the exception in the Result.Failure instance or null otherwise.

If we execute the above method using a valid JobId, we’ll get the following output:

Job found: Job(id=JobId(value=1), company=Company(name=Apple, Inc.), role=Role(name=Software Engineer), salary=Salary(value=70000.0))

However, it’s far more idiomatic to transform and react to values of a Result rather than extracting it. To apply a transformation to the value of a Result, we can use the classic map function:

val appleJobSalary: Result<Salary> = appleJob.map { it.salary }

Instead, we can use the mapCatching function if the transformation to apply to the value of the Result can throw an exception. Let’s reuse our CurrencyConverter class from the first part of the series. The CurrencyConverter is a class that converts amounts from one currency to another one. In detail, we want to develop a method to convert an amount in USD to EUR. This time, we add validation on the input amount:

class CurrencyConverter {
    @Throws(IllegalArgumentException::class)
    fun convertUsdToEur(amount: Double?): Double =
        if (amount != null && amount >= 0.0) {
            amount * 0.91
        } else {
            throw IllegalArgumentException("Amount must be positive")
        }
}

The converter will throw an exception if the input amount is null or negative. Let’s think about the converter as an external library that we can’t change. We can use the mapCatching function to convert the salary of a job from USD to EUR, handling the fact that the conversion can fail, throwing an exception. Let’s add the converter as a dependency to our JobService class, and let’s use it to implement a new method:

class JobService(private val jobs: Jobs, private val currencyConverter: CurrencyConverter) {

    fun getSalaryInEur(jobId: JobId): Result<Double> =
        jobs.findById(jobId)
            .map { it?.salary }
            .mapCatching { currencyConverter.convertUsdToEur(it?.value) }
}

If we execute the above function using an invalid JobId, we’ll get a Result containing the exception thrown by the convertUsdToEur function:

fun main() {
    val currencyConverter = CurrencyConverter()
    val jobs = LiveJobs()
    val maybeSalary = JobService(jobs, currencyConverter).getSalaryInEur(JobId(42))
    println(maybeSalary)
}

The output is the following:

Failure(java.lang.IllegalArgumentException: Amount must be positive)

If we want to recover from a failure Result, we can use the recover function. This function takes a lambda that will be executed if the Result is a failure. The lambda takes as input the exception contained in the Result.Failure instance and returns a new value of the same type as the successful type of the original Result:

// Kotlin SDK
public inline fun <R, T : R> Result<T>.recover(transform: (exception: Throwable) -> R): Result<R> {
    contract {
        callsInPlace(transform, InvocationKind.AT_MOST_ONCE)
    }
    return when (val exception = exceptionOrNull()) {
        null -> this
        else -> Result.success(transform(exception))
    }
}

The original T type must be a subtype of the new R type since we return the initial value if the Result succeeds.

In our example, we can use the recover function to return a default value if no job is found:

val maybeSalary: Result<Double> = JobService(jobs, currencyConverter).getSalaryInEur(JobId(42))
val recovered = maybeSalary.recover {
    when (it) {
        is IllegalArgumentException -> println("The amount must be positive")
        else -> println("An error occurred ${it.message}")
    }
    0.0
}
println(recovered)

If we execute the above code with the same input as the previous example, we can get a more detailed and more precise output than the previous one:

The amount must be positive
Success(0.0)

As we did for the map function, we can use the recoverCatching variant if the lambda passed to the recover function can throw an exception.

To execute some side effect with the value of a Result, whether successful or a failure, we can use the reliable methods the SDK gives us, i.e., the functions onSuccess and onFailure. Both functions return the original Result instance, so we can chain them:

// Kotlin SDK
public inline fun <T> Result<T>.onSuccess(action: (value: T) -> Unit): Result<T> {
    contract {
        callsInPlace(action, InvocationKind.AT_MOST_ONCE)
    }
    if (isSuccess) action(value as T)
    return this
}

public inline fun <T> Result<T>.onFailure(action: (exception: Throwable) -> Unit): Result<T> {
    contract {
        callsInPlace(action, InvocationKind.AT_MOST_ONCE)
    }
    exceptionOrNull()?.let { action(it) }
    return this
}

