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Fixing Checkstyle problems.

This commit is contained in:
Jochen Wiedmann 2020-02-07 21:59:23 +01:00
parent 2ea44b2ada
commit 3ce3b27dbd
2 changed files with 346 additions and 299 deletions
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src/main/java/org/apache/commons/lang3/Streams.java
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@ -16,6 +16,7 @@
*/ */
package org.apache.commons.lang3; package org.apache.commons.lang3;
import java.util.Collection;
import java.util.function.BiConsumer; import java.util.function.BiConsumer;
import java.util.function.BinaryOperator; import java.util.function.BinaryOperator;
import java.util.function.Consumer; import java.util.function.Consumer;
@ -48,7 +49,7 @@ import org.apache.commons.lang3.Functions.FailablePredicate;
* </pre> * </pre>
* Using a {@link FailableStream}, this can be rewritten as follows: * Using a {@link FailableStream}, this can be rewritten as follows:
* <pre> * <pre>
* ObjectStreams.failable(stream).forEach((m) -&gt; m.invoke(o, args)); * Streams.failable(stream).forEach((m) -&gt; m.invoke(o, args));
* </pre> * </pre>
* Obviously, the second version is much more concise and the spirit of * Obviously, the second version is much more concise and the spirit of
* Lambda expressions is met better than in the first version. * Lambda expressions is met better than in the first version.
@ -56,309 +57,309 @@ import org.apache.commons.lang3.Functions.FailablePredicate;
* @see Functions * @see Functions
*/ */
public class Streams { public class Streams {
/** A reduced, and simplified version of a {@link Stream} with /** A reduced, and simplified version of a {@link Stream} with
* failable method signatures. * failable method signatures.
* @param <O> The streams element type. * @param <O> The streams element type.
*/ */
public static class FailableStream<O extends Object> { public static class FailableStream<O extends Object> {
private Stream<O> stream; private Stream<O> stream;
private boolean terminated; private boolean terminated;
public FailableStream(Stream<O> pStream) { public FailableStream(Stream<O> pStream) {
stream = pStream; stream = pStream;
} }
protected void assertNotTerminated() { protected void assertNotTerminated() {
if (terminated) { if (terminated) {
throw new IllegalStateException("This stream is already terminated."); throw new IllegalStateException("This stream is already terminated.");
} }
} }
protected void makeTerminated() { protected void makeTerminated() {
assertNotTerminated(); assertNotTerminated();
terminated = true; terminated = true;
} }
/** /**
* Returns a FailableStream consisting of the elements of this stream that match * Returns a FailableStream consisting of the elements of this stream that match
* the given FailablePredicate. * the given FailablePredicate.
* *
* <p>This is an intermediate operation. * <p>This is an intermediate operation.
* *
* @param pPredicate a non-interfering, stateless predicate to apply to each * @param pPredicate a non-interfering, stateless predicate to apply to each
* element to determine if it should be included. * element to determine if it should be included.
* @return the new stream * @return the new stream
*/ */
public FailableStream<O> filter(FailablePredicate<O,?> pPredicate){ public FailableStream<O> filter(FailablePredicate<O, ?> pPredicate){
assertNotTerminated(); assertNotTerminated();
stream = stream.filter(Functions.asPredicate(pPredicate)); stream = stream.filter(Functions.asPredicate(pPredicate));
return this; return this;
} }
/** /**
* Performs an action for each element of this stream. * Performs an action for each element of this stream.
* *
* <p>This is a terminal operation. * <p>This is a terminal operation.
* *
* <p>The behavior of this operation is explicitly nondeterministic. * <p>The behavior of this operation is explicitly nondeterministic.
* For parallel stream pipelines, this operation does <em>not</em> * For parallel stream pipelines, this operation does <em>not</em>
* guarantee to respect the encounter order of the stream, as doing so * guarantee to respect the encounter order of the stream, as doing so
* would sacrifice the benefit of parallelism. For any given element, the * would sacrifice the benefit of parallelism. For any given element, the
* action may be performed at whatever time and in whatever thread the * action may be performed at whatever time and in whatever thread the
* library chooses. If the action accesses shared state, it is * library chooses. If the action accesses shared state, it is
* responsible for providing the required synchronization. * responsible for providing the required synchronization.
