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* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
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*
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* accompanied this code).
*
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*
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package java8.util.stream;
import java8.util.IntSummaryStatistics;
import java8.util.PrimitiveIterator;
import java8.util.function.BiConsumer;
import java8.util.function.Function;
import java8.util.function.IntBinaryOperator;
import java8.util.function.IntConsumer;
import java8.util.function.IntFunction;
import java8.util.function.IntPredicate;
import java8.util.function.IntSupplier;
import java8.util.function.IntToDoubleFunction;
import java8.util.function.IntToLongFunction;
import java8.util.function.IntUnaryOperator;
import java8.util.function.ObjIntConsumer;
import java8.util.function.Supplier;
import java8.util.OptionalDouble;
import java8.util.OptionalInt;
import java8.util.Spliterator;
/**
* A sequence of primitive int-valued elements supporting sequential and parallel
* aggregate operations. This is the {@code int} primitive specialization of
* {@link Stream}.
*
* The following example illustrates an aggregate operation using
* {@link Stream} and {@link IntStream}, computing the sum of the weights of the
* red widgets:
*
*
{@code
* int sum = widgets.stream()
* .filter(w -> w.getColor() == RED)
* .mapToInt(w -> w.getWeight())
* .sum();
* }
*
* See the class documentation for {@link Stream} and the package documentation
* for java8.util.stream for additional
* specification of streams, stream operations, stream pipelines, and
* parallelism.
*
* @since 1.8
* @see Stream
* @see java8.util.stream
*/
public interface IntStream extends BaseStream {
/**
* Returns a stream consisting of the elements of this stream that match
* the given predicate.
*
* This is an intermediate
* operation.
*
* @param predicate a non-interfering,
* stateless
* predicate to apply to each element to determine if it
* should be included
* @return the new stream
*/
IntStream filter(IntPredicate predicate);
/**
* Returns a stream consisting of the results of applying the given
* function to the elements of this stream.
*
*
This is an intermediate
* operation.
*
* @param mapper a non-interfering,
* stateless
* function to apply to each element
* @return the new stream
*/
IntStream map(IntUnaryOperator mapper);
/**
* Returns an object-valued {@code Stream} consisting of the results of
* applying the given function to the elements of this stream.
*
*
This is an
* intermediate operation.
*
* @param the element type of the new stream
* @param mapper a non-interfering,
* stateless
* function to apply to each element
* @return the new stream
*/
Stream mapToObj(IntFunction mapper);
/**
* Returns a {@code LongStream} consisting of the results of applying the
* given function to the elements of this stream.
*
*
This is an intermediate
* operation.
*
* @param mapper a non-interfering,
* stateless
* function to apply to each element
* @return the new stream
*/
LongStream mapToLong(IntToLongFunction mapper);
/**
* Returns a {@code DoubleStream} consisting of the results of applying the
* given function to the elements of this stream.
*
*
This is an intermediate
* operation.
*
* @param mapper a non-interfering,
* stateless
* function to apply to each element
* @return the new stream
*/
DoubleStream mapToDouble(IntToDoubleFunction mapper);
/**
* Returns a stream consisting of the results of replacing each element of
* this stream with the contents of a mapped stream produced by applying
* the provided mapping function to each element. Each mapped stream is
* {@link java8.util.stream.BaseStream#close() closed} after its contents
* have been placed into this stream. (If a mapped stream is {@code null}
* an empty stream is used, instead.)
*
*
This is an intermediate
* operation.
*
* @param mapper a non-interfering,
* stateless
* function to apply to each element which produces an
* {@code IntStream} of new values
* @return the new stream
* @see Stream#flatMap(Function)
*/
IntStream flatMap(IntFunction mapper);
/**
* Returns a stream consisting of the results of replacing each element of
* this stream with multiple elements, specifically zero or more elements.
* Replacement is performed by applying the provided mapping function to each
* element in conjunction with a {@linkplain IntConsumer consumer} argument
* that accepts replacement elements. The mapping function calls the consumer
* zero or more times to provide the replacement elements.
*
*
This is an intermediate
* operation.
*
*
If the {@linkplain IntConsumer consumer} argument is used outside the scope of
* its application to the mapping function, the results are undefined.
*
*
Implementation Requirements:
* The default implementation invokes {@link #flatMap flatMap} on this stream,
* passing a function that behaves as follows. First, it calls the mapper function
* with an {@code IntConsumer} that accumulates replacement elements into a newly created
* internal buffer. When the mapper function returns, it creates an {@code IntStream} from the
* internal buffer. Finally, it returns this stream to {@code flatMap}.