We can refactor our primary example to use the onSuccess and onFailure functions:

val notFoundJobId = JobId(42)
val maybeSalary: Result<Double> =
    JobService(jobs, currencyConverter).getSalaryInEur(notFoundJobId)
maybeSalary.onSuccess {
    println("The salary of jobId $notFoundJobId is $it")
}.onFailure {
    when (it) {
        is IllegalArgumentException -> println("The amount must be positive")
        else -> println("An error occurred ${it.message}")
    }
}

Clearly, the output of the above code is the following since the JobId 42 is not present in our database:

The amount must be positive

If we want to give both the lambda to apply in case of success and the lambda to apply in case of failure, we can use the fold function:

// Kotlin SDK
public inline fun <R, T> Result<T>.fold(
    onSuccess: (value: T) -> R,
    onFailure: (exception: Throwable) -> R
): R {
    contract {
        callsInPlace(onSuccess, InvocationKind.AT_MOST_ONCE)
        callsInPlace(onFailure, InvocationKind.AT_MOST_ONCE)
    }
    return when (val exception = exceptionOrNull()) {
        null -> onSuccess(value as T)
        else -> onFailure(exception)
    }
}

As we can see, the fold function is not only used to apply side effects. It can be used to transform a Result into another type. In fact, many of the transformations we’ve seen so far are shorthands for applying the fold function in particular cases.

The above example can be rewritten using the fold function as follows:

maybeSalary.fold({
    println("The salary of jobId $notFoundJobId is $it")
}, {
    when (it) {
        is IllegalArgumentException -> println("The amount must be positive")
        else -> println("An error occurred ${it.message}")
    }
})

Composing Result Instances

As we saw in the previous article, we often deal with types (usually some containers) that are “chainable” or “monadic” in structure (more details on A Fresh Perspective on Monads: Generalizing Chained Computations), so the crucial point is how we can compose and combine them. In the first part of this series, we implemented a function that returns the gap between the job salary given a job id and the maximum compensation for the same company. We called the function getSalaryGapWithMax.

We want to refactor the example using the Result type. First, we need to add the findAll function to the Jobs interface and implementation:

interface Jobs {

    fun findAll(): Result<List<Job>>
    // Omissis...
}

class LiveJobs : Jobs {

    override fun findAll(): Result<List<Job>> =
        Result.success(JOBS_DATABASE.values.toList())
    // Omissis...
}

To calculate the gap with the max salary, we need to retrieve a job with a given id and all the jobs available. So, we need to compose two Result instances.

The Kotlin SDK doesn’t provide any form of flatMap like function for the Result type. So, how can we compose subsequent computations resulting in a Result? Remember that two of the most essential principle of Kotlin are pragmatism and ergonomics. If we think about it, we already have all the tools to build some monadic style list comprehension without using flatMap.

One of the main properties of monadic list-comprehension is the ability to short-circuit the computation if one of the steps fails. Exceptions are very good at doing short-circuiting, so why not use them? We saw that on a Result, we can call the getOrThrow function to get the value of a Result or throw an exception if the Result is a failure. So, we can use the getOrThrow function to short-circuit the computation if one of the steps fails. However, we want to avoid handling exceptions through try-catch blocks. So, we can use the runCatching function to wrap the computation again in a Result.

To make the code more readable, first, we define an extension function that returns the maximum salary of a list of Job:

fun List<Job>.maxSalary(): Result<Salary> = runCatching {
    if (this.isEmpty()) {
        throw NoSuchElementException("No job present")
    } else {
        this.maxBy { it.salary.value }.salary
    }
}

If the list is empty, we threw a NoSuchElementException, wrapping it together in a Result. Then, we can use the new function to implement the getSalaryGapWithMax function in the JobService as follows:

class JobService(private val jobs: Jobs, private val currencyConverter: CurrencyConverter) {

    // Omissis...
    fun getSalaryGapWithMax(jobId: JobId): Result<Double> = runCatching {
        val maybeJob: Job? = jobs.findById(jobId).getOrThrow()
        val jobSalary = maybeJob?.salary ?: Salary(0.0)
        val jobList = jobs.findAll().getOrThrow()
        val maxSalary: Salary = jobList.maxSalary().getOrThrow()
        maxSalary.value - jobSalary.value
    }
}

As we can see, we can forget about the Result type during the composition process with this approach, focusing on the success values. The rise of exceptions and the use of the runCatching function allows us to short-circuit the computation if one of the steps fails.

