Gen

sealed abstract class Gen[+T] extends Serializable

A generator produces values for Props

A generator produces values for Props

This module provides:

  1. Definitions for non-arbitrary generators,
  2. Factories to construct generators,
  3. Methods to modify a generator, and
  4. Various combinators for producing generators of values for more complex data types.

Explicit generators aren't required to write Props:

Prop.forAll { (n: Int) =>
 n == n
}

The Prop above is defined with parameters only and without an explicit generator, because generators are implicitly provided by Arbitrary for various data types.

However, it's not uncommon to need to write explicit custom generators:

val genInt: Gen[Int] = Gen.choose(1,10)
Prop.forAll(genInt) { (n: Int) =>
 n == n
}

This is a simple definition of a generator for booleans:

val genBool: Gen[Boolean] = Gen.oneOf(true,false)

The above definition isn't necessary, though. The same boolean generator is defined in Arbitrary as an implicit declaration for automatically parameterizing Props. Instead, use use a generator that is defined in Arbitrary with the polymorphic method Arbitrary.arbitrary and an explicit type parameter:

val genBool: Gen[Boolean] = Arbitrary.arbitrary[Boolean]

Alternatively, this is a boolean generator, but one that always produces true:

val genBool = Gen.const(true)

This is a generator of booleans that is true at a 2-to-1 ratio:

val genBool = Gen.frequency(2 -> true, 1 -> false)

This is a boolean generator that will produce true 75% of the time:

val genBool = Gen.prob(0.75)

For more information on designing custom generators and the motivations for doing so, see chapter 6, ''Generators in Detail'', of the book ''ScalaCheck: The Definitive Guide'' (2013) by Rickard Nilsson published by Artima Press.

This is an example of a custom generator for integers:

val genSmallInt: Gen[Int] = Gen.choose(-100,100)

This can be used to generate different collections of zero or more small integers:

val genListOfInts: Gen[List[Int]] = Gen.listOf(genSmallInt)

val genSeqOfInts: Gen[Seq[Int]] = Gen.someOf(-100 to 100)

val genVectorOfInts: Gen[Vector[Int]] = Gen.containerOf[Vector,Int](genSmallInt)

val genMap: Gen[Map[Int,Boolean]] = Gen.mapOf(Gen.zip(genSmallInt, genBool))

val genOptionalInt: Gen[Option[Int]] = Gen.option(genSmallInt)

Or collections of one or more small integers:

val genListOfInts: Gen[List[Int]] = Gen.nonEmptyListOf(genSmallInt)

val genSeqOfInts: Gen[Seq[Int]] = Gen.atLeastOne(-100 to 100)

val genVectorOfInts: Gen[Vector[Int]] = Gen.nonEmptyContainerOf[Vector,Int](genSmallInt)

val genMap: Gen[Map[Int,Boolean]] = Gen.nonEmptyMap(Gen.zip(genSmallInt, genBool))

val genOptionalInt: Gen[Option[Int]] = Gen.some(genSmallInt)

The class methods for Gen should be familiar with those in the Scala collections API:

  • map - Apply a function to generated values
  • flatMap - Apply a function that returns a generator
  • filter - Use values that satisfy a predicate

The Gen class also supports for-comprehensions to compose complex generators:

val genPerson = for {
 firstName <- Gen.oneOf("Alan", "Ada", "Alonzo")
 lastName <- Gen.oneOf("Lovelace", "Turing", "Church")
 age <- Gen.choose(0,100) if (age >= 18)
} yield Person(firstName, lastName, age)

Constructors and factories for generators:

  • const - Always generates a single value
  • oneOf - Generate a value from a list of values
  • atLeastOne - Generate a collection with at least one value from a list
  • someOf - Generate a collection with zero or more values from a list
  • choose - Generate numeric values in an (inclusive) range
  • frequency - Choose from multiple values with a weighted distribution

Combinators of generators:

