test
An Annotated[A] contains a value of type A along with zero or more
test annotations.
The Annotations trait provides access to an annotation map that tests
can add arbitrary annotations to.
The Annotations trait provides access to an annotation map that tests
can add arbitrary annotations to. Each annotation consists of a string
identifier, an initial value, and a function for combining two values.
Annotations form monoids and you can think of Annotations as a more
structured logging service or as a super polymorphic version of the writer
monad effect.
An Assertion[A] is capable of producing assertion results on an A.
An Assertion[A] is capable of producing assertion results on an A. As a
proposition, assertions compose using logical conjunction and disjunction,
and can be negated.
An AssertionM[A] is capable of producing assertion results on an A.
An AssertionM[A] is capable of producing assertion results on an A. As a
proposition, assertions compose using logical conjunction and disjunction,
and can be negated.
An AssertionValue keeps track of a assertion and a value, existentially
hiding the type.
An AssertionValue keeps track of a assertion and a value, existentially
hiding the type. This is used internally by the library to provide useful
error messages in the event of test failures.
A BoolAlgebra[A] is a description of logical operations on values of type
A.
A default runnable spec that provides testable versions of all of the modules in ZIO (Clock, Has[Random], etc).
A value of type Eql[A, B] provides implicit evidence that two values with
types A and B could potentially be equal, that is, that
A is a subtype of B or B is a subtype of A.
A value of type Eql[A, B] provides implicit evidence that two values with
types A and B could potentially be equal, that is, that
A is a subtype of B or B is a subtype of A.
An ExecutedSpec is a spec that has been run to produce test results.
FailureDetails keeps track of details relevant to failures.
A Gen[R, A] represents a generator of values of type A, which requires
an environment R.
A Gen[R, A] represents a generator of values of type A, which requires
an environment R. Generators may be random or deterministic.
GenFailureDetails keeps track of relevant information related to a failure in a generative test.
A RunnableSpec has a main function and can be run by the JVM / Scala.js.
A sample is a single observation from a random variable, together with a tree of "shrinkings" used for minimization of "large" failures.
A Spec[R, E, T] is the backbone of _ZIO Test_.
A Spec[R, E, T] is the backbone of _ZIO Test_. Every spec is either a
suite, which contains other specs, or a test of type T. All specs require
an environment of type R and may potentially fail with an error of type
E.
A type of annotation.
An annotation map keeps track of annotations of different types.
A TestAnnotationRenderer knows how to render test annotations.
A TestAspect is an aspect that can be weaved into specs.
A TestAspect is an aspect that can be weaved into specs. You can think of
an aspect as a polymorphic function, capable of transforming one test into
another, possibly enlarging the environment or error type.
A TestAspectAtLeast[R] is a TestAspect that requires at least an R in its environment.
A TestAspectPoly is a TestAspect that is completely polymorphic,
having no requirements on error or environment.
The TestConfig service provides access to default configuration settings
used by ZIO Test, including the number of times to repeat tests to ensure
they are stable, the number of times to retry flaky tests, the sufficient
number of samples to check from a random variable, and the maximum number
of shrinkings to minimize large failures.
A TestExecutor[R, E] is capable of executing specs that require an
environment R and may fail with an E.
A TestReporter[E] is capable of reporting test results with error type
E.
A TestRunner[R, E] encapsulates all the logic necessary to run specs that
require an environment R and may fail with an error E.
A TestRunner[R, E] encapsulates all the logic necessary to run specs that
require an environment R and may fail with an error E. Test runners
require a test executor, a runtime configuration, and a reporter.
A ZSpec[R, E] is the canonical spec for testing ZIO programs.
A ZSpec[R, E] is the canonical spec for testing ZIO programs. The spec's
test type is a ZIO effect that requires an R and might fail with an E.
A ZTest[R, E] is an effectfully produced test that requires an R and
may fail with an E.
A ZRTestEnv is an alias for all ZIO provided Restorable
TestEnvironment objects
Syntax for writing test like
Syntax for writing test like
object MySpec extends DefaultMutableRunnableSpec { suite("foo") { test("name") { } @@ ignore test("name 2") } suite("another suite") { test("name 3") } }
(Since version 2.0.0) use DefaultRunnableSpec
Syntax for writing test like
Syntax for writing test like
object MySpec extends MutableRunnableSpec(layer, aspect) { suite("foo") { test("name") { } @@ ignore test("name 2") } suite("another suite") { test("name 3") } }
(Since version 2.0.0) use RunnableSpec
Proxy methods to call package private methods from the macro
TestPlatform provides information about the platform tests are being run
on to enable platform specific test configuration.
TestVersion provides information about the Scala version tests are being
run on to enable platform specific test configuration.
Checks the assertion holds for the given value.
Checks the assertion holds for the given value.
Asserts that the given test was completed.
Asserts that the given test was completed.
Checks the assertion holds for the given effectfully-computed value.
Checks the assertion holds for the given effectfully-computed value.
Checks the assertion holds for the given value.
Checks the assertion holds for the given value.
A version of check that accepts six random variables.
A version of check that accepts five random variables.
A version of check that accepts four random variables.
A version of check that accepts three random variables.
A version of check that accepts two random variables.