What about the Arrow library and the Result type? As we saw for the nullable types, Arrow offers some exciting extensions. First, Arrow adds the flatMap function to the Result type. If we are Haskell lovers, we can’t live without it, and we can use the flatMap to compose subsequent computations resulting in a Result. Let’s try to rewrite the previous example using the flatMap function from the Arrow library:

import arrow.core.flatMap

class JobService(private val jobs: Jobs, private val currencyConverter: CurrencyConverter) {

    // Omissis...
    fun getSalaryGapWithMax2(jobId: JobId): Result<Double> =
        jobs.findById(jobId).flatMap { maybeJob ->
            val jobSalary = maybeJob?.salary ?: Salary(0.0)
            jobs.findAll().flatMap { jobList ->
                jobList.maxSalary().map { maxSalary ->
                    maxSalary.value - jobSalary.value
                }
            }
        }
}

As we said in the previous article, the absence of native support for monadic comprehension in Kotlin makes the code less readable if we use sequences of flatMap and map invocations. However, as we saw both for nullable types and for the Option type, Arrow gives us nice DSLs to deal with the readability problem. For the Resulttype, the DSL is called result:

// Arrow SDK
public object result {
    public inline fun <A> eager(crossinline f: suspend ResultEagerEffectScope.() -> A): Result<A>
    // Omissis

    public suspend inline operator fun <A> invoke(crossinline f: suspend ResultEffectScope.() -> A): Result<A>
    // Omissis
}

The suspend and the eager version of the DSL define a scope object as the receiver, respectively arrow.core.continuations.ResultEffectScope and arrow.core.continuations.ResultEagerEffectScope. As we did in the previous article, we’ll use the eager flavor of the DSL.

As for the nullable types and the Option type, the result DSL gives us the bind extension function to unwrap the value of a Result and use it. If the Result fails, the bind function will short-circuit the calculation and the whole block inside the result DSL returns the failure. The bind function is defined as an extension function inside the ResultEagerEffectScope:

// Arrow SDK
public value class ResultEagerEffectScope(/* Omissis */) : EagerEffectScope<Throwable> {

    // Omissis
    public suspend fun <B> Result<B>.bind(): B =
        fold(::identity) { shift(it) }
}

The shift function short-circuits the computation and returns the failure, terminating the continuation chain. Remember, Arrow implements all the scopes concerning error handling using a continuation-style approach.

fun getSalaryGapWithMax3(jobId: JobId): Result<Double> = result.eager {
    println("Searching for the job with id $jobId")
    val maybeJob: Job? = jobs.findById(jobId).bind()
    ensureNotNull(maybeJob) { NoSuchElementException("Job not found") }
    val jobSalary = maybeJob.salary
    println("Job found: $maybeJob")
    println("Getting all the available jobs")
    val jobList = jobs.findAll().bind()
    println("Jobs found: $jobList")
    println("Searching for max salary")
    val maxSalary: Salary = jobList.maxSalary().bind()
    println("Max salary found: $maxSalary")
    maxSalary.value - jobSalary.value
}

This time, we’ll change the example’s main workflow. We’ll use a NoSuchElementException to signal the job with the given jobId is not present in the database. We used the ensureNotNull function to check and apply if a nullable value is not null and apply. In the case of the scope defined in the result DSL, the function short-circuits the execution with a Result containing the given exception as a failure.

Let’s change the main function to use the new getSalaryGapWithMax3 function:

fun main() {
    val currencyConverter = CurrencyConverter()
    val jobs = LiveJobs()
    val notFoundJobId = JobId(42)
    val salaryGap: Result<Double> =
        JobService(jobs, currencyConverter).getSalaryGapWithMax3(notFoundJobId)
    salaryGap.fold({
        println("Salary gap for job $notFoundJobId is $it")
    }, {
        println("There was an error during execution: $it")
    })
}

If we run the previous example giving the JobId 42 as input, we’ll get the following expected output:

Searching for the job with id JobId(value=42)
There was an error during execution: java.util.NoSuchElementException: Job not found