  • buildableOf - Generates a collection with a generator
  • buildableOfN - Generates a collection of at most ''n'' elements
  • nonEmptyBuildableOf - Generates a non-empty collection
  • containerOf - Generates a collection with a generator
  • containerOfN - Generates a collection of at most ''n'' elements
  • nonEmptyContainerOf - Generates a non-empty collection
  • either - Generate a disjoint union of scala.util.Either
  • infiniteLazyList - Generates an infinite lazy list
  • infiniteStream - Generates an infinite stream
  • listOf - Generates a list of random length
  • listOfN - Generates a list of at most ''n'' elements
  • nonEmptyListOf - Generates a non-empty list of random length.
  • mapOf - Generates a scala.collection.Map
  • mapOfN - Generates a scala.collection.Map with at most ''n'' elements
  • nonEmptyMap - Generates a non-empty map of random length
  • option - Generate values of scala.Some and scala.None
  • pick - A generator that randomly picks ''n'' elements from a list
  • sequence - Sequences generators.
  • some - A generator of scala.Some
  • someOf - A generator that picks a random number of elements from a list
  • stringOf - Generate string of characters
  • stringOfN - Generate string of at most ''n'' characters

Methods for working with Gen internals:

  • resize - Creates a resized version of a generator
  • parameterized - Generator with the parameters
  • size - Generate with the value of the default size parameter
  • sized - Build a generator using the default size parameter

Methods for probabilistic generators:

  • exponential - Generate numbers according to an exponential distribution
  • gaussian - Generates numbers according to a Gaussian distribution
  • geometric - Generates numbers according to a geometric distribution
  • poisson - Generates numbers according to a Poisson distribution
  • prob - Generates a boolean for the probability of true

Definitions for generating various, non-arbitrary, common values of strings and characters:

  • alphaChar - Generates an alpha character
  • alphaStr - Generates a string of alpha characters
  • numChar - Generates a numerical character
  • numStr - Generates a string of digits
  • alphaNumChar - Generates an alphanumerical character
  • alphaNumStr - Generates a string of alphanumerical characters
  • alphaLowerChar - Generates a lower-case alpha character
  • alphaLowerStr - Generates a string of lower-case alpha characters
  • alphaUpperChar - Generates an upper-case alpha character
  • alphaUpperStr - Generates a string of upper-case alpha characters
  • asciiChar - Generates an ASCII character
  • asciiStr - Generates a string of ASCII characters
  • identifier - Generates an identifier
  • uuid - Generates a UUID
  • hexChar - Generates a character of a hexadecimal digit
  • hexStr - Generates a string of hexadecimal digits

Definitions for generating arbitrary values of commonly used types in Scala are defined elsewhere, see Arbitrary.

There are a couple of factory methods that are for advanced uses of generators:

  • delay - Generate a value of an expression by-name
  • lzy - Lazily generate a value of an expression
  • fail - Fail to generate any values of a type
  • recursive - A fixed point generator
  • resultOf - Generate values with a function or class
  • zip - Generate tuples
Companion
object
trait Serializable
class Object
trait Matchable
class Any

Type members

Classlikes

case class RetryUntilException(n: Int) extends RuntimeException
final class WithFilter(p: T => Boolean)

A class supporting filtered operations.

A class supporting filtered operations.

Value members

Concrete methods

def !=[U](g: Gen[U]): Prop
def !==[U](g: Gen[U]): Prop
def :|(l: String): Gen[T]

Put a label on the generator to make test reports clearer

Put a label on the generator to make test reports clearer

def :|(l: Symbol): Gen[T]

Put a label on the generator to make test reports clearer

Put a label on the generator to make test reports clearer

def ==[U](g: Gen[U]): Prop

Returns a new property that holds if and only if both this and the given generator generates the same result, or both generators generate no result.

