libraryDependencies  = "io.getkyo" %% "kyo-prelude"       % "<version>"
libraryDependencies  = "io.getkyo" %% "kyo-core"          % "<version>"
libraryDependencies  = "io.getkyo" %% "kyo-direct"        % "<version>"
libraryDependencies  = "io.getkyo" %% "kyo-combinators"   % "<version>"
libraryDependencies  = "io.getkyo" %% "kyo-sttp"          % "<version>"
libraryDependencies  = "io.getkyo" %% "kyo-tapir"         % "<version>"
libraryDependencies  = "io.getkyo" %% "kyo-zio"           % "<version>"
libraryDependencies  = "io.getkyo" %% "kyo-caliban"       % "<version>"
libraryDependencies  = "io.getkyo" %% "kyo-cache"         % "<version>"
libraryDependencies  = "io.getkyo" %% "kyo-stats-otel"    % "<version>"
libraryDependencies  = "io.getkyo" %% "kyo-tag"           % "<version>"
libraryDependencies  = "io.getkyo" %% "kyo-data"          % "<version>"
libraryDependencies  = "io.getkyo" %% "kyo-scheduler"     % "<version>"
libraryDependencies  = "io.getkyo" %% "kyo-scheduler-zio" % "<version>"

libraryDependencies  = "io.getkyo" %%  "kyo-prelude"     % "<version>"
libraryDependencies  = "io.getkyo" %%% "kyo-core"        % "<version>"
libraryDependencies  = "io.getkyo" %%% "kyo-direct"      % "<version>"
libraryDependencies  = "io.getkyo" %%  "kyo-combinators" % "<version>"
libraryDependencies  = "io.getkyo" %%% "kyo-sttp"        % "<version>"
libraryDependencies  = "io.getkyo" %%  "kyo-tag"         % "<version>"
libraryDependencies  = "io.getkyo" %%  "kyo-data"        % "<version>"

import kyo.*

// 'Int' pending 'Abort[Maybe.Empty]'
Int < Abort[Maybe.Empty]

// 'String' pending 'Abort[Maybe.Empty]' and 'IO'
String < (Abort[Maybe.Empty] & IO)

import kyo.*

// An 'Int' is also an 'Int < Any'
val a: Int < Any = 1

// Since there are no pending effects,
// the computation can produce a pure value
val b: Int = a.eval

import kyo.*

// Kyo still supports both `map`
// and `flatMap`.
def example1(
    a: Int < IO,
    b: Int < Abort[Exception]
): Int < (IO & Abort[Exception]) =
    a.flatMap(v => b.map(_   v))

// But using only `map` is recommended
// since it functions like `flatMap` due
// to effect widening.
def example2(
    a: Int < IO,
    b: Int < Abort[Exception]
): Int < (IO & Abort[Exception]) =
    a.map(v => b.map(_   v))

import kyo.*

// An example computation that
// produces 'Unit'.
val a: Unit < IO =
    IO(println("hello"))

// Use 'andThen'.
val b: String < IO =
    a.andThen("test")

import kyo.*

// An 'Int' with an empty effect set (`Any`)
val a: Int < Any =
    1

// Widening the effect set from empty (`Any`)
// to include `IO`
val b: Int < IO =
    a

// Further widening the effect set to include
// both `IO` and `Abort[Exception]`
val c: Int < (IO & Abort[Exception]) =
    b

// Directly widening a pure value to have
// `IO` and `Abort[Exception]`
val d: Int < (IO & Abort[Exception]) =
    42

import kyo.*

// The function expects a parameter with both
// 'IO' and 'Abort' effects pending
def example1(v: Int < (IO & Abort[Exception])) =
    v.map(_   1)

// A value with only the 'Abort' effect can be
// automatically widened to include 'IO'
def example2(v: Int < Abort[Exception]) =
    example1(v)

// A pure value can also be automatically widened
def example3 = example1(42)

import kyo.*

val a: Int < Abort[Exception] = 42

// Handle the 'Options' effect
// 'Result' is similar to 'Either'
val b: Result[Exception, Int] < Any =
    Abort.run(a)

// Retrieve pure value as there are no more pending effects
val c: Result[Exception, Int] =
    b.eval

import kyo.*

def abortStringFirst(a: Int < (Abort[String] & Abort[Exception])): Result[Exception, Result[String, Int]] =
    val b: Result[String, Int] < Abort[Exception] =
        Abort.run[String](a)
    val c: Result[Exception, Result[String, Int]] < Any =
        Abort.run[Exception](b)
    c.eval
end abortStringFirst

// Note how 'Abort' supports type unions. This method's parameter is equivalent to 'abortStringFirst'.
def abortExceptionFirst(a: Int < Abort[String | Exception]): Result[String, Result[Exception, Int]] =
    val b: Result[Exception, Int] < Abort[String] =
        Abort.run[Exception](a)
    val c: Result[String, Result[Exception, Int]] < Any =
        Abort.run[String](b)
    c.eval
end abortExceptionFirst

// The sequence in which effects are handled has a significant impact on the outcome.
// This is especially true for effects that can short-circuit the computation.

val ex = new Exception

// If the computation doesn't short-circuit, only the order of nested types in the result changes.
// This code uses a pure value as the computation as an example.
val a: Result[Exception, Result[String, Int]] = abortStringFirst(1)    // Result.Success(Result.Success(1))
val b: Result[String, Result[Exception, Int]] = abortExceptionFirst(1) // Result.Success(Result.Success(1))

// If there's short-circuiting, the resulting value can be different depending on the handling order.
abortStringFirst(Abort.fail("test"))    // Result.Success(Result.Fail("test"))
abortStringFirst(Abort.fail(ex))        // Result.Fail(ex)

abortExceptionFirst(Abort.fail("test")) // Result.Fail("test")
abortExceptionFirst(Abort.fail(ex))     // Result.Success(Result.Fail(ex))

import kyo.*

// Use the direct syntax
val a: String < (Abort[Exception] & IO) =
    defer {
        val b: String =
            await(IO("hello"))
        val c: String =
            await(Abort.get(Right("world")))
        b   " "   c
    }

// Equivalent desugared
val b: String < (Abort[Exception] & IO) =
    IO("hello").map { b =>
        Abort.get(Right("world")).map { c =>
            b   " "   c
        }
    }

import kyo.*

// This code fails to compile
val a: Int < IO =
    defer {
        // Incorrect usage of a '<' value
        // without 'await'
        IO(println(42))
        42
    }

import kyo.*

defer {
    // Pure expression
    val a: Int = 5

    // Effectful value
    val b: Int = await(IO(10))

    // Control flow
    val c: String =
        if await(IO(true)) then "True branch" else "False branch"