As we can see, the execution was short-circuited when the ensureNotNull function returned a Result containing the NoSuchElementException as a failure. However, the result DSL does not equal the runCatching function. If we throw an exception inside the result DSL, it will be propagated to the caller and bubble up through the call stack. Let’s try to throw an exception inside the result DSL:

fun main() {
    val result: Result<Nothing> = result.eager {
        throw RuntimeException("Boom!")
    }
}

If we run the above code, we RuntimeException will escape the result DSL, printing the following stack trace:

Exception in thread "main" java.lang.RuntimeException: Boom!
	at in.rcard.result.ResultTypeErroHandlingKt$main$$inlined$eager-IoAF18A$1.invokeSuspend(result.kt:43)
	at in.rcard.result.ResultTypeErroHandlingKt$main$$inlined$eager-IoAF18A$1.invoke(result.kt)
	at in.rcard.result.ResultTypeErroHandlingKt$main$$inlined$eager-IoAF18A$1.invoke(result.kt)
	at arrow.core.continuations.DefaultEagerEffect$fold$1.invokeSuspend(EagerEffect.kt:190)
	at arrow.core.continuations.DefaultEagerEffect$fold$1.invoke(EagerEffect.kt)
	at arrow.core.continuations.DefaultEagerEffect$fold$1.invoke(EagerEffect.kt)
	at arrow.core.continuations.DefaultEagerEffect.fold(EagerEffect.kt:192)
	at arrow.core.continuations.ResultKt.toResult(result.kt:10)
	at in.rcard.result.ResultTypeErroHandlingKt.main(ResultTypeErroHandling.kt:122)
	at in.rcard.result.ResultTypeErroHandlingKt.main(ResultTypeErroHandling.kt)

If we want to use some computation that can throw an exception, we can use the runCatching function inside the result DSL:

fun main() {
    result.eager {
        runCatching<Int> {
            throw RuntimeException("Boom!")
        }.bind()
    }
}

However, sometimes we want to map errors in custom types that don’t belong to the Throwable hierarchy. For example, we can map a NoSuchElementException to a JobNotFound type or any rich and meaningful type we want. To do this, we need another strategy to handle errors. It’s time to introduce the Either type.

Type-safe Error Handling: The Either Type

Let’s now introduce the Either type for error handling. Kotlin doesn’t ship the Either type with the standard SDK. We need Arrow to add it to the game. The structure of Either<E, A> is that of an Algebraic Data Type (ADT). In detail, it’s a sum type that can contain either a value A wrapped in the type Right<A> or a value E wrapped in a type Left<E>. It’s common to associate Left instances with the result of a failed computation and Right instances with the result of a successful calculation. The Either type is defined as follows:

// Arrow SDK
public sealed class Either<out A, out B>
public data class Left<out A> constructor(val value: A) : Either<A, Nothing>()
public data class Right<out B> constructor(val value: B) : Either<Nothing, B>()

The Either type is a sealed class, so it cannot be extended outside the Arrow library, and the compiler can check if all the possible cases are handled in a when expression.

Since we can now use any type to represent errors, we can create an ADT on error causes. For example, we can define a JobError sealed class and extend it with the JobNotFound and GenericError classes:

sealed interface JobError
data class JobNotFound(val jobId: JobId) : JobError
data class GenericError(val cause: String) : JobError

Let’s see how to create an Either instance. The Left and Right classes have a constructor that takes a single parameter. Here’s an example of how to create a Right instance:

val appleJobId = JobId(1)
val appleJob: Either<JobError, Job> = Right(JOBS_DATABASE[appleJobId]!!)

Here, we forced the type of the left part of the Either to be JobError. Notice that the constructor returns an Either with the left part defined as Nothing. The compiler allows us to do this because the Nothing type is a subtype of any other type, and the Either<A, B> is covariant on the left part since it’s defined using the out keyword (we already saw variance in previous articles on Scala, Demystifying Variance Positions in Scala).