*
* @param mapper a non-interfering,
* stateless
* function that generates replacement elements
* @return the new stream
* @see Stream#mapMulti Stream.mapMulti
* @since 16
*/
IntStream mapMulti(IntMapMultiConsumer mapper);
/**
* Returns a stream consisting of the distinct elements of this stream.
*
*
This is a stateful
* intermediate operation.
*
* @return the new stream
*/
IntStream distinct();
/**
* Returns a stream consisting of the elements of this stream in sorted
* order.
*
*
This is a stateful
* intermediate operation.
*
* @return the new stream
*/
IntStream sorted();
/**
* Returns a stream consisting of the elements of this stream, additionally
* performing the provided action on each element as elements are consumed
* from the resulting stream.
*
*
This is an intermediate
* operation.
*
*
For parallel stream pipelines, the action may be called at
* whatever time and in whatever thread the element is made available by the
* upstream operation. If the action modifies shared state,
* it is responsible for providing the required synchronization.
*
*
API Note:
This method exists mainly to support debugging, where you want
* to see the elements as they flow past a certain point in a pipeline:
*
{@code
* IntStreams.of(1, 2, 3, 4)
* .filter(e -> e > 2)
* .peek(e -> System.out.println("Filtered value: " + e))
* .map(e -> e * e)
* .peek(e -> System.out.println("Mapped value: " + e))
* .sum();
* }
*
* In cases where the stream implementation is able to optimize away the
* production of some or all the elements (such as with short-circuiting
* operations like {@code findFirst}, or in the example described in
* {@link #count}), the action will not be invoked for those elements.
*
* @param action a
* non-interfering action to perform on the elements as
* they are consumed from the stream
* @return the new stream
*/
IntStream peek(IntConsumer action);
/**
* Returns a stream consisting of the elements of this stream, truncated
* to be no longer than {@code maxSize} in length.
*
*
This is a short-circuiting
* stateful intermediate operation.
*
*
API Note:
* While {@code limit()} is generally a cheap operation on sequential
* stream pipelines, it can be quite expensive on ordered parallel pipelines,
* especially for large values of {@code maxSize}, since {@code limit(n)}
* is constrained to return not just any n elements, but the
* first n elements in the encounter order. Using an unordered
* stream source (such as {@link IntStreams#generate(IntSupplier)}) or removing the
* ordering constraint with {@link #unordered()} may result in significant
* speedups of {@code limit()} in parallel pipelines, if the semantics of
* your situation permit. If consistency with encounter order is required,
* and you are experiencing poor performance or memory utilization with
* {@code limit()} in parallel pipelines, switching to sequential execution
* with {@link #sequential()} may improve performance.
*
* @param maxSize the number of elements the stream should be limited to
* @return the new stream
* @throws IllegalArgumentException if {@code maxSize} is negative
*/
IntStream limit(long maxSize);
/**
* Returns a stream consisting of the remaining elements of this stream
* after discarding the first {@code n} elements of the stream.
* If this stream contains fewer than {@code n} elements then an
* empty stream will be returned.
*
*
This is a stateful
* intermediate operation.
*
*
API Note:
* While {@code skip()} is generally a cheap operation on sequential
* stream pipelines, it can be quite expensive on ordered parallel pipelines,
* especially for large values of {@code n}, since {@code skip(n)}
* is constrained to skip not just any n elements, but the
* first n elements in the encounter order. Using an unordered
* stream source (such as {@link IntStreams#generate(IntSupplier)}) or removing the
* ordering constraint with {@link #unordered()} may result in significant
* speedups of {@code skip()} in parallel pipelines, if the semantics of
* your situation permit. If consistency with encounter order is required,
* and you are experiencing poor performance or memory utilization with
* {@code skip()} in parallel pipelines, switching to sequential execution
* with {@link #sequential()} may improve performance.
*
* @param n the number of leading elements to skip
* @return the new stream
* @throws IllegalArgumentException if {@code n} is negative
*/
IntStream skip(long n);
/**
* Returns, if this stream is ordered, a stream consisting of the longest
* prefix of elements taken from this stream that match the given predicate.
* Otherwise returns, if this stream is unordered, a stream consisting of a
* subset of elements taken from this stream that match the given predicate.
*
*
If this stream is ordered then the longest prefix is a contiguous
* sequence of elements of this stream that match the given predicate. The
* first element of the sequence is the first element of this stream, and
* the element immediately following the last element of the sequence does
* not match the given predicate.