* *
* @param pAction a non-interfering action to perform on the elements * @param pAction a non-interfering action to perform on the elements
*/ */
public void forEach(FailableConsumer<O,?> pAction) { public void forEach(FailableConsumer<O, ?> pAction) {
makeTerminated();
stream().forEach(Functions.asConsumer(pAction));
}
/**
* Performs a mutable reduction operation on the elements of this stream using a
* {@code Collector}. A {@code Collector}
* encapsulates the functions used as arguments to
* {@link #collect(Supplier, BiConsumer, BiConsumer)}, allowing for reuse of
* collection strategies and composition of collect operations such as
* multiple-level grouping or partitioning.
*
* <p>If the underlying stream is parallel, and the {@code Collector}
* is concurrent, and either the stream is unordered or the collector is
* unordered, then a concurrent reduction will be performed
* (see {@link Collector} for details on concurrent reduction.)
*
* <p>This is a terminal operation.
*
* <p>When executed in parallel, multiple intermediate results may be
* instantiated, populated, and merged so as to maintain isolation of
* mutable data structures. Therefore, even when executed in parallel
* with non-thread-safe data structures (such as {@code ArrayList}), no
* additional synchronization is needed for a parallel reduction.
*
* \@apiNote
* The following will accumulate strings into an ArrayList:
* <pre>{@code
* List<String> asList = stringStream.collect(Collectors.toList());
* }</pre>
*
* <p>The following will classify {@code Person} objects by city:
* <pre>{@code
* Map<String, List<Person>> peopleByCity
* = personStream.collect(Collectors.groupingBy(Person::getCity));
* }</pre>
*
* <p>The following will classify {@code Person} objects by state and city,
* cascading two {@code Collector}s together:
* <pre>{@code
* Map<String, Map<String, List<Person>>> peopleByStateAndCity
* = personStream.collect(Collectors.groupingBy(Person::getState,
* Collectors.groupingBy(Person::getCity)));
* }</pre>
*
* @param <R> the type of the result
* @param <A> the intermediate accumulation type of the {@code Collector}
* @param pCollector the {@code Collector} describing the reduction
* @return the result of the reduction
* @see #collect(Supplier, BiConsumer, BiConsumer)
* @see Collectors
*/
public <A,R> R collect(Collector<? super O,A,R> pCollector) {
makeTerminated(); makeTerminated();
return stream().collect(pCollector); stream().forEach(Functions.asConsumer(pAction));
} }
/** /**
* Performs a mutable reduction operation on the elements of this FailableStream. * Performs a mutable reduction operation on the elements of this stream using a
* A mutable reduction is one in which the reduced value is a mutable result * {@code Collector}. A {@code Collector}
* container, such as an {@code ArrayList}, and elements are incorporated by updating * encapsulates the functions used as arguments to
* the state of the result rather than by replacing the result. This produces a result equivalent to: * {@link #collect(Supplier, BiConsumer, BiConsumer)}, allowing for reuse of
* <pre>{@code * collection strategies and composition of collect operations such as
* R result = supplier.get(); * multiple-level grouping or partitioning.
* for (T element : this stream) *
* accumulator.accept(result, element); * <p>If the underlying stream is parallel, and the {@code Collector}
* return result; * is concurrent, and either the stream is unordered or the collector is
* }</pre> * unordered, then a concurrent reduction will be performed
* * (see {@link Collector} for details on concurrent reduction.)
* <p>Like {@link #reduce(Object, BinaryOperator)}, {@code collect} operations *
* can be parallelized without requiring additional synchronization. * <p>This is a terminal operation.
* *
* <p>This is a terminal operation. * <p>When executed in parallel, multiple intermediate results may be
* * instantiated, populated, and merged so as to maintain isolation of
* \@apiNote There are many existing classes in the JDK whose signatures are * mutable data structures. Therefore, even when executed in parallel
* well-suited for use with method references as arguments to {@code collect()}. * with non-thread-safe data structures (such as {@code ArrayList}), no
* For example, the following will accumulate strings into an {@code ArrayList}: * additional synchronization is needed for a parallel reduction.