    // Logical operations
    val d: Boolean =
        await(IO(true)) && await(IO(false))

    val e: Boolean =
        await(IO(true)) || await(IO(true))

    // Loop (for demonstration; this loop
    // won't execute its body)
    while await(IO(false)) do "Looping"

    // Pattern matching
    val matchResult: String =
        await(IO(1)) match
            case 1 => "One"
            case _ => "Other"
}

import kyo.*

object MyApp extends KyoApp:
    // Use 'run' blocks to execute Kyo computations.
    // The execution of the run block is lazy to avoid
    // field initialization issues.
    run {
        for
            _            <- Console.println(s"Main args: $args")
            currentTime  <- Clock.now
            _            <- Console.println(s"Current time is: $currentTime")
            randomNumber <- Random.nextInt(100)
            _            <- Console.println(s"Generated random number: $randomNumber")
        yield
        // The produced value can be of any type and is
        // automatically printed to the console.
        "example"
    }
end MyApp

import kyo.*

// An example computation
val a: Int < IO =
    IO(Math.cos(42).toInt)

// Avoid! Run the application with a specific timeout
val b: Int =
    KyoApp.run(2.minutes)(a)

// Avoid! Run the application without specifying a timeout
val c: Int =
    KyoApp.run(a)

import kyo.*

// The 'get' method "extracts" the value
// from an 'Either' (right projection)
val a: Int < Abort[String] =
    Abort.get(Right(1))

// short-circuiting via 'Left'
val b: Int < Abort[String] =
    Abort.get(Left("failed!"))

// short-circuiting via 'Fail'
val c: Int < Abort[String] =
    Abort.fail("failed!")

// 'catching' automatically catches exceptions
val d: Int < Abort[Exception] =
    Abort.catching(throw new Exception)

import kyo.*

def aSideEffect = 1 // placeholder

// 'apply' is used to suspend side effects
val a: Int < IO =
    IO(aSideEffect)

import kyo.*

val a: Int < IO =
    IO(42)

// ** Avoid 'IO.run', use 'KyoApp' instead. **
val b: Int =
    IO.run(a).eval
// ** Avoid 'IO.run', use 'KyoApp' instead. **

import kyo.*

// Computation with 'Env' and then 'IO' suspensions
val a: Int < (Env[Int] & IO) =
    Env.get[Int].map { v =>
        IO {
            println(v)
            v
        }
    }

// ** Avoid 'IO.runLazy', use 'KyoApp' instead. **
// Handle the 'IO' effect lazily
val b: Int < Env[Int] =
    IO.runLazy(a)
// ** Avoid 'IO.runLazy', use 'KyoApp' instead. **

// Since the computation is suspended with the
// 'Env' effect first, the lazy 'IO' execution
// will be triggered once 'Env' is handled
val c: Int =
    Env.run(42)(b).eval

import kyo.*

// Given an interface
trait Database:
    def count: Int < IO

// The 'Env' effect can be used to summon an instance.
// Note how the computation produces a 'Database' but at the
// same time requires a 'Database' from its environment
val a: Database < Env[Database] =
    Env.get[Database]

// Use the 'Database' to obtain the count
val b: Int < (Env[Database] & IO) =
    a.map(_.count)

// A 'Database' mock implementation
val db = new Database:
    def count = 1

// Handle the 'Env' effect with the mock database
val c: Int < IO =
    Env.run(db)(b)

// Additionally, a computation can require multiple values
// from its environment.

// A second interface to be injected
trait Cache:
    def clear: Unit < IO

// A computation that requires two values
val d: Unit < (Env[Database] & Env[Cache] & IO) =
    Env.get[Database].map { db =>
        db.count.map {
            case 0 =>
                Env.get[Cache].map(_.clear)
            case _ =>
                ()
        }
    }

import kyo.*

// Define some services
trait Database:
    def query: String < IO

trait Cache:
    def get: Int < IO

trait Logger:
    def log(msg: String): Unit < IO

// Create layers for each service
val dbLayer: Layer[Database, Any] =
    Layer {
        new Database:
            def query = IO("DB result")
    }

val cacheLayer: Layer[Cache, Any] =
    Layer {
        new Cache:
            def get = IO(42)
    }

val loggerLayer: Layer[Logger, Any] =
    Layer {
        new Logger:
            def log(msg: String) = IO(println(msg))
    }

// The `Layer.init` method provides a way to create a layer from multiple sub-layers, automatically 
// resolving dependencies between them. It can be used for more complex compositions as well
val appLayer: Layer[Database & Cache & Logger, Any] =
    Layer.init[Database & Cache & Logger](dbLayer, cacheLayer, loggerLayer)

// Use the composed layer in a computation
val computation: String < (Env[Database] & Env[Cache] & Env[Logger] & IO) =
    for
        db     <- Env.get[Database]
        cache  <- Env.get[Cache]
        logger <- Env.get[Logger]
        _      <- logger.log("Starting query")
        result <- db.query
        _      <- logger.log(s"Query result: $result")
        cached <- cache.get
        _      <- logger.log(s"Cached value: $cached")
    yield result

// Run the computation with the composed layer
val result: String < (IO & Memo) =
    Env.runLayer(appLayer)(computation)

// The 'Memo' effect is used by Layer to ensure components are initialized only once
val result2: String < IO =
    Memo.run(result)

import kyo.*

trait Database:
    def query: String < IO

trait UserService:
    def getUser(id: Int): String < IO

trait EmailService:
    def sendEmail(to: String, content: String): Unit < IO

// Define layers
val dbLayer: Layer[Database, IO] = Layer {
    new Database:
        def query = IO("DB result")
}

val userServiceLayer: Layer[UserService, Env[Database] & IO] =
    Layer.from { (db: Database) =>
        new UserService:
            def getUser(id: Int) = db.query.map(result => s"User $id: $result")
    }

val emailServiceLayer: Layer[EmailService, IO] = Layer {
    new EmailService:
        def sendEmail(to: String, content: String) =
            IO(println(s"Email sent to $to: $content"))
}

// Example of `to`: Output of dbLayer is used as input for userServiceLayer
val dbToUserService: Layer[UserService, IO] =
    dbLayer.to(userServiceLayer)

// Example of `and`: Combines dbLayer and emailServiceLayer in parallel
val dbAndEmail: Layer[Database & EmailService, IO] =
    dbLayer.and(emailServiceLayer)

// Example of `using`: Similar to `to`, but keeps both Database and UserService
val dbUsingUserService: Layer[Database & UserService, IO] =
    dbLayer.using(userServiceLayer)

// Complex composition
val fullAppLayer: Layer[Database & UserService & EmailService, IO] =
    dbLayer.using(userServiceLayer).and(emailServiceLayer)

