Interface Arbitrary<T>
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- Type Parameters:
T
- The type of generated objects. Primitive objects (e.g. int, boolean etc.) are represented by their boxed type (e.g. Integer, Boolean).
- All Known Subinterfaces:
ActionSequenceArbitrary<M>
,ArrayArbitrary<T,A>
,BigDecimalArbitrary
,BigIntegerArbitrary
,ByteArbitrary
,CalendarArbitrary
,CharacterArbitrary
,DateArbitrary
,DoubleArbitrary
,EmailArbitrary
,FloatArbitrary
,FunctionArbitrary<F,R>
,IntegerArbitrary
,IteratorArbitrary<T>
,ListArbitrary<T>
,LocalDateArbitrary
,LongArbitrary
,MapArbitrary<K,V>
,MonthDayArbitrary
,NumericalArbitrary<T,A>
,PeriodArbitrary
,SetArbitrary<T>
,ShortArbitrary
,SizableArbitrary<U>
,StreamableArbitrary<T,U>
,StreamArbitrary<T>
,StringArbitrary
,TypeArbitrary<T>
,YearArbitrary
,YearMonthArbitrary
- All Known Implementing Classes:
ArbitraryDecorator
@API(status=STABLE, since="1.0") public interface Arbitrary<T>
The main interface for representing objects that can be generated and shrunk.
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Nested Class Summary
Nested Classes Modifier and Type Interface Description static class
Arbitrary.ArbitraryFacade
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Method Summary
All Methods Instance Methods Abstract Methods Default Methods Modifier and Type Method Description default java.util.Optional<java.util.stream.Stream<T>>
allValues()
Create optional stream of all possible values this arbitrary could generate.default <A> ArrayArbitrary<T,A>
array(java.lang.Class<A> arrayClass)
Create a new arbitrary of typeT[]
using the existing arbitrary for generating the elements of the array.default Arbitrary<java.lang.Object>
asGeneric()
default Arbitrary<java.util.List<T>>
collect(java.util.function.Predicate<java.util.List<T>> until)
Create a new arbitrary of typeList<T>
by adding elements of type T until conditionuntil
is fulfilled.default Arbitrary<T>
dontShrink()
Create a new arbitrary of typeT
that will use the underlying arbitrary to create the tuple values but will return unshrinkable values.default EdgeCases<T>
edgeCases()
Return an arbitrary's edge cases up to a limit of 1000.EdgeCases<T>
edgeCases(int maxEdgeCases)
default Arbitrary<T>
edgeCases(java.util.function.Consumer<EdgeCases.Config<T>> configurator)
Experimental interface to change generated edge cases of a specific arbitrary.default java.util.Optional<ExhaustiveGenerator<T>>
exhaustive()
Create the exhaustive generator for an arbitrary using the maximum allowed number of generated samples.default java.util.Optional<ExhaustiveGenerator<T>>
exhaustive(long maxNumberOfSamples)
Create the exhaustive generator for an arbitrary.default Arbitrary<T>
filter(java.util.function.Predicate<T> filterPredicate)
Create a new arbitrary of the same typeT
that creates and shrinks the original arbitrary but only allows values that are accepted by thefilterPredicate
.default Arbitrary<T>
fixGenSize(int genSize)
Fix the genSize of an arbitrary so that it can no longer be influenced from outsidedefault <U> Arbitrary<U>
flatMap(java.util.function.Function<T,Arbitrary<U>> mapper)
Create a new arbitrary of typeU
that uses the values of the existing arbitrary to create a new arbitrary using themapper
function.default void
forEachValue(java.util.function.Consumer<? super T> action)
Iterate through each value this arbitrary can generate if - and only if - exhaustive generation is possible.RandomGenerator<T>
generator(int genSize)
Create the random generator for an arbitrary.default RandomGenerator<T>
generator(int genSize, boolean withEdgeCases)
Create the random generator for an arbitrary with or without edge cases.default RandomGenerator<T>
generatorWithEmbeddedEdgeCases(int genSize)
Create the random generator for an arbitrary where the embedded generators, if there are any, also generate edge cases.default Arbitrary<T>
ignoreException(java.lang.Class<? extends java.lang.Throwable> exceptionType)
Create a new arbitrary of typeT
that will use the underlying arbitrary to create the tuple values but will ignore any raised exception of typeexceptionType
during generation.default Arbitrary<T>
injectDuplicates(double duplicateProbability)
Create a new arbitrary of typeIterable<T>
that will inject duplicates of previously generated values with a probability ofduplicateProbability
.default Arbitrary<T>
injectNull(double nullProbability)
Create a new arbitrary of the same type but inject null values with a probability ofnullProbability
.default IteratorArbitrary<T>
iterator()
Create a new arbitrary of typeIterable<T>
using the existing arbitrary for generating the elements of the stream.default ListArbitrary<T>
list()
Create a new arbitrary of typeList<T>
using the existing arbitrary for generating the elements of the list.default <U> Arbitrary<U>
map(java.util.function.Function<T,U> mapper)