* <pre>{@code *
* List<String> asList = stringStream.collect(ArrayList::new, ArrayList::add, * \@apiNote
* ArrayList::addAll); * The following will accumulate strings into an ArrayList:
* }</pre> * <pre>{@code
* * List<String> asList = stringStream.collect(Collectors.toList());
* <p>The following will take a stream of strings and concatenates them into a * }</pre>
* single string: *
* <pre>{@code * <p>The following will classify {@code Person} objects by city:
* String concat = stringStream.collect(StringBuilder::new, StringBuilder::append, * <pre>{@code
* StringBuilder::append) * Map<String, List<Person>> peopleByCity
* .toString(); * = personStream.collect(Collectors.groupingBy(Person::getCity));
* }</pre> * }</pre>
* *
* @param <R> type of the result * <p>The following will classify {@code Person} objects by state and city,
* @param <A> Type of the accumulator. * cascading two {@code Collector}s together:
* @param pSupplier a function that creates a new result container. For a * <pre>{@code
* parallel execution, this function may be called * Map<String, Map<String, List<Person>>> peopleByStateAndCity
* multiple times and must return a fresh value each time. * = personStream.collect(Collectors.groupingBy(Person::getState,
* @param pAccumulator An associative, non-interfering, stateless function for * Collectors.groupingBy(Person::getCity)));
* incorporating an additional element into a result * }</pre>
* @param pCombiner An associative, non-interfering, stateless *
* function for combining two values, which must be compatible with the * @param <R> the type of the result
* accumulator function * @param <A> the intermediate accumulation type of the {@code Collector}
* @return The result of the reduction * @param pCollector the {@code Collector} describing the reduction
*/ * @return the result of the reduction
public <A,R> R collect(Supplier<R> pSupplier, BiConsumer<R,? super O> pAccumulator, BiConsumer<R,R> pCombiner) { * @see #collect(Supplier, BiConsumer, BiConsumer)
* @see Collectors
*/
public <A, R> R collect(Collector<? super O, A, R> pCollector) {
makeTerminated(); makeTerminated();
return stream().collect(pSupplier, pAccumulator, pCombiner); return stream().collect(pCollector);
} }
/** /**
* Performs a reduction on the elements of this stream, using the provided * Performs a mutable reduction operation on the elements of this FailableStream.
* identity value and an associative accumulation function, and returns * A mutable reduction is one in which the reduced value is a mutable result
* the reduced value. This is equivalent to: * container, such as an {@code ArrayList}, and elements are incorporated by updating
* <pre>{@code * the state of the result rather than by replacing the result. This produces a result equivalent to:
* T result = identity; * <pre>{@code
* for (T element : this stream) * R result = supplier.get();
* result = accumulator.apply(result, element) * for (T element : this stream)
* return result; * accumulator.accept(result, element);
* }</pre> * return result;
* * }</pre>
* but is not constrained to execute sequentially. *
* * <p>Like {@link #reduce(Object, BinaryOperator)}, {@code collect} operations
* <p>The {@code identity} value must be an identity for the accumulator * can be parallelized without requiring additional synchronization.
* function. This means that for all {@code t}, *
* {@code accumulator.apply(identity, t)} is equal to {@code t}. * <p>This is a terminal operation.
* The {@code accumulator} function must be an associative function. *
* * \@apiNote There are many existing classes in the JDK whose signatures are
* <p>This is a terminal operation. * well-suited for use with method references as arguments to {@code collect()}.
* * For example, the following will accumulate strings into an {@code ArrayList}:
* \@apiNote Sum, min, max, average, and string concatenation are all special * <pre>{@code
* cases of reduction. Summing a stream of numbers can be expressed as: * List<String> asList = stringStream.collect(ArrayList::new, ArrayList::add,
* * ArrayList::addAll);
* <pre>{@code * }</pre>
* Integer sum = integers.reduce(0, (a, b) -> a+b); *
* }</pre> * <p>The following will take a stream of strings and concatenates them into a
* * single string:
* or: * <pre>{@code
* * String concat = stringStream.collect(StringBuilder::new, StringBuilder::append,
* <pre>{@code * StringBuilder::append)
* Integer sum = integers.reduce(0, Integer::sum); * .toString();
* }</pre> * }</pre>
* *
* <p>While this may seem a more roundabout way to perform an aggregation * @param <R> type of the result
* compared to simply mutating a running total in a loop, reduction * @param <A> Type of the accumulator.
* operations parallelize more gracefully, without needing additional * @param pSupplier a function that creates a new result container. For a
* synchronization and with greatly reduced risk of data races. * parallel execution, this function may be called
* * multiple times and must return a fresh value each time.