*
*
If this stream is unordered, and some (but not all) elements of this
* stream match the given predicate, then the behavior of this operation is
* nondeterministic; it is free to take any subset of matching elements
* (which includes the empty set).
*
*
Independent of whether this stream is ordered or unordered if all
* elements of this stream match the given predicate then this operation
* takes all elements (the result is the same as the input), or if no
* elements of the stream match the given predicate then no elements are
* taken (the result is an empty stream).
*
*
This is a short-circuiting
* stateful intermediate operation.
*
*
Implementation Requirements:
* The default implementation obtains the {@link #spliterator() spliterator}
* of this stream, wraps that spliterator so as to support the semantics
* of this operation on traversal, and returns a new stream associated with
* the wrapped spliterator. The returned stream preserves the execution
* characteristics of this stream (namely parallel or sequential execution
* as per {@link #isParallel()}) but the wrapped spliterator may choose to
* not support splitting. When the returned stream is closed, the close
* handlers for both the returned and this stream are invoked.
*
*
API Note:
* While {@code takeWhile()} is generally a cheap operation on sequential
* stream pipelines, it can be quite expensive on ordered parallel
* pipelines, since the operation is constrained to return not just any
* valid prefix, but the longest prefix of elements in the encounter order.
* Using an unordered stream source (such as {@link IntStreams#generate(IntSupplier)})
* or removing the ordering constraint with {@link #unordered()} may result
* in significant speedups of {@code takeWhile()} in parallel pipelines, if
* the semantics of your situation permit. If consistency with encounter
* order is required, and you are experiencing poor performance or memory
* utilization with {@code takeWhile()} in parallel pipelines, switching to
* sequential execution with {@link #sequential()} may improve performance.
*
* @param predicate a non-interfering,
* stateless
* predicate to apply to elements to determine the longest
* prefix of elements.
* @return the new stream
* @since 9
*/
IntStream takeWhile(IntPredicate predicate);
/**
* Returns, if this stream is ordered, a stream consisting of the remaining
* elements of this stream after dropping the longest prefix of elements
* that match the given predicate. Otherwise returns, if this stream is
* unordered, a stream consisting of the remaining elements of this stream
* after dropping a subset of elements that match the given predicate.
*
*
If this stream is ordered then the longest prefix is a contiguous
* sequence of elements of this stream that match the given predicate. The
* first element of the sequence is the first element of this stream, and
* the element immediately following the last element of the sequence does
* not match the given predicate.
*
*
If this stream is unordered, and some (but not all) elements of this
* stream match the given predicate, then the behavior of this operation is
* nondeterministic; it is free to drop any subset of matching elements
* (which includes the empty set).
*
*
Independent of whether this stream is ordered or unordered if all
* elements of this stream match the given predicate then this operation
* drops all elements (the result is an empty stream), or if no elements of
* the stream match the given predicate then no elements are dropped (the
* result is the same as the input).
*
*
This is a stateful
* intermediate operation.
*
*
Implementation Requirements:
* The default implementation obtains the {@link #spliterator() spliterator}
* of this stream, wraps that spliterator so as to support the semantics
* of this operation on traversal, and returns a new stream associated with
* the wrapped spliterator. The returned stream preserves the execution
* characteristics of this stream (namely parallel or sequential execution
* as per {@link #isParallel()}) but the wrapped spliterator may choose to
* not support splitting. When the returned stream is closed, the close
* handlers for both the returned and this stream are invoked.
*
*
API Note:
* While {@code dropWhile()} is generally a cheap operation on sequential
* stream pipelines, it can be quite expensive on ordered parallel
* pipelines, since the operation is constrained to return not just any
* valid prefix, but the longest prefix of elements in the encounter order.
* Using an unordered stream source (such as {@link IntStreams#generate(IntSupplier)})
* or removing the ordering constraint with {@link #unordered()} may result
* in significant speedups of {@code dropWhile()} in parallel pipelines, if
* the semantics of your situation permit. If consistency with encounter
* order is required, and you are experiencing poor performance or memory
* utilization with {@code dropWhile()} in parallel pipelines, switching to
* sequential execution with {@link #sequential()} may improve performance.
*
* @param predicate a non-interfering,
* stateless
* predicate to apply to elements to determine the longest
* prefix of elements.
* @return the new stream
* @since 9
*/
IntStream dropWhile(IntPredicate predicate);
/**
* Performs an action for each element of this stream.
*
*
This is a terminal
* operation.