// Use the full app layer
val computation: Unit < (Env[Database] & Env[UserService] & Env[EmailService] & IO) =
    for
        db           <- Env.get[Database]
        userService  <- Env.get[UserService]
        emailService <- Env.get[EmailService]
        _            <- db.query
        user         <- userService.getUser(1)
        _            <- emailService.sendEmail("[email protected]", s"User data: $user")
    yield ()

val result: Unit < (IO & Memo) =
    Env.runLayer(fullAppLayer)(computation)

import kyo.*

// Local need to be initialized with a default value
val myLocal: Local[Int] =
    Local.init(42)

// The 'get' method returns the current value of the local
val a: Int < IO =
    myLocal.get

// The 'let' method assigns a value to a local within the
// scope of a computation. This code produces 43 (42   1)
val b: Int < IO =
    myLocal.let(42)(a.map(_   1))

import java.io.Closeable
import kyo.*

class Database extends Closeable:
    def count: Int < IO = 42
    def close()          = {}

// The `acquire` method accepts any object that
// implements Java's `Closeable` interface
val db: Database < (Resource & Async) =
    Resource.acquire(new Database)

// Use `run` to handle the effect, while also
// closing the resources utilized by the
// computationation
val b: Int < Async =
    Resource.run(db.map(_.count))

// The `ensure` method provides a low-level API to handle the finalization of
// resources directly. The `acquire` method is implemented in terms of `ensure`.

// Example method to execute a function on a database
def withDb[T](f: Database => T < Async): T < (Resource & Async) =
    // Initializes the database ('new Database' is a placeholder)
    IO(new Database).map { db =>
        // Registers `db.close` to be finalized
        Resource.ensure(db.close).map { _ =>
            // Invokes the function
            f(db)
        }
    }

// Execute a function
val c: Int < (Resource & Async) =
    withDb(_.count)

// Close resources
val d: Int < Async =
    Resource.run(c)

import kyo.*

// Evaluate each of the provided `Seq`s.
// Note how 'get' takes a 'Seq[T]'
// and returns a 'T < Choice'
val a: Int < Choice =
    Choice.get(Seq(1, 2, 3, 4))

// 'filter' discards the current element if
// a condition is not met. Produces a 'Seq(1, 2)'
// since values greater than 2 are dropped
val b: Int < Choice =
    a.map(v => Choice.dropIf(v > 2).map(_ => v))

// 'drop' unconditionally discards the
// current choice. Produces a 'Seq(42)'
// since only the value 1 is transformed
// to 42 and all other values are dropped
val c: Int < Choice =
    b.map {
        case 1 => 42
        case _ => Choice.drop
    }

// Handle the effect to evaluate all elements
// and return a 'Seq' with the results
val d: Seq[Int] < Any =
    Choice.run(c)

import kyo.*

// Iteratively increment an 'Int' value
// until it reaches 5
val a: Int < Any =
    Loop(1)(i =>
        if i < 5 then Loop.continue(i   1)
        else Loop.done(i)
    )

// Transform with multiple input values
val b: Int < Any =
    Loop(1, 1)((i, j) =>
        if i   j < 5 then Loop.continue(i   1, j   1)
        else Loop.done(i   j)
    )

// Mixing 'IO' with 'Loop'
val d: Int < IO =
    Loop(1)(i =>
        if i < 5 then
            IO(println(s"Iteration: $i")).map(_ => Loop.continue(i   1))
        else
            Loop.done(i)
    )

// Mixing 'Console' with 'Loop'
val e: Int < IO =
    Loop(1)(i =>
        if i < 5 then
            Console.println(s"Iteration: $i").map(_ => Loop.continue(i   1))
        else
            Loop.done(i)
    )

import kyo.*

// Version 1: Regular while loop
def whileLoop: Int =
    var i   = 0
    var sum = 0
    while i < 10 do
        sum  = i
        i  = 1
    sum
end whileLoop

// Version 2: Recursive method loop
def recursiveLoop(i: Int = 0, sum: Int = 0): Int =
    if i < 10 then
        recursiveLoop(i   1, sum   i)
    else
        sum

// Version 3: Using Loop
def loopsVersion: Int < Any =
    Loop(0, 0)((i, sum) =>
        if i < 10 then
            Loop.continue(i   1, sum   i)
        else
            Loop.done(sum)
    )

import kyo.*

// Print a message every 3 iterations
val a: Int < IO =
    Loop.indexed(1)((idx, i) =>
        if idx < 10 then
            if idx % 3 == 0 then
                Console.println(s"Iteration $idx").map(_ => Loop.continue(i   1))
            else
                Loop.continue(i   1)
        else
            Loop.done(i)
    )

// Terminate the loop after 5 iterations
val b: Int < Any =
    Loop.indexed(1, 1)((idx, i, j) =>
        if idx < 5 then Loop.continue(i   1, j   1)
        else Loop.done(i   j)
    )

// Use the index to calculate the next value
val c: Int < Any =
    Loop.indexed(1, 1, 1)((idx, i, j, k) =>
        if idx < 5 then Loop.continue(i   idx, j   idx, k   idx)
        else Loop.done(i   j   k)
    )

import kyo.*

val fibonacci: Int => Int < Memo = 
    Memo { n =>
        if (n <= 1) n
        else
            for
                a <- fibonacci(n - 1)
                b <- fibonacci(n - 2)
            yield a   b
    }

val result: (Int, Int) < Memo = 
    Memo.run {
        for
            fib10 <- fibonacci(10)
            fib11 <- fibonacci(11)
        yield (fib10, fib11)
    }

val result2: (Int, Int) < Any =
    Memo.run(result)

import kyo.*

// Construct chunks
val a: Chunk[Int] = Chunk(1, 2, 3)
val b: Chunk[Int] = Chunk.from(Seq(4, 5, 6))

// Perform O(1) operations
val c = a.append(4)
val d = b.take(2)
val e = c.dropLeft(1)

// Perform O(n) operations
val f = d.map(_.toString)
val g = e.filter(_ % 2 == 0)

import kyo.*

val a: Chunk[Int] = Chunk(1, 2, 3, 4, 5)

// Efficient O(1) operations with Chunk
val b: Chunk[Int] = a.append(6)
val c: Chunk[Int] = a.take(3)
val d: Chunk[Int] = a.dropLeft(2)

import kyo.*

val a: Chunk.Indexed[Int] =
    Chunk(1, 2, 3, 4, 5).toIndexed

// Efficient O(1) operations with Chunk.Indexed
val b: Int                 = a(2)
val c: Int                 = a.head
val d: Chunk.Indexed[Int] = a.tail

import kyo.*

// Creation
val a: Chunk[Int] = Chunk(1, 2, 3)
val b: Chunk[Int] = Chunk.from(Seq(4, 5, 6))