Now, we can create our Left type instance:

val jobNotFound: Either<JobError, Job> = Left(JobNotFound(appleJobId))

For those who prefer extension functions, Arrow provides the left and right functions to create Left and Right instances:

val anotherAppleJob = JOBS_DATABASE[appleJobId]!!.right()
val anotherJobNotFound: Either<JobError, Job> = JobNotFound(appleJobId).left()

Since Arrow defines the Either type as a sealed class, we can use the when expression to handle all the possible cases taking advantage of the smart casting. For example, in the following printSalaryfunction, we can access the value attribute of the Right instance without any explicit cast:

fun printSalary(maybeJob: Either<JobError, Job>) = when (maybeJob) {
    is Right -> println("Job salary is ${maybeJob.value.salary}")
    is Left -> println("No job found")
}

If we want to extract the contained value from an Either, we have some functions. The getOrNull function returns a nullable type containing the value if it’s a Right instance. We can use it if we want to discard the error:

val appleJobOrNull: Job? = appleJob.getOrNull()

Similarly, we can transform an Either instance into an Option instance using the getOrNone function:

val maybeAppleJob: Option<Job> = appleJob.getOrNone()

Then, the getOrElse function lets us extract the value contained in a Right instance or a default value if it’s a Left instance:

val jobCompany: String = appleJob.map { it.company.name }.getOrElse { "Unknown company" }

The getOrElse function takes a lambda with the error as a parameter, so we can use it to react differently to different errors:

val jobCompany2: String =
    appleJob.map { it.company.name }.getOrElse { jobError ->
        when (jobError) {
            is JobNotFound -> "Job not found"
            is GenericError -> "Generic error"
        }
}

Using typed errors has many advantages:

  1. We can use the type system to check if all the possible cases are handled.
  2. The possible causes of failure are listed directly in the function’s signature as the left part of the Either type. Understanding the possible causes of failure lets us build better tests and error-handling strategies.
  3. Typed errors compose better than exceptions.

To prove the above advantages, as we previously did for the Result type, it’s time to use the Either type in our example. Let’s change the Jobs module to return an Either type instead of a Result type:

interface Jobs {

    fun findById(id: JobId): Either<JobError, Job>
}

Here we are using the JobError ADT we defined so far. At this point, we can know precisely how the function can fail by looking at the signature. Now, we can implement the LiveJobs class:

class LiveJobs : Jobs {

    override fun findById(id: JobId): Either<JobError, Job> =
        try {
            JOBS_DATABASE[id]?.right() ?: JobNotFound(id).left()
        } catch (e: Exception) {
            GenericError(e.message ?: "Unknown error").left()
        }
}

As we might expect, we’re wrapping the happy path with a Right instance and all the available error cases with a Left instance. We are treating the absence of a job as a logic error, and we’re wrapping it with a JobNotFound object using the recommended and idiomatic syntax:

value?.right() ?: error.left()

On the other hand, we catch all the exceptions and wrap them in a GenericError instance. The pattern of catching exceptions and wrapping them in a Left instance is so common that Arrow provides the catch function to do it for us in the companion object of the Either type:

@JvmStatic
@JvmName("tryCatch")
public inline fun <R> catch(f: () -> R): Either<Throwable, R> =
  try {
    f().right()
  } catch (t: Throwable) {
    t.nonFatalOrThrow().left()
  }

The nonFatalOrThrow function checks whether the exception should be handled. The fatal exceptions are the following and their subclasses:

  • VirtualMachineError
  • ThreadDeath
  • InterruptedException
  • LinkageError
  • ControlThrowable
  • CancellationException

The subtypes of these errors should not be caught. For example, CancellationException should not be caught because it’s used by Kotlin to cancel coroutines, and catching it can break normal functioning of coroutines.

Then, we can rewrite the LiveJobs class using the catch function:

class LiveJobs : Jobs {

    override fun findById(id: JobId): Either<JobError, Job> = catch {
        JOBS_DATABASE[id]
    }.mapLeft { GenericError(it.message ?: "Unknown error") }
     .flatMap { maybeJob -> maybeJob?.right() ?: JobNotFound(id).left() }
}

Wait. We introduced a bunch of new functions here. Let’s see them in detail. First, the Either type is right-based, which means that Right is assumed to be the default case to operate on. If it is Left, operations like map, flatMap, return the Left value unchanged. In this case, we applied the flatMap function to check if the retrieved job was null, eventually creating a Left value using the pattern we saw a moment ago.