*
*
For parallel stream pipelines, this operation does not
* guarantee to respect the encounter order of the stream, as doing so
* would sacrifice the benefit of parallelism. For any given element, the
* action may be performed at whatever time and in whatever thread the
* library chooses. If the action accesses shared state, it is
* responsible for providing the required synchronization.
*
* @param action a
* non-interfering action to perform on the elements
*/
void forEach(IntConsumer action);
/**
* Performs an action for each element of this stream, guaranteeing that
* each element is processed in encounter order for streams that have a
* defined encounter order.
*
*
This is a terminal
* operation.
*
* @param action a
* non-interfering action to perform on the elements
* @see #forEach(IntConsumer)
*/
void forEachOrdered(IntConsumer action);
/**
* Returns an array containing the elements of this stream.
*
*
This is a terminal
* operation.
*
* @return an array containing the elements of this stream
*/
int[] toArray();
/**
* Performs a reduction on the
* elements of this stream, using the provided identity value and an
* associative
* accumulation function, and returns the reduced value. This is equivalent
* to:
*
{@code
* int result = identity;
* for (int element : this stream)
* result = accumulator.applyAsInt(result, element)
* return result;
* }
*
* but is not constrained to execute sequentially.
*
* The {@code identity} value must be an identity for the accumulator
* function. This means that for all {@code x},
* {@code accumulator.apply(identity, x)} is equal to {@code x}.
* The {@code accumulator} function must be an
* associative function.
*
*
This is a terminal
* operation.
*
*
API Note:
Sum, min and max are all special cases of
* reduction that can be expressed using this method.
* For example, summing a stream can be expressed as:
*
*
{@code
* int sum = integers.reduce(0, (a, b) -> a+b);
* }
*
* or more compactly:
*
* {@code
* int sum = integers.reduce(0, Integer::sum);
* }
*
* 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 identity the identity value for the accumulating function
* @param op an associative,
* non-interfering,
* stateless
* function for combining two values
* @return the result of the reduction
* @see #sum()
* @see #min()
* @see #max()
* @see #average()
*/
int reduce(int identity, IntBinaryOperator op);
/**
* Performs a reduction on the
* elements of this stream, using an
* associative accumulation
* function, and returns an {@code OptionalInt} describing the reduced value,
* if any. This is equivalent to:
*
{@code
* boolean foundAny = false;
* int result = null;
* for (int element : this stream) {
* if (!foundAny) {
* foundAny = true;
* result = element;
* }
* else
* result = accumulator.applyAsInt(result, element);
* }
* return foundAny ? OptionalInt.of(result) : OptionalInt.empty();
* }
*
* but is not constrained to execute sequentially.
*
* The {@code accumulator} function must be an
* associative function.
*
*
This is a terminal
* operation.
*
* @param op an associative,
* non-interfering,
* stateless
* function for combining two values
* @return the result of the reduction
* @see #reduce(int, IntBinaryOperator)
*/
OptionalInt reduce(IntBinaryOperator op);
/**
* Performs a mutable
* reduction operation on the elements of this stream. A mutable
* reduction is one in which the reduced value is a mutable result container,
* such as an {@code ArrayList}, and elements are incorporated by updating
* the state of the result rather than by replacing the result. This
* produces a result equivalent to:
*
{@code
* R result = supplier.get();
* for (int element : this stream)
* accumulator.accept(result, element);
* return result;
* }
*
* Like {@link #reduce(int, IntBinaryOperator)}, {@code collect} operations
* can be parallelized without requiring additional synchronization.
*
*
This is a terminal
* operation.
*
* @param the type of the mutable result container
* @param supplier a function that creates a new mutable result container.
* For a parallel execution, this function may be called
* multiple times and must return a fresh value each time
* @param accumulator an associative,
* non-interfering,
* stateless
* function that must fold an element into a result
* container
* @param combiner an associative,
* non-interfering,
* stateless
* function that accepts two partial result containers
* and merges them, which must be compatible with the
* accumulator function. The combiner function must fold
* the elements from the second result container into the
* first result container
* @return the result of the reduction
* @see Stream#collect(Supplier, BiConsumer, BiConsumer)
*/
R collect(Supplier supplier,
ObjIntConsumer accumulator,
BiConsumer combiner);
/**
* Returns the sum of elements in this stream. This is a special case
* of a reduction
* and is equivalent to:
* {@code
* return reduce(0, Integer::sum);
* }
*
* This is a terminal
* operation.