// Size and emptiness
val c: Int     = a.size
val d: Boolean = a.isEmpty

// Take and drop
val e: Chunk[Int] = a.take(2)
val f: Chunk[Int] = a.dropLeft(1)

// Append and last
val g: Chunk[Int] = a.append(4)
val h: Int        = a.last

// Concatenation
val i: Chunk[Int] = a.concat(b)

// Copying to arrays
val n: Array[Int] = a.toArray

// Flatten a nested chunk
val o: Chunk[Int] =
    Chunk(a, b).flatten

// Obtain sequentially distict elements.
// Outputs: Chunk(1, 2, 3, 1)
val p: Chunk[Int] =
    Chunk(1, 1, 2, 3, 3, 1, 1).changes

import kyo.*

// Create a stream from a sequence
val a: Stream[Int, Any] =
    Stream.init(Seq(1, 2, 3, 4, 5))

// Map over stream elements
val b: Stream[String, Any] =
    a.map(_.toString)

// Filter stream elements
val c: Stream[Int, Any] =
    a.filter(_ % 2 == 0)

// Take a limited number of elements
val d: Stream[Int, Any] =
    a.take(3)

// Drop elements from the beginning
val e: Stream[Int, Any] =
    a.drop(2)

// Concatenate streams
val f: Stream[Int, Any] =
    a.concat(Stream.init(Seq(6, 7, 8)))

// FlatMap over stream elements
val g: Stream[Int, Any] =
    a.flatMap(x => Stream.init(Seq(x, x * 2)))

// Collect stream results into a Chunk
val h: Chunk[Int] < Any =
    a.run

// Process stream elements without collecting results
val i: Unit < Any =
    a.runDiscard

// Fold over stream elements
val j: Int < Any =
    a.runFold(0)(_   _)

// Process each element with side effects
val k: Unit < IO =
    a.runForeach(Console.println(_))

import kyo.*

case class Config(someConfig: String)

// Stream with IO effect
val a: Stream[String, IO] =
    Stream.init(Seq("file1.txt", "file2.txt"))
        .map(fileName => IO(scala.io.Source.fromFile(fileName).mkString))

// Stream with Abort effect
val b: Stream[Int, Abort[NumberFormatException]] =
    Stream.init(Seq("1", "2", "abc", "3"))
        .map(s => Abort.catching[NumberFormatException](s.toInt))

def fetchUserData(config: Config, username: String): Seq[String] < Async =
    Seq(s"user data for $username") // mock implementation

// Combining multiple effects
val c: Stream[String, Env[Config] & Async] =
    Stream.init(Seq("user1", "user2", "user3"))
        .flatMap { username =>
            Stream.init {
                for
                    config <- Env.get[Config]
                    result <- fetchUserData(config, username)
                yield result
            }
        }

// Run the stream and handle effects
val result: Chunk[String] < (Env[Config] & Async) =
    c.run

import kyo.*

// Get the current value
val a: Int < Var[Int] =
    Var.get[Int]

// Set a new value and return the previous one
val b: Int < Var[Int] =
    Var.set(10)

// Update the state and return the new value
val c: Int < Var[Int] =
    Var.update[Int](v => v   1)

// Use in a computation
val d: String < Var[Int] =
    Var.use[Int](v => v.toString)

// Handle the effect and discard state
val e: String < Any =
    Var.run(10)(d)

import kyo.*

// A computation that uses `Var` to maintain a counter
def counter[S](n: Int): Int < (Var[Int] & S) =
    if n <= 0 then
        Var.get[Int]
    else
        for
            _      <- Var.update[Int](_   1)
            result <- counter(n - 1)
        yield result

// Initialize the counter with an initial state
val a: Int < Any =
    Var.run(0)(counter(10))

import kyo.*

// Add a value
val a: Emit.Ack < Emit[Int] =
    Emit(42)

// Add multiple values
val b: String < Emit[Int] =
    for
        _ <- Emit(1)
        _ <- Emit(2)
        _ <- Emit(3)
    yield "r"

// Handle the effect to obtain the
// accumulated log and the result.
// Evaluates to `(Chunk(1, 2, 3), "r")`
val c: (Chunk[Int], String) < Any =
    Emit.run(b)

import kyo.*

val a: String < (Emit[Int] & Emit[String]) =
    for
        _ <- Emit(1)
        _ <- Emit("log")
        _ <- Emit(2)
    yield "result"

// Note how `run` requires an explicit type
// parameter when a computation has multiple
// pending `Sum`s.
val b: (Chunk[Int], (Chunk[String], String)) < Any =
    Emit.run[Int](Emit.run[String](a))

import java.io.Closeable
import kyo.*

class Database extends Closeable:
    def count: Int < IO = 42
    def close()          = {}

// Initialize an aspect that takes a 'Database' and returns
// an 'Int', potentially performing 'IO' effects
val countAspect: Aspect[Database, Int, IO] =
    Aspect.init[Database, Int, IO]

// The method 'apply' activates the aspect for a computation
def count(db: Database): Int < IO =
    countAspect(db)(_.count)

// To bind an aspect to an implementation, first create a new 'Cut'
val countPlusOne =
    new Cut[Database, Int, IO]:
        // The first param is the input of the computation and the second is
        // the computation being handled
        def apply[S](v: Database < S)(f: Database => Int < IO) =
            v.map(db => f(db).map(_   1))

// Bind the 'Cut' to a computation with the 'let' method.
// The first param is the 'Cut' and the second is the computation
// that will run with the custom binding of the aspect
def example(db: Database): Int < IO =
    countAspect.let(countPlusOne) {
        count(db)
    }

// If an aspect is bound to multiple `Cut` implementations, the order of
// their execution is determined by the sequence in which they are scoped
// within the computation.