Moreover, we introduced the mapLeft function. This function is similar to the map function but applies to the Left part of the Either type. In this case, we’re mapping Throwable exceptions to a GenericError object. The mapLeft function is defined as follows:

// Arrow SDK
public inline fun <C> mapLeft(f: (A) -> C): Either<C, B> =
    fold({ Left(f(it)) }, { Right(it) })

As we can see, the definition of the mapLeft function allows us to introduce another essential function, the fold function. We already saw this function in the Result type, and we can use it to transform both the Left and Right instances of the Either class into a target type. The fold function is defined as follows:

// Arrow SDK
public inline fun <C> fold(ifLeft: (left: A) -> C, ifRight: (right: B) -> C): C =
    when (this) {
        is Right -> ifRight(value)
        is Left -> ifLeft(value)
    }

The fold function wraps around the when expression. It’s crucial in the library, and many of the getOr* are implemented using it. For example, let’s say we want to get the salary of a job, whether it’s a Left or a Right instance. We can use the fold function and return a default value if the job is not found:

val jobSalary: Salary = jobNotFound.fold({ Salary(0.0) }, { it.salary })

The same thing can be done using a composition of map and getOrElse functions:

val jobSalary2: Salary = jobNotFound.map { it.salary }.getOrElse { Salary(0.0) }

Composing Either Instances

It’s time to talk about how to compose different Either instances. As you might imagine, since the Either type is a monad on the right type, we can use the map and flatMap functions to compose different instances (remember, monads have a single type parameters, while the Either type has two of them).

We will again implement the getSalaryGapWithMax function, using the Either type to handle errors. First, we need to add the findAll function to our Jobs module:

interface Jobs {

    // Omissis
    fun findAll(): Either<JobError, List<Job>>
}

class LiveJobs : Jobs {

    // Omissis
    override fun findAll(): Either<JobError, List<Job>> =
        JOBS_DATABASE.values.toList().right()
}

Then, we can use map and flatMap to compose the findAll and findById functions and implement the getSalaryGapWithMax function. As we did for the Result type, we define a utility function getting the maximum salary from a list of jobs, this time using an Either instance as a result:

private fun List<Job>.maxSalary(): Either<GenericError, Salary> =
    if (this.isEmpty()) {
        GenericError("No jobs found").left()
    } else {
        this.maxBy { it.salary.value }.salary.right()
    }

Then, we can assemble all the pieces together in our first version of the getSalaryGapWithMax function:

class JobsService(private val jobs: Jobs) {

    fun getSalaryGapWithMax(jobId: JobId): Either<JobError, Double> =
        jobs.findById(jobId).flatMap { job ->
            jobs.findAll().flatMap { jobs ->
                jobs.maxSalary().map { maxSalary ->
                    (maxSalary.value - job.salary.value)
                }
            }
        }
}

Apart from the type used to express failures, the getSalaryGapWithMax function is similar to the one we implemented using the Result type or the Option type in part one. Another thing similar to the previous implementations is the pain of reading such code. We have a lot of nested calls, no monadic list-comprehension support, and it’s not easy to understand what’s going on.

As we might guess, Arrow offers a DSL to simplify the composition of Either instances, and it’s called either. The either.eager DSL is the non-suspending counterpart:

// Arrow SDK
public object either {
    public inline fun <E, A> eager(noinline f: suspend EagerEffectScope<E>.() -> A): Either<E, A> =
        // Omissis...

    public suspend operator fun <E, A> invoke(f: suspend EffectScope<E>.() -> A): Either<E, A> =
        // Omissis...
}

Both the DSL are builders for two different scopes they defined as receivers, respectively arrow.core.continuations.EagerEffectScope<A>, and arrow.core.continuations.EffectScope<A>. Let’s try to make the getSalaryGapWithMax function more readable using the either DSL:

fun getSalaryGapWithMax2(jobId: JobId): Either<JobError, Double> = either.eager {
    println("Searching for the job with id $jobId")
    val job = jobs.findById(jobId).bind()
    println("Job found: $job")
    println("Getting all the available jobs")
    val jobsList = jobs.findAll().bind()
    println("Jobs found: $jobsList")
    println("Searching for max salary")
    val maxSalary = jobsList.maxSalary().bind()
    println("Max salary found: $maxSalary")
    maxSalary.value - job.salary.value
}

