zio-test
Packages
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.test.environment.Live
import zio.clock.nanoTime
import Assertion.isGreaterThan
object MyTest extends DefaultRunnableSpec {
def spec = suite("clock")(
testM("time is non-zero") {
assertM(Live.live(nanoTime))(isGreaterThan(0))
}
)
}
The environment
package contains testable versions of all the standard ZIO
environment types through the TestClock, TestConsole, TestSystem,
and TestRandom modules. See the documentation on the individual modules
for more detail about using each of them.
The environment
package contains testable versions of all the standard ZIO
environment types through the TestClock, TestConsole, TestSystem,
and TestRandom modules. See the documentation on the individual modules
for more detail about using each of them.
If you are using ZIO Test and extending RunnableSpec
a TestEnvironment
containing all of them will be automatically provided to each of your tests.
Otherwise, the easiest way to use the test implementations in ZIO Test is by
providing the TestEnvironment
to your program.
import zio.test.environment._
myProgram.provideLayer(testEnvironment)
Then all environmental effects, such as printing to the console or generating
random numbers, will be implemented by the TestEnvironment
and will be
fully testable. When you do need to access the "live" environment, for
example to print debugging information to the console, just use the live
combinator along with the effect as your normally would.
If you are only interested in one of the test implementations for your
application, you can also access them a la carte through the make
method on
each module. Each test module requires some data on initialization. Default
data is included for each as DefaultData
.
import zio.test.environment._
myProgram.provideM(TestConsole.make(TestConsole.DefaultData))
Finally, you can create a Test
object that implements the test interface
directly using the makeTest
method. This can be useful when you want to
access some testing functionality without using the environment type.
import zio.test.environment._
for {
testRandom <- TestRandom.makeTest(TestRandom.DefaultData)
n <- testRandom.nextInt
} yield n
This can also be useful when you are creating a more complex environment to provide the implementation for test services that you mix in.
The laws
package provides functionality for describing laws as values. The
fundamental abstraction is a set of ZLaws[Caps, R]
. These laws model the
laws that instances having a capability of type Caps
are expected to
satisfy. A capability Caps[_]
is an abstraction describing some
functionality that is common across different data types and obeys certain
laws. For example, we can model the capability of two values of a type being
compared for equality as follows:
The laws
package provides functionality for describing laws as values. The
fundamental abstraction is a set of ZLaws[Caps, R]
. These laws model the
laws that instances having a capability of type Caps
are expected to
satisfy. A capability Caps[_]
is an abstraction describing some
functionality that is common across different data types and obeys certain
laws. For example, we can model the capability of two values of a type being
compared for equality as follows:
trait Equal[-A] {
def equal(a1: A, a2: A): Boolean
}
Definitions of equality are expected to obey certain laws:
- Reflexivity -
a1 === a1
- Symmetry -
a1 === a2 ==> a2 === a1
- Transitivity -
(a1 === a2) && (a2 === a3) ==> (a1 === a3)
These laws define what the capabilities mean and ensure that it is safe to abstract across different instances with the same capability.
Using ZIO Test, we can represent these laws as values. To do so, we define
each law using one of the ZLaws
constructors. For example:
val transitivityLaw = ZLaws.Laws3[Equal]("transitivityLaw") {
def apply[A: Equal](a1: A, a2: A, a3: A): TestResult =
???
}
We can then combine laws using the +
operator:
val reflexivityLaw: = ???
val symmetryLaw: = ???
val equalLaws = reflexivityLaw + symmetryLaw + transitivityLaw
Laws have a run
method that takes a generator of values of type A
and
checks that those values satisfy the laws. In addition, objects can extend
ZLawful
to provide an even more convenient syntax for users to check that
instances satisfy certain laws.
object Equal extends Lawful[Equal]
object Hash extends Lawful[Hash]
object Ord extends Lawful[Ord]
checkAllLaws(Equal + Hash + Ord)(Gen.anyInt)
Note that capabilities compose seamlessly because of contravariance. We can combine laws describing different capabilities to construct a set of laws requiring that instances having all of the capabilities satisfy each of the laws.