* @param pIdentity the identity value for the accumulating function * @param pAccumulator An associative, non-interfering, stateless function for
* @param pAccumulator an associative, non-interfering, stateless * incorporating an additional element into a result
* function for combining two values * @param pCombiner An associative, non-interfering, stateless
* @return the result of the reduction * function for combining two values, which must be compatible with the
*/ * accumulator function
public O reduce(O pIdentity, BinaryOperator<O> pAccumulator) { * @return The result of the reduction
*/
public <A, R> R collect(Supplier<R> pSupplier, BiConsumer<R, ? super O> pAccumulator, BiConsumer<R, R> pCombiner) {
makeTerminated(); makeTerminated();
return stream().reduce(pIdentity, pAccumulator); return stream().collect(pSupplier, pAccumulator, pCombiner);
} }
/** /**
* Returns a stream consisting of the results of applying the given * Performs a reduction on the elements of this stream, using the provided
* function to the elements of this stream. * identity value and an associative accumulation function, and returns
* * the reduced value. This is equivalent to:
* <p>This is an intermediate operation. * <pre>{@code
* * T result = identity;
* @param <R> The element type of the new stream * for (T element : this stream)
* @param pMapper A non-interfering, stateless function to apply to each element * result = accumulator.apply(result, element)
* @return the new stream * return result;
*/ * }</pre>
public <R> FailableStream<R> map(FailableFunction<O,R,?> pMapper) { *
assertNotTerminated(); * but is not constrained to execute sequentially.
return new FailableStream<R>(stream.map(Functions.asFunction(pMapper))); *
} * <p>The {@code identity} value must be an identity for the accumulator
* function. This means that for all {@code t},
* {@code accumulator.apply(identity, t)} is equal to {@code t}.
* The {@code accumulator} function must be an associative function.
*
* <p>This is a terminal operation.
*
* \@apiNote Sum, min, max, average, and string concatenation are all special
* cases of reduction. Summing a stream of numbers can be expressed as:
*
* <pre>{@code
* Integer sum = integers.reduce(0, (a, b) -> a+b);
* }</pre>
*
* or:
*
* <pre>{@code
* Integer sum = integers.reduce(0, Integer::sum);
* }</pre>
*
* <p>While this may seem a more roundabout way to perform an aggregation
* compared to simply mutating a running total in a loop, reduction
* operations parallelize more gracefully, without needing additional
* synchronization and with greatly reduced risk of data races.
*
* @param pIdentity the identity value for the accumulating function
* @param pAccumulator an associative, non-interfering, stateless
* function for combining two values
* @return the result of the reduction
*/
public O reduce(O pIdentity, BinaryOperator<O> pAccumulator) {
makeTerminated();
return stream().reduce(pIdentity, pAccumulator);
}
/** /**
* Converts the FailableStream into an equivalent stream. * Returns a stream consisting of the results of applying the given
* @return A stream, which will return the same elements, which this FailableStream would return. * function to the elements of this stream.
*/ *
public Stream<O> stream() { * <p>This is an intermediate operation.
return stream; *
} * @param <R> The element type of the new stream
* @param pMapper A non-interfering, stateless function to apply to each element
* @return the new stream
*/
public <R> FailableStream<R> map(FailableFunction<O, R, ?> pMapper) {
assertNotTerminated();
return new FailableStream<R>(stream.map(Functions.asFunction(pMapper)));
}
/** /**
* Returns whether all elements of this stream match the provided predicate. * Converts the FailableStream into an equivalent stream.
* May not evaluate the predicate on all elements if not necessary for * @return A stream, which will return the same elements, which this FailableStream would return.
* determining the result. If the stream is empty then {@code true} is */
* returned and the predicate is not evaluated. public Stream<O> stream() {
* return stream;
* <p>This is a short-circuiting terminal operation. }
*
* \@apiNote
* This method evaluates the <em>universal quantification</em> of the
* predicate over the elements of the stream (for all x P(x)). If the
* stream is empty, the quantification is said to be <em>vacuously
* satisfied</em> and is always {@code true} (regardless of P(x)).
*
* @param pPredicate A non-interfering, stateless predicate to apply to
* elements of this stream
* @return {@code true} If either all elements of the stream match the
* provided predicate or the stream is empty, otherwise {@code false}.
*/
public boolean allMatch(FailablePredicate<O,?> pPredicate) {
assertNotTerminated();
return stream().allMatch(Functions.asPredicate(pPredicate));
}
/** /**
* Returns whether any elements of this stream match the provided * Returns whether all elements of this stream match the provided predicate.
