Best Kotest code snippet using io.kotest.property.arbitrary.map.thunk
predef-test.kt
Source:predef-test.kt
...80}81/**82 * Catches `System.err` output, for testing purposes.83 */84fun catchSystemErr(thunk: () -> Unit): String {85 val outStream = ByteArrayOutputStream()86 catchSystemErrInto(outStream, thunk)87 return String(outStream.toByteArray(), StandardCharsets.UTF_8)88}89/**90 * Catches `System.err` output into `outStream`, for testing purposes.91 */92@Synchronized93fun <A> catchSystemErrInto(outStream: OutputStream, thunk: () -> A): A {94 val oldErr = System.err95 val fakeErr = PrintStream(outStream)96 System.setErr(fakeErr)97 return try {98 thunk()99 } finally {100 System.setErr(oldErr)101 fakeErr.close()102 }103}104fun Arb.Companion.throwable(): Arb<Throwable> =105 Arb.string().map(::RuntimeException)106fun <A> Arb.Companion.result(right: Arb<A>): Arb<Result<A>> {107 val failure: Arb<Result<A>> = Arb.throwable().map { e -> Result.failure<A>(e) }108 val success: Arb<Result<A>> = right.map { a -> Result.success(a) }109 return Arb.choice(failure, success)110}111fun <L, R> Arb.Companion.either(left: Arb<L>, right: Arb<R>): Arb<Either<L, R>> {112 val failure: Arb<Either<L, R>> = left.map { l -> l.left() }...
map.kt
Source:map.kt
...24 * Returns a new [TrampolineArb] from the receiver [Arb] which composes the operations of [next] lambda25 * using a trampoline method. This allows [next] function to be executed without exhausting call stack.26 */27internal fun <A, B> Arb<A>.trampoline(next: (Sample<A>) -> Arb<B>): Arb<B> = when (this) {28 is TrampolineArb -> this.thunk(next)29 else -> TrampolineArb(this).thunk(next)30}31/**32 * The [TrampolineArb] is a special Arb that exchanges call stack with heap.33 * In a nutshell, this arb stores command chains to be applied to the original arb inside a list.34 * This technique is an imperative reduction of Free Monads. This eliminates the need of creating intermediate35 * Trampoline Monad and tail-recursive function on those which can be expensive.36 * This minimizes the amount of code and unnecessary object allocation during sample generation in the expense of typesafety.37 *38 * This is an internal implementation. Do not use this TrampolineArb as is and please do not expose this39 * to users outside of the library. For library maintainers, please use the [Arb.trampoline] extension function.40 * The extension function will provide some type-guardrails to workaround the loss of types within this Arb.41 */42@Suppress("UNCHECKED_CAST")43internal class TrampolineArb<A> private constructor(44 private val first: Arb<A>,45 private val commands: List<(Sample<Any>) -> Arb<Any>>46) : Arb<A>() {47 constructor(first: Arb<A>) : this(first, emptyList())48 fun <A, B> thunk(fn: (Sample<A>) -> Arb<B>): TrampolineArb<B> =49 TrampolineArb(50 first,51 commands + (fn as (Sample<Any>) -> Arb<Any>)52 ) as TrampolineArb<B>53 override fun edgecase(rs: RandomSource): A? =54 commands55 .fold(first as Arb<Any>) { currentArb, next ->56 val currentEdge = currentArb.edgecase(rs) ?: currentArb.sample(rs).value57 next(Sample(currentEdge))58 }59 .edgecase(rs) as A?60 override fun sample(rs: RandomSource): Sample<A> =61 commands62 .fold(first as Arb<Any>) { currentArb, next ->...
thunk
Using AI Code Generation
1forAll(::additionIsCommutative)2forAll { (a: Int, b: Int, c: Int) -> (a + b) == (c + b) }3forAll { (a: Int, b: Int, c: Int, d: Int, e: Int, f: Int) -> (a + b + c + d + e + f) == (f + e + d + c + b + a) }4forAll(::additionIsCommutative)5forAll { (a: Int, b: Int, c: Int) -> (a + b) == (c + b) }6forAll { (a: Int, b: Int, c: Int, d: Int, e: Int, f: Int) -> (a + b + c + d + e + f) == (f + e + d + c + b + a) }7forAll(::additionIsCommutative)
thunk
Using AI Code Generation
1) : Arb<String> by arb.map { it + "!" } {2 override fun toString() = "MyArb($arb)"3}4val myArb = MyArb(Arb.string())5) : Arb<String> {6 private val arb2 = arb.map { it + "!" }7 override fun edgecases() = arb2.edgecases()8 override fun sample(rs: RandomSource): Sample<String> = arb2.sample(rs)9 override fun toString() = "MyArb($arb)"10}11val myArb = MyArb(Arb.string())12Arb.map() is a useful method that allows us to map the data generated by an Arb to a different type. It can be used to convert
thunk
Using AI Code Generation
1val arb = Arb . string (). map { it . toInt () } arb . edgecases () shouldBe listOf ( 0 ) arb . values ( 100 ) shouldContain 02val arb = Arb . string (). map { it . toInt () } arb . edgecases () shouldBe listOf ( 0 ) arb . values ( 100 ) shouldContain 03val arb = Arb . string (). map { it . toInt () } arb . edgecases () shouldBe listOf ( 0 ) arb . values ( 100 ) shouldContain 04val arb = Arb . string (). map { it . toInt () } arb . edgecases () shouldBe listOf ( 0 ) arb . values ( 100 ) shouldContain 05val arb = Arb . string (). map { it . toInt () } arb . edgecases () shouldBe listOf ( 0 ) arb . values ( 100 ) shouldContain 06val arb = Arb . string (). map { it . toInt () } arb . edgecases () shouldBe listOf ( 0 ) arb . values ( 100 ) shouldContain 07val arb = Arb . string (). map { it . toInt () } arb . edgecases () shouldBe listOf ( 0 ) arb . values ( 100 ) shouldContain 08val arb = Arb . string (). map { it . toInt () } arb . edgecases () shouldBe listOf ( 0 ) arb . values ( 100 ) shouldContain 09val arb = Arb . string (). map { it . toInt () } arb . edgecases () shouldBe listOf ( 0 ) arb . values ( 100 ) shouldContain 0
thunk
Using AI Code Generation
1 init {2 "should generate a map of size 0" {3 forAll(0..10) { size: Int ->4 val map = MapArbitrary(StringArbitrary(), IntArbitrary()).map { it }.edgecases().first()5 }6 }7 }8}9override fun edgecases(): List<Map<K, V>> {10 val keys = keyArb.edgecases()11 val values = valueArb.edgecases()12 return (0..maxSize).map { size ->13 (0 until size).map { keys[it] to values[it] }.toMap()14 }15}
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