Value Members

1.  def live[E, A](zio: ZIO[zio.ZEnv, E, A]): ZIO[Live, E, A]

   Provides an effect with the "real" environment as opposed to the test environment.

   Provides an effect with the "real" environment as opposed to the test environment. This is useful for performing effects such as timing out tests, accessing the real time, or printing to the real console.

2.  val liveEnvironment: Layer[Nothing, zio.ZEnv]
3.  val testEnvironment: Layer[Nothing, TestEnvironment]
4.  def withLive[R, E, E1, A, B](zio: ZIO[R, E, A])(f: (IO[E, A]) ⇒ ZIO[zio.ZEnv, E1, B]): ZIO[R with Live, E1, B]

   Transforms this effect with the specified function.

   Transforms this effect with the specified function. The test environment will be provided to this effect, but the live environment will be provided to the transformation function. This can be useful for applying transformations to an effect that require access to the "real" environment while ensuring that the effect itself uses the test environment.

   withLive(test)(_.timeout(duration))

5.  object Live

   The Live trait provides access to the "live" environment from within the test environment for effects such as printing test results to the console or timing out tests where it is necessary to access the real environment.

   The Live trait provides access to the "live" environment from within the test environment for effects such as printing test results to the console or timing out tests where it is necessary to access the real environment.

   The easiest way to access the "live" environment is to use the live method with an effect that would otherwise access the test environment.

   import zio.clock
   import zio.test.environment._
   
   val realTime = live(clock.nanoTime)

   The withLive method can be used to apply a transformation to an effect with the live environment while ensuring that the effect itself still runs with the test environment, for example to time out a test. Both of these methods are re-exported in the environment package for easy availability.

6.  object TestClock extends Serializable

   TestClock makes it easy to deterministically and efficiently test effects involving the passage of time.

   TestClock makes it easy to deterministically and efficiently test effects involving the passage of time.

   Instead of waiting for actual time to pass, sleep and methods implemented in terms of it schedule effects to take place at a given clock time. Users can adjust the clock time using the adjust and setTime methods, and all effects scheduled to take place on or before that time will automatically be run in order.

   For example, here is how we can test ZIO#timeout using TestClock:

   import zio.ZIO
   import zio.duration._
   import zio.test.environment.TestClock
   
   for {
     fiber  <- ZIO.sleep(5.minutes).timeout(1.minute).fork
     _      <- TestClock.adjust(1.minute)
     result <- fiber.join
   } yield result == None

   Note how we forked the fiber that sleep was invoked on. Calls to sleep and methods derived from it will semantically block until the time is set to on or after the time they are scheduled to run. If we didn't fork the fiber on which we called sleep we would never get to set the time on the line below. Thus, a useful pattern when using TestClock is to fork the effect being tested, then adjust the clock time, and finally verify that the expected effects have been performed.

   For example, here is how we can test an effect that recurs with a fixed delay:

   import zio.Queue
   import zio.duration._
   import zio.test.environment.TestClock
   
   for {
     q <- Queue.unbounded[Unit]
     _ <- q.offer(()).delay(60.minutes).forever.fork
     a <- q.poll.map(_.isEmpty)
     _ <- TestClock.adjust(60.minutes)
     b <- q.take.as(true)
     c <- q.poll.map(_.isEmpty)
     _ <- TestClock.adjust(60.minutes)
     d <- q.take.as(true)
     e <- q.poll.map(_.isEmpty)
   } yield a && b && c && d && e

   Here we verify that no effect is performed before the recurrence period, that an effect is performed after the recurrence period, and that the effect is performed exactly once. The key thing to note here is that after each recurrence the next recurrence is scheduled to occur at the appropriate time in the future, so when we adjust the clock by 60 minutes exactly one value is placed in the queue, and when we adjust the clock by another 60 minutes exactly one more value is placed in the queue.

7.  object TestConsole extends Serializable

   TestConsole provides a testable interface for programs interacting with the console by modeling input and output as reading from and writing to input and output buffers maintained by TestConsole and backed by a Ref.

   TestConsole provides a testable interface for programs interacting with the console by modeling input and output as reading from and writing to input and output buffers maintained by TestConsole and backed by a Ref.

   All calls to putStr and putStrLn using the TestConsole will write the string to the output buffer and all calls to getStrLn will take a string from the input buffer. To facilitate debugging, by default output will also be rendered to standard output. You can enable or disable this for a scope using debug, silent, or the corresponding test aspects.

   TestConsole has several methods to access and manipulate the content of these buffers including feedLines to feed strings to the input buffer that will then be returned by calls to getStrLn, output to get the content of the output buffer from calls to putStr and putStrLn, and clearInput and clearOutput to clear the respective buffers.

   Together, these functions make it easy to test programs interacting with the console.

   import zio.console._
   import zio.test.environment.TestConsole
   import zio.ZIO
   
   val sayHello = for {
     name <- getStrLn
     _    <- putStrLn("Hello, " + name + "!")
   } yield ()
   
   for {
     _ <- TestConsole.feedLines("John", "Jane", "Sally")
     _ <- ZIO.collectAll(List.fill(3)(sayHello))
     result <- TestConsole.output
   } yield result == Vector("Hello, John!\n", "Hello, Jane!\n", "Hello, Sally!\n")

8.  object TestEnvironment

   Definition Classes

   PlatformSpecific

9.  object TestRandom extends Serializable

   TestRandom allows for deterministically testing effects involving randomness.

   TestRandom allows for deterministically testing effects involving randomness.

   TestRandom operates in two modes. In the first mode, TestRandom 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 TestRandom 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, TestRandom 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.environment.TestRandom
   
   for {
     _ <- TestRandom.feedInts(4, 5, 2)
     x <- random.nextIntBounded(6)
     y <- random.nextIntBounded(6)
     z <- random.nextIntBounded(6)
   } yield x + y + z == 11

   TestRandom 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 pseudo-random number generation.

10.  object TestSystem extends Serializable

    TestSystem supports deterministic testing of effects involving system properties.

    TestSystem supports deterministic testing of effects involving system properties. Internally, TestSystem maintains mappings of environment variables and system properties that can be set and accessed. No actual environment variables or system properties will be accessed or set as a result of these actions.

    import zio.system
    import zio.test.environment.TestSystem
    
    for {
      _      <- TestSystem.putProperty("java.vm.name", "VM")
      result <- system.property("java.vm.name")
    } yield result == Some("VM")