Returns a new property that holds if and only if both this and the given generator generates the same result, or both generators generate no result.

def apply(p: Parameters, seed: Seed): Option[T]

Evaluate this generator with the given parameters

Evaluate this generator with the given parameters

def doPureApply(p: Parameters, seed: Seed, retries: Int): R[T]
def filter(p: T => Boolean): Gen[T]

Create a new generator that uses this generator to produce a value that fulfills the given condition. If the condition is not fulfilled, the generator fails (returns None). Also, make sure that the provided test property is side-effect free, e.g. it should not use external vars.

Create a new generator that uses this generator to produce a value that fulfills the given condition. If the condition is not fulfilled, the generator fails (returns None). Also, make sure that the provided test property is side-effect free, e.g. it should not use external vars.

def filterNot(p: T => Boolean): Gen[T]

Create a new generator that uses this generator to produce a value that doesn't fulfill the given condition. If the condition is fulfilled, the generator fails (returns None). Also, make sure that the provided test property is side-effect free, e.g. it should not use external vars.

Create a new generator that uses this generator to produce a value that doesn't fulfill the given condition. If the condition is fulfilled, the generator fails (returns None). Also, make sure that the provided test property is side-effect free, e.g. it should not use external vars.

def flatMap[U](f: T => Gen[U]): Gen[U]

Create a new generator by flat-mapping the result of this generator

Create a new generator by flat-mapping the result of this generator

def label(l: String): Gen[T]

Put a label on the generator to make test reports clearer

Put a label on the generator to make test reports clearer

def map[U](f: T => U): Gen[U]

Create a new generator by mapping the result of this generator

Create a new generator by mapping the result of this generator

def pureApply(p: Parameters, seed: Seed, retries: Int): T

Evaluate this generator with the given parameters.

Evaluate this generator with the given parameters.

The generator will attempt to generate a valid T value. If a valid value is not produced it may retry several times, determined by the retries parameter (which defaults to 100).

If all the retries fail it will throw a Gen.RetrievalError exception.

def retryUntil(p: T => Boolean, maxTries: Int): Gen[T]

Create a generator that calls this generator repeatedly until the given condition is fulfilled. The generated value is then returned. Make sure that the provided test property is side-effect free (it should not use external vars).

Create a generator that calls this generator repeatedly until the given condition is fulfilled. The generated value is then returned. Make sure that the provided test property is side-effect free (it should not use external vars).

If the generator fails more than maxTries, a RetryUntilException will be thrown.

def retryUntil(p: T => Boolean): Gen[T]

Create a generator that calls this generator repeatedly until the given condition is fulfilled. The generated value is then returned. Make sure that the provided test property is side-effect free (it should not use external vars).

Create a generator that calls this generator repeatedly until the given condition is fulfilled. The generated value is then returned. Make sure that the provided test property is side-effect free (it should not use external vars).

If the generator fails more than 10000 times, a RetryUntilException will be thrown. You can call retryUntil with a second parameter to change this number.

def sample: Option[T]
def suchThat(f: T => Boolean): Gen[T]

Create a new generator that uses this generator to produce a value that fulfills the given condition. If the condition is not fulfilled, the generator fails (returns None). Also, make sure that the provided test property is side-effect free, e.g. it should not use external vars. This method is identical to [Gen.filter].

Create a new generator that uses this generator to produce a value that fulfills the given condition. If the condition is not fulfilled, the generator fails (returns None). Also, make sure that the provided test property is side-effect free, e.g. it should not use external vars. This method is identical to [Gen.filter].

def withFilter(p: T => Boolean): WithFilter

Creates a non-strict filtered version of this generator.

Creates a non-strict filtered version of this generator.

def withPerturb(f: Seed => Seed): Gen[T]

Perform some RNG perturbation before generating

Perform some RNG perturbation before generating

def |:(l: String): Gen[T]

Put a label on the generator to make test reports clearer

Put a label on the generator to make test reports clearer

def |:(l: Symbol): Gen[T]

Put a label on the generator to make test reports clearer

Put a label on the generator to make test reports clearer