Checks the test passes for "sufficient" numbers of samples from the given random variable.
A version of checkAll that accepts six random variables.
A version of checkAll that accepts five random variables.
A version of checkAll that accepts four random variables.
A version of checkAll that accepts three random variables.
A version of checkAll that accepts two random variables.
Checks the test passes for all values from the given random variable.
Checks the test passes for all values from the given random variable. This
is useful for deterministic Gen that comprehensively explore all
possibilities in a given domain.
A version of checkAllMPar that accepts six random variables.
A version of checkAllMPar that accepts five random variables.
A version of checkAllMPar that accepts four random variables.
A version of checkAllMPar that accepts three random variables.
A version of checkAllMPar that accepts two random variables.
Checks in parallel the effectual test passes for all values from the given random variable.
Checks in parallel the effectual test passes for all values from the given random
variable. This is useful for deterministic Gen that comprehensively
explore all possibilities in a given domain.
Checks the test passes for the specified number of samples from the given random variable.
A Runner that provides a default testable environment.
The environment package contains testable versions of all the standard ZIO
environment types through the TestClock, TestConsole,
TestSystem, and TestRandom modules.
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.
Creates a failed test result with the specified runtime cause.
Creates an ignored test result.
The laws package provides functionality for describing laws as values.
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:
a1 === a1
2. Symmetry - a1 === a2 ==> a2 === a1
3. 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.int)
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.
Passes platform specific information to the specified function, which will use that information to create a test.
Passes platform specific information to the specified function, which will use that information to create a test. If the platform is neither ScalaJS nor the JVM, an ignored test result will be returned.
Builds a suite containing a number of other specs.
Builds a spec with a single test.
Returns either Right if the specified string type checks as valid Scala
code or Left with an error message otherwise.
Returns either Right if the specified string type checks as valid Scala
code or Left with an error message otherwise. Dies with a runtime
exception if specified string cannot be parsed or is not a known value at
compile time.
Passes version specific information to the specified function, which will use that information to create a test.
Passes version specific information to the specified function, which will use that information to create a test. If the version is neither Dotty nor Scala 2, an ignored test result will be returned.
A version of checkAllM that accepts six random variables.
A version of checkAllM that accepts six random variables.
(Since version 2.0.0) use checkAll
A version of checkAllM that accepts five random variables.
A version of checkAllM that accepts five random variables.
(Since version 2.0.0) use checkAll
A version of checkAllM that accepts four random variables.
A version of checkAllM that accepts four random variables.
(Since version 2.0.0) use checkAll
A version of checkAllM that accepts three random variables.
A version of checkAllM that accepts three random variables.
(Since version 2.0.0) use checkAll
A version of checkAllM that accepts two random variables.
A version of checkAllM that accepts two random variables.
(Since version 2.0.0) use checkAll
Checks the effectual test passes for all values from the given random variable.
Checks the effectual test passes for all values from the given random
variable. This is useful for deterministic Gen that comprehensively
explore all possibilities in a given domain.
(Since version 2.0.0) use checkAll
A version of checkAllMPar that accepts six random variables.
A version of checkAllMPar that accepts six random variables.
(Since version 2.0.0) use checkPar
A version of checkAllMPar that accepts five random variables.
A version of checkAllMPar that accepts five random variables.
(Since version 2.0.0) use checkPar
A version of checkAllMPar that accepts four random variables.
A version of checkAllMPar that accepts four random variables.
(Since version 2.0.0) use checkPar
A version of checkAllMPar that accepts three random variables.
A version of checkAllMPar that accepts three random variables.
(Since version 2.0.0) use checkPar
A version of checkAllMPar that accepts two random variables.
A version of checkAllMPar that accepts two random variables.
(Since version 2.0.0) use checkPar
Checks in parallel the effectual test passes for all values from the given random variable.
Checks in parallel the effectual test passes for all values from the given random
variable. This is useful for deterministic Gen that comprehensively
explore all possibilities in a given domain.
(Since version 2.0.0) use checkPar
A version of checkM that accepts six random variables.
A version of checkM that accepts six random variables.
(Since version 2.0.0) use check
A version of checkM that accepts five random variables.
A version of checkM that accepts five random variables.
(Since version 2.0.0) use check
A version of checkM that accepts four random variables.
A version of checkM that accepts four random variables.
(Since version 2.0.0) use check
A version of checkM that accepts three random variables.
A version of checkM that accepts three random variables.
(Since version 2.0.0) use check
A version of checkM that accepts two random variables.
A version of checkM that accepts two random variables.
(Since version 2.0.0) use check
Checks the effectual test passes for "sufficient" numbers of samples from the given random variable.
Checks the effectual test passes for "sufficient" numbers of samples from the given random variable.
(Since version 2.0.0) use check
Checks the effectual test passes for the specified number of samples from the given random variable.
Checks the effectual test passes for the specified number of samples from the given random variable.
(Since version 2.0.0) use checkN
Builds an effectual suite containing a number of other specs.
Builds an effectual suite containing a number of other specs.
(Since version 2.0.0) use suite
Builds a spec with a single effectful test.
Builds a spec with a single effectful test.
(Since version 2.0.0) use test
_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.