The either DSL gives us access to the bind member extension function on the EagerEffectScope to extract Right values from an Either instance or to short-circuit the entire computation if a Left instance is found. The bind function is defined as follows:

// Arrow SDK
public interface EagerEffectScope<in R> {

    // Omissis...
    public suspend fun <B> Either<R, B>.bind(): B =
        when (this) {
            is Either.Left -> shift(value)
            is Either.Right -> value
        }
}

Nothing new in here. If we run the getSalaryGapWithMax2 function with the JobId(42), the execution will be short-circuited after the call to the jobs.findById(jobId) statement, and we get the following output:

Searching for the job with id JobId(value=42)

Similarly, we have access to the ensureNotNull extension function, which short-circuits the computation if a null value is found, and it’s defined as follows:

// Arrow SDK
@OptIn(ExperimentalContracts::class)
public suspend fun <R, B : Any> EagerEffectScope<R>.ensureNotNull(value: B?, shift: () -> R): B {
    contract { returns() implies (value != null) }
    return value ?: shift(shift())
}

To demonstrate the ensureNotNull function, let’s try to implement a variant of the getSalaryGapWithMax function using a new version of the extension function maxSalary we implemented before:

private fun List<Job>.maxSalary2(): Salary? = this.maxBy { it.salary.value }.salary

The above version of the function returns a nullable Salary object instead of an Either. We can use the ensureNotNull function to short-circuit the computation if a null value is found in the getSalaryGapWithMax function:

fun getSalaryGapWithMax3(jobId: JobId): Either<JobError, Double> = either.eager {
    val job = jobs.findById(jobId).bind()
    val jobsList = jobs.findAll().bind()
    val maxSalary = ensureNotNull(jobsList.maxSalary2()) { GenericError("No jobs found") }
    maxSalary.value - job.salary.value
}

If the jobsList.maxSalary2() statement returns a null value, we short-circuit the computation with a Left instance containing a GenericError.

The ensure extension function is similar to the ensureNotNull function but works with a predicate instead of a nullable value. The ensure function is defined as follows:

// Arrow SDK
public suspend fun ensure(condition: Boolean, shift: () -> R): Unit =
    if (condition) Unit else shift(shift())

We can use the ensure function when implementing smart constructors. For example, let’s implement a pimped version of the Salary type containing a smart constructor, which checks if the given value is a positive integer:

object NegativeAmount : JobError

object EitherJobDomain {

    @JvmInline
    value class Salary private constructor(val value: Double) {

        companion object {
            operator fun invoke(value: Double): Either<JobError, Salary> = either.eager {
                ensure(value >= 0.0) { NegativeAmount }
                Salary(value)
            }
        }
    }
}

We use the ensure function to short-circuit the computation if the given value is negative. We can quickly test the smart constructor and check if it works as expected:

fun main() {
    val salaryOrError: Either<JobError, Salary> = Salary(-1.0)
    println(salaryOrError)
}

The above code produces the following expected output if executed:

Either.Left(in.rcard.either.NegativeAmount@246b179d)

What if we have to accumulate many errors, for example, while creating an object? The Either type in version 1.1.5 of Arrow does not fit this need. In fact, the Validated type suits better this use case. However, in the next version of Arrow, 1.2.0, the Validated class will be deprecated. In the next part of this series, we will learn how to accumulate errors directly using the new version of the Either type.

And that’s all, folks!

Conclusion

In this second part of the series dedicated to error handling in Kotlin, we introduced the Result and the Eithertype. These types represent both the happy and error paths, unlike the types we saw in the first part of the series. We explored their APIs in deep and saw which features the Arrow library offers us to simplify the composition of Result and Either instances. It’s time to recap what we’ve learned so far. We can use nullable types and the Option type if we are not interested in the possible error path of a computation. In Kotlin, such types are quite similar. If we want to know the cause of an error, we can use the Result type. Here, we use the subclasses of the Throwable type to express the cause. Finally, we use the Either type to avoid the Throwable type and handle errors using a hierarchy of custom-typed errors. In the last part of this series, we will introduce the upcoming features of the next version of the Arrow library, 1.2.0, which will further simplify the functional handling of errors.

If you found this article (or the first part) too difficult, you can quickly get the experience you need by following the complete Kotlin Essentials course on Rock the JVM.