// Another 'Cut' implementation
val countTimesTen =
    new Cut[Database, Int, IO]:
        def apply[S](v: Database < S)(f: Database => Int < IO) =
            v.map(db => f(db).map(_ * 10))

// First bind 'countPlusOne' then 'countTimesTen'
// the result will be (db.count   1) * 10
def example1(db: Database) =
    countAspect.let(countPlusOne) {
        countAspect.let(countTimesTen) {
            count(db)
        }
    }

// First bind 'countTimesTen' then 'countPlusOne'
// the result will be (db.count * 10)   1
def example2(db: Database) =
    countAspect.let(countTimesTen) {
        countAspect.let(countPlusOne) {
            count(db)
        }
    }

// Cuts can also be composed via `andThen`
def example3(db: Database) =
    countAspect.let(countTimesTen.andThen(countPlusOne)) {
        count(db)
    }

import kyo.*

// Read a line from the console
val a: String < IO =
    Console.readln

// Print to stdout
val b: Unit < IO =
    Console.print("ok")

// Print to stdout with a new line
val c: Unit < IO =
    Console.println("ok")

// Print to stderr
val d: Unit < IO =
    Console.printErr("fail")

// Print to stderr with a new line
val e: Unit < IO =
    Console.printlnErr("fail")

// Explicitly specifying the 'Console' implementation
val f: Unit < IO =
    Console.let(Console.live)(e)

import java.time.Instant
import kyo.*

// Obtain the current time
val a: Instant < IO =
    Clock.now

// Run with an explicit 'Clock'
val c: Instant < IO =
    Clock.let(Clock.live)(a)

import kyo.*

// Generate a random 'Int'
val a: Int < IO = Random.nextInt

// Generate a random 'Int' within a bound
val b: Int < IO = Random.nextInt(42)

// A few method variants
val c: Long < IO    = Random.nextLong
val d: Double < IO  = Random.nextDouble
val e: Boolean < IO = Random.nextBoolean
val f: Float < IO   = Random.nextFloat
val g: Double < IO  = Random.nextGaussian

// Obtain a random value from a sequence
val h: Int < IO =
    Random.nextValue(List(1, 2, 3))

// Explicitly specify the `Random` implementation
val k: Int < IO =
    Random.let(Random.live)(h)

import kyo.*

// Log provide trace, debug, info,
// warn, and error method variants.
val a: Unit < IO =
    Log.error("example")

// Each variant also has a method overload
// that takes a 'Throwable' as a second param
val d: Unit < IO =
    Log.error("example", new Exception)

import kyo.*
import kyo.stats.*

// Initialize a Stat instance
// for a scope path
val stats: Stat =
    Stat.initScope("my_application", "my_module")

// Initialize a counter
val a: Counter =
    stats.initCounter("my_counter")

// It's also possible to provide
// metadata when initializing
val b: Histogram =
    stats.initHistogram(
        name = "my_histogram",
        description = "some description"
    )

// Gauges take a by-name function to
// be observed periodically
val c: Gauge =
    stats.initGauge("free_memory") {
        Runtime.getRuntime().freeMemory().toDouble
    }

import kyo.*

val stats2: Stat =
    Stat.initScope("my_application", "my_module")

// Some example computation
val a: Int < IO =
    IO(42)

// Trace the execution of the
// `a` example computation
val b: Int < IO =
    stats2.traceSpan("my_span")(a)

import kyo.*

// Create a Path instance representing a path
val path: Path = Path("tmp", "file.txt")

// Read the entire contents of a file as a String
val content: String < IO =
    path.read

// Write a String to a file
val writeResult: Unit < IO =
    path.write("Hello, world!")

// Check if a path exists
val exists: Boolean < IO =
    path.exists

// Create a directory
val createDir: Unit < IO =
    Path("tmp", "test").mkDir

import kyo.*

val path: Path = Path("tmp", "file.txt")

// Read a file as a stream of lines
val lines: Stream[String, Resource & IO] =
    path.readLinesStream()

// Process the stream
val result: Unit < (Resource & Console & Async) =
    lines.map(line => Console.println(line)).runDiscard

// Walk a directory tree
val tree: Stream[Path, IO] =
    Path("tmp").walk

// Process each file in the tree
val processedTree: Unit < (Console & Async) =
    tree.map(file => file.read.map(content => Console.println(s"File: ${file}, Content: $content"))).runDiscard

import kyo.*

// Create a stream of bytes
val bytes: Stream[Byte, IO] = Stream.init(Seq[Byte](1, 2, 3))

// Write the stream to a file
val sinkResult: Unit < (Resource & IO) =
    bytes.sink(Path("path", "to", "file.bin"))

import kyo.*

// Create a simple command
val command: Process.Command = Process.Command("echo", "Hello, World!")

// Spawn the process and obtain the result
val result: String < IO = command.text

import kyo.*

class MyClass extends KyoApp:
    run {
        Console.println(s"Executed with args: $args")
    }
end MyClass

// Spawn a new JVM process
val jvmProcess: Process < IO =
    Process.jvm.spawn(classOf[MyClass], List("arg1", "arg2"))

import java.io.File
import java.nio.file.Path
import kyo.*

// Create a piped command
val pipedCommand = Process.Command("echo", "Hello, World!").pipe(Process.Command("wc", "-w"))

// Modify the command's environment and working directory
val modifiedCommand = pipedCommand.env(Map("VAR" -> "value")).cwd(Path.of("/path/to/dir"))

// Spawn the modified command
val modifiedResult: String < IO = modifiedCommand.text

import java.io.File
import kyo.*

// Create a command with custom input and output
val command = Process.Command("my-command")
    .stdin(Process.Input.fromString("input data"))
    .stdout(Process.Output.FileRedirect(new File("output.txt")))
    .stderr(Process.Output.Inherit)

import kyo.*

// Fork a computation. The parameter is
// taken by reference and automatically
// suspended with 'IO'
val a: Fiber[Nothing, Int] < IO =
    Async.run(Math.cos(42).toInt)

// It's possible to "extract" the value of a
// 'Fiber' via the 'get' method. This is also
// referred as "joining the fiber"
val b: Int < Async =
    a.map(_.get)

import kyo.*

// An example computation
val a: Int < IO =
    IO(Math.cos(42).toInt)

// There are method overloadings for up to four
// parallel computations. Paramters taken by
// reference
val b: (Int, String) < Async =
    Async.parallel(a, "example")

// Alternatively, it's possible to provide
// a 'Seq' of computations and produce a 'Seq'
// with the results
val c: Seq[Int] < Async =
    Async.parallel(Seq(a, a.map(_   1)))

// The 'Fiber.parallel' method is similar but
// it doesn't automatically join the fibers and
// produces a 'Fiber[Seq[T]]'
val d: Fiber[Nothing, Seq[Int]] < IO =
    Fiber.parallel(Seq(a, a.map(_   1)))

import kyo.*

// An example computation
val a: Int < IO =
    IO(Math.cos(42).toInt)

// There are method overloadings for up to four
// computations. Pameters taken by reference
val b: Int < Async =
    Async.race(a, a.map(_   1))

// It's also possible to to provide a 'Seq'
// of computations
val c: Int < Async =
    Async.race(Seq(a, a.map(_   1)))

// 'Fiber.race' produces a 'Fiber' without
// joining it
val d: Fiber[Nothing, Int] < IO =
    Fiber.race(Seq(a, a.map(_   1)))

import kyo.*

// A computation that sleeps for 1s
val a: Unit < Async =
    Async.sleep(1.second)