Create a new arbitrary of typeU
that maps the values of the original arbitrary using themapper
function.default Arbitrary<java.util.Optional<T>>
optional()
Create a new arbitrary of typeOptional<T>
using the existing arbitrary for generating the elements of the stream.default T
sample()
Generate a single sample value using this arbitrary.default java.util.stream.Stream<T>
sampleStream()
Generate a stream of sample values using this arbitrary.default SetArbitrary<T>
set()
Create a new arbitrary of typeSet<T>
using the existing arbitrary for generating the elements of the set.default StreamArbitrary<T>
stream()
Create a new arbitrary of typeStream<T>
using the existing arbitrary for generating the elements of the stream.default Arbitrary<Tuple.Tuple1<T>>
tuple1()
Create a new arbitrary of typeTuple.Tuple1<T>
that will use the underlying arbitrary to create the tuple value;default Arbitrary<Tuple.Tuple2<T,T>>
tuple2()
Create a new arbitrary of typeTuple.Tuple2<T, T>
that will use the underlying arbitrary to create the tuple values;default Arbitrary<Tuple.Tuple3<T,T,T>>
tuple3()
Create a new arbitrary of typeTuple.Tuple3<T, T, T>
that will use the underlying arbitrary to create the tuple values;default Arbitrary<Tuple.Tuple4<T,T,T,T>>
tuple4()
Create a new arbitrary of typeTuple.Tuple4<T, T, T, T>
that will use the underlying arbitrary to create the tuple values;default Arbitrary<Tuple.Tuple5<T,T,T,T,T>>
tuple5()
Create a new arbitrary of typeTuple.Tuple5<T, T, T, T, T>
that will use the underlying arbitrary to create the tuple values;default Arbitrary<T>
withoutEdgeCases()
Create a new arbitrary of typeT
that will not explicitly generate any edge cases, neither directly or in embedded arbitraries.
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Method Detail
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generator
RandomGenerator<T> generator(int genSize)
Create the random generator for an arbitrary.Starting with version 1.4.0 the returned generator should no longer include edge cases explicitly since those will be injected in generator(int, boolean)
- Parameters:
genSize
- a very unspecific configuration parameter that can be used to influence the configuration and behaviour of a random generator if and only if the generator wants to be influenced. Many generators are independent of genSize.The default value of
genSize
is the number of tries configured for a property. Use fixGenSize(int) to fix the parameter for a given arbitrary.- Returns:
- a new random generator instance
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generator
@API(status=INTERNAL, since="1.4.0") default RandomGenerator<T> generator(int genSize, boolean withEdgeCases)
Create the random generator for an arbitrary with or without edge cases.Never override this method. Override generator(int) instead.
- Parameters:
genSize
- See generator(int) about meaning of this parameterwithEdgeCases
- True if edge cases should be injected into the stream of generated values- Returns:
- a new random generator instance
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generatorWithEmbeddedEdgeCases
@API(status=INTERNAL, since="1.4.0") default RandomGenerator<T> generatorWithEmbeddedEdgeCases(int genSize)
Create the random generator for an arbitrary where the embedded generators, if there are any, also generate edge cases.Override only if there are any embedded arbitraries / generators, e.g. a container using an element generator
- Parameters:
genSize
- See generator(int) about meaning of this parameter- Returns:
- a new random generator instance
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asGeneric
@API(status=INTERNAL) default Arbitrary<java.lang.Object> asGeneric()
- Returns:
- The same instance but with type Arbitrary<Object>
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exhaustive
@API(status=INTERNAL) default java.util.Optional<ExhaustiveGenerator<T>> exhaustive()
Create the exhaustive generator for an arbitrary using the maximum allowed number of generated samples. Just trying to find out if such a generator exists might take a long time. This method should never be overridden.- Returns:
- a new exhaustive generator or Optional.empty() if it cannot be created.
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exhaustive
@API(status=INTERNAL) default java.util.Optional<ExhaustiveGenerator<T>> exhaustive(long maxNumberOfSamples)
Create the exhaustive generator for an arbitrary. Depending onmaxNumberOfSamples
this can take a long time. This method must be overridden in all arbitraries that support exhaustive generation.- Parameters:
maxNumberOfSamples
- The maximum number of samples considered. If during generation it becomes clear that this number will be exceeded generation stops.- Returns:
- a new exhaustive generator or Optional.empty() if it cannot be created.