* predicate. May not evaluate the predicate on all elements if not * May not evaluate the predicate on all elements if not necessary for
* necessary for determining the result. If the stream is empty then * determining the result. If the stream is empty then {@code true} is
* {@code false} is returned and the predicate is not evaluated. * returned and the predicate is not evaluated.
* *
* <p>This is a short-circuiting terminal operation. * <p>This is a short-circuiting terminal operation.
* *
* \@apiNote * \@apiNote
* This method evaluates the <em>existential quantification</em> of the * This method evaluates the <em>universal quantification</em> of the
* predicate over the elements of the stream (for some x P(x)). * predicate over the elements of the stream (for all x P(x)). If the
* * stream is empty, the quantification is said to be <em>vacuously
* @param pPredicate A non-interfering, stateless predicate to apply to * satisfied</em> and is always {@code true} (regardless of P(x)).
* elements of this stream *
* @return {@code true} if any elements of the stream match the provided * @param pPredicate A non-interfering, stateless predicate to apply to
* predicate, otherwise {@code false} * elements of this stream
*/ * @return {@code true} If either all elements of the stream match the
public boolean anyMatch(FailablePredicate<O,?> pPredicate) { * provided predicate or the stream is empty, otherwise {@code false}.
*/
public boolean allMatch(FailablePredicate<O, ?> pPredicate) {
assertNotTerminated();
return stream().allMatch(Functions.asPredicate(pPredicate));
}
/**
* Returns whether any elements of this stream match the provided
* predicate. May not evaluate the predicate on all elements if not
* necessary for determining the result. If the stream is empty then
* {@code false} is returned and the predicate is not evaluated.
*
* <p>This is a short-circuiting terminal operation.
*
* \@apiNote
* This method evaluates the <em>existential quantification</em> of the
* predicate over the elements of the stream (for some x P(x)).
*
* @param pPredicate A non-interfering, stateless predicate to apply to
* elements of this stream
* @return {@code true} if any elements of the stream match the provided
* predicate, otherwise {@code false}
*/
public boolean anyMatch(FailablePredicate<O, ?> pPredicate) {
assertNotTerminated(); assertNotTerminated();
return stream().anyMatch(Functions.asPredicate(pPredicate)); return stream().anyMatch(Functions.asPredicate(pPredicate));
} }
} }
/** /**
* Converts the given {@link Stream stream} into a {@link FailableStream}. * Converts the given {@link Stream stream} into a {@link FailableStream}.
* This is basically a simplified, reduced version of the {@link Stream} * This is basically a simplified, reduced version of the {@link Stream}
* class, with the same underlying element stream, except that failable * class, with the same underlying element stream, except that failable
* objects, like {@link FailablePredicate}, {@link FailableFunction}, or * objects, like {@link FailablePredicate}, {@link FailableFunction}, or
* {@link FailableConsumer} may be applied, instead of * {@link FailableConsumer} may be applied, instead of
* {@link Predicate}, {@link Function}, or {@link Consumer}. The idea is * {@link Predicate}, {@link Function}, or {@link Consumer}. The idea is
* to rewrite a code snippet like this: * to rewrite a code snippet like this:
* <pre> * <pre>
* final List&lt;O&gt; list; * final List&lt;O&gt; list;
* final Method m; * final Method m;
* final Function&lt;O,String&gt; mapper = (o) -&gt; { * final Function&lt;O,String&gt; mapper = (o) -&gt; {
* try { * try {
* return (String) m.invoke(o); * return (String) m.invoke(o);
* } catch (Throwable t) { * } catch (Throwable t) {
* throw Functions.rethrow(t); * throw Functions.rethrow(t);
* } * }
* }; * };
* final List&lt;String&gt; strList = list.stream() * final List&lt;String&gt; strList = list.stream()
* .map(mapper).collect(Collectors.toList()); * .map(mapper).collect(Collectors.toList());
* </pre> * </pre>
* as follows: * as follows:
* <pre> * <pre>
* final List&lt;O&gt; list; * final List&lt;O&gt; list;
* final Method m; * final Method m;
* final List&lt;String&gt; strList = Functions.stream(list.stream()) * final List&lt;String&gt; strList = Functions.stream(list.stream())
@ -369,12 +370,54 @@ public class Streams {
* intermediate objects, of type FailableStream), it is much more * intermediate objects, of type FailableStream), it is much more
* concise, and readable, and meets the spirit of Lambdas better * concise, and readable, and meets the spirit of Lambdas better
* than the first version. * than the first version.