// Times out and interrupts the provided
// computation in case it doesn't produce
// a result within 1s
val b: Int < (Abort[Timeout] & Async) =
    Async.timeout(1.second)(Math.cos(42).toInt)

import kyo.*
import scala.concurrent.Future

// An example 'Future' instance
val a: Future[Int] = Future.successful(42)

// Transform a 'Future' into a 'Fiber'
val b: Fiber[Nothing, Int] < IO =
    Fiber.fromFuture(a)

import kyo.*
import scala.concurrent.*

// An example fiber
val a: Fiber[Nothing, Int] = Fiber.success(42)

// Check if the fiber is done
val b: Boolean < IO =
    a.isDone

// Instance-level version of 'Async.get'
val c: Int < Async =
    a.get

// Avoid this low-level API to attach a
// a callback to a fiber
val d: Unit < IO =
    a.onComplete(println(_))

// A variant of `get` that returns a `Result`
// with the failed or successful result
val e: Result[Nothing, Int] < Async =
    a.getResult

// Try to interrupt/cancel a fiber
val f: Boolean < IO =
    a.interrupt

// Transforms a fiber into a Scala 'Future'
val h: Future[Int] < IO =
    a.toFuture

// 'Fiber' provides a monadic API with both
// 'map' and 'flatMap'
val i: Fiber[Nothing, Int] < IO =
    a.flatMap(v => Fiber.success(v   1))

import kyo.*

// An example computation with fibers
val a: Int < Async =
    Async.run(Math.cos(42).toInt).map(_.get)

// Avoid handling 'Async' directly
// Note how the code has to handle the
// 'IO' effect and then handle 'Async'
val b: Fiber[Nothing, Int] < IO =
    Async.run(IO.runLazy(a))

// The 'runAndBlock' method accepts
// arbitrary pending effects but relies
// on thread blocking and requires a timeout
val c: Int < (Abort[Timeout] & IO) =
    Async.runAndBlock(5.seconds)(a)

import kyo.*

// Initialize a promise
val a: Promise[Nothing, Int] < IO =
    Promise.init[Nothing, Int]

// Try to fulfill a promise
val b: Boolean < IO =
    a.map(_.complete(Result.success(42)))

// Fullfil the promise with
// another fiber
val c: Boolean < IO =
    a.map(fiber => Async.run(1).map(fiber.become(_)))

import kyo.*
import scala.concurrent.duration.*

// Define a computation that might fail
val unreliableComputation: Int < Abort[Exception] =
    Abort.catching[Exception](throw new Exception("Temporary failure"))

// Customize retry policy
val customPolicy = Retry.Policy.default
    .limit(5)
    .exponential(100.millis, maxBackoff = 5.seconds)

val a: Int < (Abort[Exception] & Async) =
    Retry[Exception](customPolicy)(unreliableComputation)

// Use a custom policy builder
val b: Int < (Abort[Exception] & Async) =
    Retry[Exception] { policy =>
        policy
            .limit(10)
            .backoff(attempt => (attempt * 100).millis)
    }(unreliableComputation)

import kyo.*

// A bounded channel rejects new
// elements once full
val a: Queue[Int] < IO =
    Queue.init(capacity = 42)

// Obtain the number of items in the queue
// via the method 'size' in 'Queue'
val b: Int < IO =
    a.map(_.size)

// Get the queue capacity
val c: Int < IO =
    a.map(_.capacity)

// Try to offer a new item
val d: Boolean < IO =
    a.map(_.offer(42))

// Try to poll an item
val e: Maybe[Int] < IO =
    a.map(_.poll)

// Try to 'peek' an item without removing it
val f: Maybe[Int] < IO =
    a.map(_.peek)

// Check if the queue is empty
val g: Boolean < IO =
    a.map(_.isEmpty)

// Check if the queue is full
val h: Boolean < IO =
    a.map(_.isFull)

// Drain the queue items
val i: Seq[Int] < IO =
    a.map(_.drain)

// Close the queue. If successful,
// returns a Some with the drained
// elements
val j: Maybe[Seq[Int]] < IO =
    a.map(_.close)

import kyo.*

// Avoid `Queue.unbounded` since if queues can
// grow without limits, the GC overhead can make
// the system fail
val a: Queue.Unbounded[Int] < IO =
    Queue.initUnbounded()

// A 'dropping' queue discards new entries
// when full
val b: Queue.Unbounded[Int] < IO =
    Queue.initDropping(capacity = 42)

// A 'sliding' queue discards the oldest
// entries if necessary to make space for new
// entries
val c: Queue.Unbounded[Int] < IO =
    Queue.initSliding(capacity = 42)

// Note how 'dropping' and 'sliding' queues
// return 'Queue.Unbounded`. It provides
// an additional method to 'add' new items
// unconditionally
val d: Unit < IO =
    c.map(_.add(42))

import kyo.*

// Initialize a bounded queue with a
// Multiple Producers, Multiple
// Consumers policy
val a: Queue[Int] < IO =
    Queue.init(
        capacity = 42,
        access = Access.Mpmc
    )

import kyo.*

// A 'Channel' is initialized
// with a fixed capacity
val a: Channel[Int] < IO =
    Channel.init(capacity = 42)

// It's also possible to specify
// an 'Access' policy
val b: Channel[Int] < IO =
    Channel.init(
        capacity = 42,
        access = Access.Mpmc
    )

import kyo.*

// An example channel
val a: Channel[Int] < IO =
    Channel.init(capacity = 42)

// Adds a new item to the channel.
// If there's no capacity, the fiber
// is automatically suspended until
// space is made available
val b: Unit < Async =
    a.map(_.put(42))

// Takes an item from the channel.
// If the channel is empty, the fiber
// is suspended until a new item is
// made available
val c: Int < Async =
    a.map(_.take)

// 'putFiber' returns a `Fiber` that
// will complete once the put completes
val d: Fiber[Nothing, Unit] < IO =
    a.map(_.putFiber(42))

// 'takeFiber' also returns a fiber
val e: Fiber[Nothing, Int] < IO =
    a.map(_.takeFiber)

// Closes the channel. If successful,
// returns a Some with the drained
// elements. All pending puts and takes
// are automatically interrupted
val f: Maybe[Seq[Int]] < IO =
    a.map(_.close)

import kyo.*
import kyo.Hub.Listener

// Initialize a Hub with a buffer
val a: Hub[Int] < IO =
    Hub.init[Int](3)

// Hub provide APIs similar to
// channels: size, offer, isEmpty,
// isFull, putFiber, put
val b: Boolean < IO =
    a.map(_.offer(1))