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edgeCases
@API(status=EXPERIMENTAL, since="1.3.0") default EdgeCases<T> edgeCases()
Return an arbitrary's edge cases up to a limit of 1000.Never override. Override edgeCases(int) instead.
- Returns:
- an instance of type EdgeCases
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allValues
default java.util.Optional<java.util.stream.Stream<T>> allValues()
Create optional stream of all possible values this arbitrary could generate. This is only possible if the arbitrary is available for exhaustive generation.- Returns:
- optional stream of all possible values
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forEachValue
@API(status=MAINTAINED, since="1.1.2") default void forEachValue(java.util.function.Consumer<? super T> action)
Iterate through each value this arbitrary can generate if - and only if - exhaustive generation is possible. This method can be used for example to make assertions about a set of values described by an arbitrary.- Parameters:
action
- the consumer function to be invoked for each value- Throws:
java.lang.AssertionError
- if exhaustive generation is not possible
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filter
default Arbitrary<T> filter(java.util.function.Predicate<T> filterPredicate)
Create a new arbitrary of the same typeT
that creates and shrinks the original arbitrary but only allows values that are accepted by thefilterPredicate
.- Parameters:
filterPredicate
- The predicate used for filtering- Returns:
- a new arbitrary instance
- Throws:
JqwikException
- if filtering will fail to come up with a value after 10000 tries
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map
default <U> Arbitrary<U> map(java.util.function.Function<T,U> mapper)
Create a new arbitrary of typeU
that maps the values of the original arbitrary using themapper
function.- Type Parameters:
U
- type of resulting object- Parameters:
mapper
- the function used to map- Returns:
- a new arbitrary instance
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flatMap
default <U> Arbitrary<U> flatMap(java.util.function.Function<T,Arbitrary<U>> mapper)
Create a new arbitrary of typeU
that uses the values of the existing arbitrary to create a new arbitrary using themapper
function.- Type Parameters:
U
- type of resulting object- Parameters:
mapper
- the function used to map to arbitrary- Returns:
- a new arbitrary instance
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injectNull
default Arbitrary<T> injectNull(double nullProbability)
Create a new arbitrary of the same type but inject null values with a probability ofnullProbability
.- Parameters:
nullProbability
- the probability. ≤ 0 and ≥ 1.- Returns:
- a new arbitrary instance
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fixGenSize
@API(status=MAINTAINED, since="1.2.0") default Arbitrary<T> fixGenSize(int genSize)
Fix the genSize of an arbitrary so that it can no longer be influenced from outside- Parameters:
genSize
- The size used in arbitrary instead of the dynamic one- Returns:
- a new arbitrary instance
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list
default ListArbitrary<T> list()
Create a new arbitrary of typeList<T>
using the existing arbitrary for generating the elements of the list.- Returns:
- a new arbitrary instance
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set
default SetArbitrary<T> set()
Create a new arbitrary of typeSet<T>
using the existing arbitrary for generating the elements of the set.- Returns:
- a new arbitrary instance
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stream
default StreamArbitrary<T> stream()
Create a new arbitrary of typeStream<T>
using the existing arbitrary for generating the elements of the stream.- Returns:
- a new arbitrary instance
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iterator
default IteratorArbitrary<T> iterator()
Create a new arbitrary of typeIterable<T>
using the existing arbitrary for generating the elements of the stream.- Returns:
- a new arbitrary instance
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array
default <A> ArrayArbitrary<T,A> array(java.lang.Class<A> arrayClass)
Create a new arbitrary of typeT[]
using the existing arbitrary for generating the elements of the array.- Type Parameters:
A
- Type of resulting array class- Parameters:
arrayClass
- The arrays class to create, e.g.String[].class
. This is required due to limitations in Java's reflection capabilities.- Returns:
- a new arbitrary instance
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optional
default Arbitrary<java.util.Optional<T>> optional()
Create a new arbitrary of typeOptional<T>
using the existing arbitrary for generating the elements of the stream.The new arbitrary also generates
Optional.empty()
values with a probability of0.05
(i.e. 1 in 20).- Returns:
- a new arbitrary instance
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collect
@API(status=MAINTAINED, since="1.3.0") default Arbitrary<java.util.List<T>> collect(java.util.function.Predicate<java.util.List<T>> until)
Create a new arbitrary of typeList<T>
by adding elements of type T until conditionuntil
is fulfilled.- Parameters:
until
- predicate to check if final condition has been reached- Returns:
- a new arbitrary instance
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sampleStream
@API(status=MAINTAINED, since="1.3.0") default java.util.stream.Stream<T> sampleStream()
Generate a stream of sample values using this arbitrary. This can be useful for- Testing arbitraries
- Playing around with arbitraries in jshell
- Using arbitraries independently from jqwik, e.g. to feed test data builders
The underlying generator is created with size 1000. Outside a property a new instance of Random will be created to feed the generator.
