Packages

  • package root
    Definition Classes
    root
  • package zio
    Definition Classes
    root
  • package test

    _ZIO Test_ is a featherweight testing library for effectful programs.

    _ZIO Test_ is a featherweight testing library for effectful programs.

    The library imagines every spec as an ordinary immutable value, providing tremendous potential for composition. Thanks to tight integration with ZIO, specs can use resources (including those requiring disposal), have well- defined linear and parallel semantics, and can benefit from a host of ZIO combinators.

    import zio.test._
    import zio.clock.nanoTime
    import Assertion.isGreaterThan
    
    object MyTest extends DefaultRunnableSpec {
      suite("clock") {
        testM("time is non-zero") {
          assertM(nanoTime, isGreaterThan(0))
        }
      }
    }
    Definition Classes
    zio
  • package mock

    The mock package contains testable versions of all the standard ZIO environment types through the MockClock, MockConsole, MockSystem, and MockRandom modules.

    The mock package contains testable versions of all the standard ZIO environment types through the MockClock, MockConsole, MockSystem, and MockRandom modules. See the documentation on the individual modules for more detail about using each of them.

    If you are using ZIO Test and extending DefaultRunnableSpec a MockEnvironment containing all of them will be automatically provided to each of your tests. Otherwise, the easiest way to use the mocking functionality in ZIO Test is by providing the MockEnvironment to your program.

    import zio.test.mock._
    
    myProgram.provideManaged(mockEnvironmentManaged)

    Then all environmental effects, such as printing to the console or generating random numbers, will be implemented by the MockEnvironment and will be fully testable. When you do need to access the "live" environment, for example to print debugging information to the close, just use the live combinator along with the effect as your normally would.

    If you are only interested in one of the mocking modules for your application, you can also access them a la carte through the make method on each module. Each mock module requires some data on initialization. Default data is included for each as DefaultData.

    import zio.test.mock._
    
    myProgram.provideM(MockConsole.make(MockConsole.DefaultData))

    Finally, you can create a Mock object that implements the mock interface directly using the makeMock method. This can be useful when you want to access some mocking functionality without using the environment type.

    import zio.test.mock._
    
    for {
      mockRandom <- MockRandom.makeMock(MockRandom.DefaultData)
      n          <- mockRandom.nextInt
    } yield n

    This can also be useful when you are creating a more complex environment to provide the implementation for mock services that you mix in.

    Definition Classes
    test
  • Live
  • MockClock
  • MockConsole
  • MockEnvironment
  • MockRandom
  • MockSystem

trait MockRandom extends Random

MockRandom allows for deterministically testing effects involving randomness.

MockRandom operates in two modes. In the first mode, MockRandom is a purely functional pseudo-random number generator. It will generate pseudo-random values just like scala.util.Random except that no internal state is mutated. Instead, methods like nextInt describe state transitions from one random state to another that are automatically composed together through methods like flatMap. The random seed can be set using setSeed and MockRandom is guaranteed to return the same sequence of values for any given seed. This is useful for deterministically generating a sequence of pseudo-random values and powers the property based testing functionality in ZIO Test.

In the second mode, MockRandom maintains an internal buffer of values that can be "fed" with methods such as feedInts and then when random values of that type are generated they will first be taken from the buffer. This is useful for verifying that functions produce the expected output for a given sequence of "random" inputs.

import zio.random._
import zio.test.mock.MockRandom

for {
  _ <- MockRandom.feedInts(4, 5, 2)
  x <- random.nextInt(6)
  y <- random.nextInt(6)
  z <- random.nextInt(6)
} yield x + y + z == 11

MockRandom will automatically take values from the buffer if a value of the appropriate type is available and otherwise generate a pseudo-random value, so there is nothing you need to do to switch between the two modes. Just generate random values as you normally would to get pseudo-random values, or feed in values of your own to get those values back. You can also use methods like clearInts to clear the buffer of values of a given type so you can fill the buffer with new values or go back to pseuedo-random number generation.

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  1. abstract val random: Service[Any]
    Definition Classes
    MockRandom → Random

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Inherited from Random

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