// But reading from hubs can only
// happen via listener. Listeners
// only receive messages sent after
// their cration. To create call
// `listen`:
val c: Listener[Int] < IO =
    a.map(_.listen)

// Each listener can have an
// additional message buffer
val d: Listener[Int] < IO =
    a.map(_.listen(bufferSize = 3))

// Listeners provide methods for
// receiving messages similar to
// channels: size, isEmpty, isFull,
// poll, takeFiber, take
val e: Int < Async =
    d.map(_.take)

// A listener can be closed
// individually. If successful,
// a Some with the backlog of
// pending messages is returned
val f: Maybe[Seq[Int]] < IO =
    d.map(_.close)

// If the Hub is closed, all
// listeners are automatically
// closed. The returned backlog
// only include items pending in
// the hub's buffer. The listener
// buffers are discarded
val g: Maybe[Seq[Int]] < IO =
    a.map(_.close)

import kyo.*

// 'mutex': One computation at a time
val a: Meter < IO =
    Meter.initMutex

// 'semaphore': Limit concurrent tasks
val b: Meter < IO =
    Meter.initSemaphore(concurrency = 42)

// 'rateLimiter': Tasks per time window
val c: Meter < IO =
    Meter.initRateLimiter(
        rate = 10,
        period = 1.second
    )

// 'pipeline': Combine multiple 'Meter's
val d: Meter < IO =
    Meter.pipeline(a, b, c)

import kyo.*

// An example 'Meter'
val a: Meter < IO =
    Meter.initMutex

// Get available permits
val b: Int < IO =
    a.map(_.available)

// Check for available permit
val c: Boolean < IO =
    a.map(_.isAvailable)

// Use 'run' to execute tasks
// respecting meter limits
val d: Int < Async =
    a.map(_.run(Math.cos(42).toInt))

// 'tryRun' executes if a permit is
// available; returns 'None' otherwise
val e: Maybe[Int] < IO =
    a.map(_.tryRun(Math.cos(42).toInt))

import kyo.*

// An example computation to
// be scheduled
val a: Unit < IO =
    IO(())

// Schedule a delayed task
val b: TimerTask < IO =
    Timer.schedule(delay = 1.second)(a)

// Recurring task with
// intial delay
val c: TimerTask < IO =
    Timer.scheduleAtFixedRate(
        initialDelay = 1.minutes,
        period = 1.minutes
    )(a)

// Recurring task without
// initial delay
val d: TimerTask < IO =
    Timer.scheduleAtFixedRate(
        period = 1.minutes
    )(a)

// Schedule with fixed delay between tasks
val e: TimerTask < IO =
    Timer.scheduleWithFixedDelay(
        initialDelay = 1.minutes,
        period = 1.minutes
    )(a)

// without initial delay
val f: TimerTask < IO =
    Timer.scheduleWithFixedDelay(
        period = 1.minutes
    )(a)

// Specify the 'Timer' explictly
val i: TimerTask < IO =
    Timer.let(Timer.live)(f)

import kyo.*

// Example TimerTask
val a: TimerTask < IO =
    Timer.schedule(1.second)(())

// Try to cancel the task
val b: Boolean < IO =
    a.map(_.cancel)

// Check if the task is cancelled
val c: Boolean < IO =
    a.map(_.isCancelled)

// Check if the task is done
val d: Boolean < IO =
    a.map(_.isDone)

import kyo.*

// Initialize a latch with 'n' permits
val a: Latch < IO =
    Latch.init(3)

// Await until the latch releases
val b: Unit < Async =
    a.map(_.await)

// Release a permit from the latch
val c: Unit < IO =
    a.map(_.release)

// Get the number of pending permits
val d: Int < IO =
    a.map(_.pending)

import kyo.*

// Initialize atomic variables
val aInt: AtomicInt < IO =
    AtomicInt.init(0)
val aLong: AtomicLong < IO =
    AtomicLong.init(0L)
val aBool: AtomicBoolean < IO =
    AtomicBoolean.init(false)
val aRef: AtomicRef[String] < IO =
    AtomicRef.init("initial")

// Fetch values
val b: Int < IO =
    aInt.map(_.get)
val c: Long < IO =
    aLong.map(_.get)
val d: Boolean < IO =
    aBool.map(_.get)
val e: String < IO =
    aRef.map(_.get)

// Update values
val f: Unit < IO =
    aInt.map(_.set(1))
val g: Unit < IO =
    aLong.map(_.lazySet(1L))
val h: Boolean < IO =
    aBool.map(_.cas(false, true))
val i: String < IO =
    aRef.map(_.getAndSet("new"))

import kyo.*

// Initialize Adder
val longAdder: LongAdder < IO =
    LongAdder.init
val doubleAdder: DoubleAdder < IO =
    DoubleAdder.init

// Adding values
val a: Unit < IO =
    longAdder.map(_.add(10L))
val b: Unit < IO =
    doubleAdder.map(_.add(10.5))

// Increment and Decrement LongAdder
val c: Unit < IO =
    longAdder.map(_.increment)
val d: Unit < IO =
    longAdder.map(_.decrement)

// Fetch summed values
val e: Long < IO =
    longAdder.map(_.get)
val f: Double < IO =
    doubleAdder.map(_.get)

// Resetting the adders
val g: Unit < IO =
    longAdder.map(_.reset)
val h: Unit < IO =
    doubleAdder.map(_.reset)

import kyo.*

// Note that 'Debug' requires a separate import
import kyo.debug.*

// Wraps a computation, printing the source code location,
// and the result (or exception) of the computation
val a: Int < IO =
    Debug {
        IO(42)
    }

// Similar to `apply`, but also prints intermediate steps
// of the computation, providing a trace of execution
val b: Int < IO =
    Debug.trace {
        IO(41).map(_   1)
    }

// Allows printing of specific values along with their 
// variable names, useful for inspecting particular states.
// The return type of 'values' is 'Unit', not an effectful
// computation.
val c: Unit < IO =
    IO {
        val x = 42
        val y = "Hello"
        Debug.values(x, y)
    }

import kyo._

// Create a 'Maybe' value
val a: Maybe[Int] = Maybe(42)

// 'Maybe.empty' represents the absence of a value
val b: Maybe[Int] = Maybe.empty[Int]

// 'Maybe.when' conditionally creates a 'Maybe' value
val c: Maybe[Int] = Maybe.when(true)(42)

// 'Maybe.fromOption' converts an 'Option' to a 'Maybe'
val d: Maybe[Int] = Maybe.fromOption(Some(42))

// 'isEmpty' checks if the 'Maybe' is empty
val e: Boolean = a.isEmpty

// 'isDefined' checks if the 'Maybe' has a value
val f: Boolean = a.isDefined

// 'get' retrieves the value, throwing if empty
val g: Int = a.get

// 'getOrElse' provides a default value if empty
val h: Int = b.getOrElse(0)