Using this method within a property does not break reproducibility of results, i.e. rerunning it with same seed will also generate the same values.
- Returns:
- a stream of newly generated values
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sample
@API(status=MAINTAINED, since="1.3.0") default T sample()
Generate a single sample value using this arbitrary. This can be useful for- Testing arbitraries
- Playing around with arbitraries in jshell
- Using arbitraries independently from jqwik, e.g. to feed test data builders
Some additional things to be aware of:
- If you feel the need to use this method for real generation, e.g. in a provider method you are most probably doing it wrong. You might want to use flatMap(Function).
- The underlying generator is created with size 1000. Outside a property a new instance of Random will be created to feed the generator.
- Using this method within a property does not break reproducibility of results, i.e. rerunning it with same seed will also generate the same value.
- Returns:
- a newly generated value
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injectDuplicates
@API(status=MAINTAINED, since="1.3.0") default Arbitrary<T> injectDuplicates(double duplicateProbability)
Create a new arbitrary of typeIterable<T>
that will inject duplicates of previously generated values with a probability ofduplicateProbability
.Shrinking behavior for duplicate values -- if duplication is required for falsification -- is poor, i.e. those duplicate values cannot be shrunk to "smaller" duplicate values.
- Parameters:
duplicateProbability
- The probability with which a previous value will be generated- Returns:
- a new arbitrary instance
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tuple1
@API(status=MAINTAINED, since="1.3.0") default Arbitrary<Tuple.Tuple1<T>> tuple1()
Create a new arbitrary of typeTuple.Tuple1<T>
that will use the underlying arbitrary to create the tuple value;- Returns:
- a new arbitrary instance
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tuple2
@API(status=MAINTAINED, since="1.3.0") default Arbitrary<Tuple.Tuple2<T,T>> tuple2()
Create a new arbitrary of typeTuple.Tuple2<T, T>
that will use the underlying arbitrary to create the tuple values;- Returns:
- a new arbitrary instance
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tuple3
@API(status=MAINTAINED, since="1.3.0") default Arbitrary<Tuple.Tuple3<T,T,T>> tuple3()
Create a new arbitrary of typeTuple.Tuple3<T, T, T>
that will use the underlying arbitrary to create the tuple values;- Returns:
- a new arbitrary instance
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tuple4
@API(status=MAINTAINED, since="1.3.0") default Arbitrary<Tuple.Tuple4<T,T,T,T>> tuple4()
Create a new arbitrary of typeTuple.Tuple4<T, T, T, T>
that will use the underlying arbitrary to create the tuple values;- Returns:
- a new arbitrary instance
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tuple5
@API(status=MAINTAINED, since="1.3.3") default Arbitrary<Tuple.Tuple5<T,T,T,T,T>> tuple5()
Create a new arbitrary of typeTuple.Tuple5<T, T, T, T, T>
that will use the underlying arbitrary to create the tuple values;- Returns:
- a new arbitrary instance
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ignoreException
@API(status=EXPERIMENTAL, since="1.3.1") default Arbitrary<T> ignoreException(java.lang.Class<? extends java.lang.Throwable> exceptionType)
Create a new arbitrary of typeT
that will use the underlying arbitrary to create the tuple values but will ignore any raised exception of typeexceptionType
during generation.- Parameters:
exceptionType
- The exception type to ignore- Returns:
- a new arbitrary instance
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dontShrink
@API(status=MAINTAINED, since="1.4.0") default Arbitrary<T> dontShrink()
Create a new arbitrary of typeT
that will use the underlying arbitrary to create the tuple values but will return unshrinkable values. This might be necessary if values are being mutated during a property run and the mutated state would make a shrunk value invalid.This is a hack to get around a weakness in jqwik's shrinking mechanism
- Returns:
- a new arbitrary instance
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edgeCases
@API(status=EXPERIMENTAL, since="1.3.9") default Arbitrary<T> edgeCases(java.util.function.Consumer<EdgeCases.Config<T>> configurator)
Experimental interface to change generated edge cases of a specific arbitrary.- Parameters:
configurator
- A consumer that configures deviating edge cases behaviour- Returns:
- a new arbitrary instance
- See Also:
EdgeCases.Config
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withoutEdgeCases
@API(status=EXPERIMENTAL, since="1.4.0") default Arbitrary<T> withoutEdgeCases()
Create a new arbitrary of typeT
that will not explicitly generate any edge cases, neither directly or in embedded arbitraries. This is useful if you want to prune selected branches of edge case generation because they are to costly or generate too many cases.- Returns:
- a new arbitrary instance
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