* @param <O> The streams element type. * @param <O> The streams element type.
* @param pStream The stream, which is being converted. * @param pStream The stream, which is being converted.
* @return The {@link FailableStream}, which has been created by * @return The {@link FailableStream}, which has been created by
* converting the stream. * converting the stream.
*/ */
public static <O> FailableStream<O> stream(Stream<O> pStream) { public static <O> FailableStream<O> stream(Stream<O> pStream) {
return new FailableStream<O>(pStream); return new FailableStream<O>(pStream);
} }
/**
* Converts the given {@link Collection} into a {@link FailableStream}.
* This is basically a simplified, reduced version of the {@link Stream}
* class, with the same underlying element stream, except that failable
* objects, like {@link FailablePredicate}, {@link FailableFunction}, or
* {@link FailableConsumer} may be applied, instead of
* {@link Predicate}, {@link Function}, or {@link Consumer}. The idea is
* to rewrite a code snippet like this:
* <pre>
* final List&lt;O&gt; list;
* final Method m;
* final Function&lt;O,String&gt; mapper = (o) -&gt; {
* try {
* return (String) m.invoke(o);
* } catch (Throwable t) {
* throw Functions.rethrow(t);
* }
* };
* final List&lt;String&gt; strList = list.stream()
* .map(mapper).collect(Collectors.toList());
* </pre>
* as follows:
* <pre>
* final List&lt;O&gt; list;
* final Method m;
* final List&lt;String&gt; strList = Functions.stream(list.stream())
* .map((o) -&gt; (String) m.invoke(o)).collect(Collectors.toList());
* </pre>
* While the second version may not be <em>quite</em> as
* efficient (because it depends on the creation of additional,
* intermediate objects, of type FailableStream), it is much more
* concise, and readable, and meets the spirit of Lambdas better
* than the first version.
* @param <O> The streams element type.
* @param pStream The stream, which is being converted.
* @return The {@link FailableStream}, which has been created by
* converting the stream.
*/
public static <O> FailableStream<O> stream(Collection<O> pStream) {
return stream(pStream.stream());
}
} }

12
src/test/java/org/apache/commons/lang3/StreamsTest.java
View File

@ -16,7 +16,9 @@
*/ */
package org.apache.commons.lang3; package org.apache.commons.lang3;
import static org.junit.jupiter.api.Assertions.*; import static org.junit.jupiter.api.Assertions.assertEquals;
import static org.junit.jupiter.api.Assertions.assertSame;
import static org.junit.jupiter.api.Assertions.fail;
import java.lang.reflect.UndeclaredThrowableException; import java.lang.reflect.UndeclaredThrowableException;
import java.util.ArrayList; import java.util.ArrayList;
@ -62,7 +64,7 @@ class StreamsTest {
} }
} }
protected <T extends Throwable> FailableConsumer<String,T> asIntConsumer(T pThrowable) { protected <T extends Throwable> FailableConsumer<String, T> asIntConsumer(T pThrowable) {
return (s) -> { return (s) -> {
final Integer i = Integer.valueOf(s); final Integer i = Integer.valueOf(s);
if (i.intValue() == 4) { if (i.intValue() == 4) {
@ -105,7 +107,9 @@ class StreamsTest {
final List<String> input = Arrays.asList("1", "2", "3", "4", "5", "6"); final List<String> input = Arrays.asList("1", "2", "3", "4", "5", "6");
final List<Integer> output = Functions.stream(input) final List<Integer> output = Functions.stream(input)
.map((s) -> Integer.valueOf(s)) .map((s) -> Integer.valueOf(s))
.filter((i) -> { return i.intValue() %2 == 0;}) .filter((i) -> {
return i.intValue() %2 == 0;
})
.collect(Collectors.toList()); .collect(Collectors.toList());
assertEvenNumbers(output); assertEvenNumbers(output);
} }
@ -117,7 +121,7 @@ class StreamsTest {
} }
} }
protected <T extends Throwable> FailablePredicate<Integer,T> asIntPredicate(T pThrowable) { protected <T extends Throwable> FailablePredicate<Integer, T> asIntPredicate(T pThrowable) {
return (i) -> { return (i) -> {
if (i.intValue() == 5) { if (i.intValue() == 5) {
if (pThrowable != null) { if (pThrowable != null) {