// 'fold' applies a function based on emptiness
val i: String = a.fold("Empty")(_.toString)

// 'map' transforms the value if present
val j: Maybe[String] = a.map(_.toString)

// 'flatMap' allows chaining 'Maybe' operations
val k: Maybe[Int] = a.flatMap(v => Maybe(v   1))

// 'filter' conditionally keeps or discards the value
val l: Maybe[Int] = a.filter(_ > 0)

// 'contains' checks if the 'Maybe' contains a value
val m: Boolean = a.contains(42)

// 'exists' checks if a predicate holds for the value
val n: Boolean = a.exists(_ > 0)

// 'foreach' applies a side-effecting function if non-empty
a.foreach(println)

// 'collect' applies a partial function if defined
val o: Maybe[String] = a.collect { case 42 => "forty-two" }

// 'orElse' returns an alternative if empty
val p: Maybe[Int] = b.orElse(Maybe(0))

// 'zip' combines two 'Maybe' values into a tuple
val q: Maybe[(Int, String)] = a.zip(Maybe("hello"))

// 'toOption' converts a 'Maybe' to an 'Option'
val r: Option[Int] = a.toOption

// Using 'Maybe' in a for-comprehension
val s: Maybe[Int] = for {
  x <- Maybe(1)
  y <- Maybe(2)
  if x < y
} yield x   y

// Nesting 'Maybe' values
val nested: Maybe[Maybe[Int]] = Maybe(Maybe(42))
val flattened: Maybe[Int] = nested.flatten

import kyo.*
import kyo.Duration.Units.*

// Create durations using convenient extension methods
val a: Duration = 5.seconds
val b: Duration = 100.millis
val c: Duration = 1.hour

// Perform arithmetic operations
val d: Duration = a   b
val e: Duration = c * 2

// Compare durations
val f: Boolean = a > b
val g: Boolean = c <= 60.minutes

// Convert to different time units
val h: Long = c.toMinutes // 60
val i: Long = a.toMillis  // 5000

// Create durations from various units
val j: Duration = Duration.fromNanos(1000000)
val k: Duration = Duration.fromUnits(2, Weeks)

// Convert to and from Java and Scala durations
import java.time.Duration as JavaDuration
import scala.concurrent.duration.Duration as ScalaDuration

val l: Duration = Duration.fromJava(JavaDuration.ofSeconds(30))
val m: Duration = Duration.fromScala(ScalaDuration(1, "day"))

val n: JavaDuration = c.toJava
val o: ScalaDuration = b.toScala

// Special durations
val p: Duration = Duration.Zero
val q: Duration = Duration.Infinity

// Render duration as a string
val r: String = a.show // "Duration(5000000000 ns)"

import kyo._
import scala.util.Try

// Create a 'Result' from a value
val a: Result[Nothing, Int] = Result.success(42)

// Create a 'Result' from an failure
val b: Result[Exception, Int] = Result.fail(new Exception("Oops"))

// Use 'apply' to create a 'Result' from a block of code
val c: Result[Nothing, Int] = Result(42 / 0)

// 'isSuccess' checks if the 'Result' is a success
val d: Boolean = a.isSuccess

// 'isFail' checks if the 'Result' is a failure
val e: Boolean = b.isFail

// 'get' retrieves the value if successful, otherwise throws
val f: Int = a.get

// 'getOrElse' provides a default value for failures
val g: Int = b.getOrElse(0)

// 'fold' applies a function based on success or failure
val h: String = a.fold(e => "failure "   e)(_.toString)

// 'map' transforms the value if successful
val i: Result[Nothing, String] = a.map(_.toString)

// 'flatMap' allows chaining 'Result' operations
val j: Result[Nothing, Int] = a.flatMap(v => Result.success(v   1))

// 'flatten' removes one level of nesting from a 'Result[Result[T]]'
val k: Result[Nothing, Result[Nothing, Int]] = Result.success(a)
val l: Result[Nothing, Int] = k.flatten

// 'filter' conditionally keeps or discards the value
val m: Result[NoSuchElementException, Int] = a.filter(_ > 0)

// 'recover' allows handling failures with a partial function
val n: Result[Exception, Int] = b.recover { case Result.Fail(_: ArithmeticException) => 0 }

// 'recoverWith' allows handling failures with a partial function returning a 'Result'
val o: Result[Exception, Int] = b.recoverWith { case Result.Fail(_: ArithmeticException) => Result.success(0) }

// 'toEither' converts a 'Result' to an 'Either'
val p: Either[Throwable, Int] = a.toEither

// 'toTry' converts a 'Result' to a 'Try'
val q: Try[Int] = a.toTry

import kyo.*

// Create an empty TypeMap
val empty: TypeMap[Any] = TypeMap.empty

// Constructors for up to 4 elements
val map1: TypeMap[String] = TypeMap("Hello")
val map2: TypeMap[String & Int] = TypeMap("Hello", 42)
val map3: TypeMap[String & Int & Boolean] = TypeMap("Hello", 42, true)
val map4: TypeMap[String & Int & Boolean & Double] = TypeMap("Hello", 42, true, 3.14)

// Add a value to an existing TypeMap
val mapWithNewValue: TypeMap[String & Int] = map1.add(42)

// Retrieve a value from the TypeMap
val str: String = map2.get[String]
val num: Int = map2.get[Int]

// Combine two TypeMaps
val combined: TypeMap[String & Int & Boolean] = map2.union(TypeMap(true))

// Filter the TypeMap to only include subtypes of a given type
val pruned: TypeMap[String] = map2.prune[String]

// Check if the TypeMap is empty and get its size
val isEmpty: Boolean = map2.isEmpty
val size: Int = map2.size

// Get a string representation of the TypeMap
val representation: String = map2.show

import kyo.*

// The 'String' extension methods require a separate import
import kyo.Ansi.*

// Add colors to strings
val redText: String = "Error".red
val blueText: String = "Info".blue

// Add text formatting
val boldText: String = "Important".bold
val underlinedText: String = "Underlined".underline

// Combine colors and formatting
val importantError: String = "Critical Error".red.bold

// Strip ANSI codes from a string
val plainText: String = "\u001b[31mColored\u001b[0m".stripAnsi

// Highlight code snippets
val code = """
def hello(name: String): Unit =
println(s"Hello, $name!")
"""
lazy val highlightedCode: String = Ansi.highlight(code)

// Highlight code with custom header and trailer
lazy val customHighlight: String = 
    Ansi.highlight(
        header = "// File: example.scala",
        code = code,
        trailer = "// End of file",
        startLine = 1
    )