*
* @return the sum of elements in this stream
*/
int sum();
/**
* Returns an {@code OptionalInt} describing the minimum element of this
* stream, or an empty optional if this stream is empty. This is a special
* case of a reduction
* and is equivalent to:
*
{@code
* return reduce(Integer::min);
* }
*
* This is a terminal operation.
*
* @return an {@code OptionalInt} containing the minimum element of this
* stream, or an empty {@code OptionalInt} if the stream is empty
*/
OptionalInt min();
/**
* Returns an {@code OptionalInt} describing the maximum element of this
* stream, or an empty optional if this stream is empty. This is a special
* case of a reduction
* and is equivalent to:
*
{@code
* return reduce(Integer::max);
* }
*
* This is a terminal
* operation.
*
* @return an {@code OptionalInt} containing the maximum element of this
* stream, or an empty {@code OptionalInt} if the stream is empty
*/
OptionalInt max();
/**
* Returns the count of elements in this stream. This is a special case of
* a reduction and is (at least
* in the predominant case where the count can't be directly obtained from
* the stream source) equivalent to:
*
{@code
* return mapToLong(e -> 1L).sum();
* }
*
* This is a terminal operation.
*
*
API Note:
* An implementation may choose to not execute the stream pipeline (either
* sequentially or in parallel) if it is capable of computing the count
* directly from the stream source. In such cases no source elements will
* be traversed and no intermediate operations will be evaluated.
* Behavioral parameters with side-effects, which are strongly discouraged
* except for harmless cases such as debugging, may be affected. For
* example, consider the following stream:
*
{@code
* IntStream s = IntStreams.of(1, 2, 3, 4);
* long count = s.peek(System.out::println).count();
* }
* The number of elements covered by the stream source is known and the
* intermediate operation, {@code peek}, does not inject into or remove
* elements from the stream (as may be the case for {@code flatMap} or
* {@code filter} operations). Thus the count is 4 and there is no need to
* execute the pipeline and, as a side-effect, print out the elements.
*
* @return the count of elements in this stream
*/
long count();
/**
* Returns an {@code OptionalDouble} describing the arithmetic mean of elements of
* this stream, or an empty optional if this stream is empty. This is a
* special case of a
* reduction.
*
* This is a terminal
* operation.
*
* @return an {@code OptionalDouble} containing the average element of this
* stream, or an empty optional if the stream is empty
*/
OptionalDouble average();
/**
* Returns an {@code IntSummaryStatistics} describing various
* summary data about the elements of this stream. This is a special
* case of a reduction.
*
*
This is a terminal
* operation.
*
* @return an {@code IntSummaryStatistics} describing various summary data
* about the elements of this stream
*/
IntSummaryStatistics summaryStatistics();
/**
* 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.
*
*
This is a short-circuiting
* terminal operation.
*
*
API Note:
* This method evaluates the existential quantification of the
* predicate over the elements of the stream (for some x P(x)).
*
* @param predicate 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}
*/
boolean anyMatch(IntPredicate predicate);
/**
* Returns whether all 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 true} is
* returned and the predicate is not evaluated.
*
*
This is a short-circuiting
* terminal operation.
*
*
API Note:
* This method evaluates the universal quantification 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 vacuously
* satisfied and is always {@code true} (regardless of P(x)).
*
* @param predicate 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}
*/
boolean allMatch(IntPredicate predicate);
/**
* Returns whether no 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 true} is
* returned and the predicate is not evaluated.
*
*
This is a short-circuiting
* terminal operation.
*
*
API Note:
* This method evaluates the universal quantification of the
* negated predicate over the elements of the stream (for all x ~P(x)). If
* the stream is empty, the quantification is said to be vacuously satisfied
* and is always {@code true}, regardless of P(x).
*
* @param predicate a non-interfering,
* stateless
* predicate to apply to elements of this stream
* @return {@code true} if either no elements of the stream match the
* provided predicate or the stream is empty, otherwise {@code false}
*/
boolean noneMatch(IntPredicate predicate);
/**
* Returns an {@link OptionalInt} describing the first element of this
* stream, or an empty {@code OptionalInt} if the stream is empty. If the
* stream has no encounter order, then any element may be returned.
*
*
This is a short-circuiting
* terminal operation.
*
* @return an {@code OptionalInt} describing the first element of this stream,
* or an empty {@code OptionalInt} if the stream is empty
*/
OptionalInt findFirst();
/**
* Returns an {@link OptionalInt} describing some element of the stream, or
* an empty {@code OptionalInt} if the stream is empty.
*
*
This is a short-circuiting
* terminal operation.
*
*
The behavior of this operation is explicitly nondeterministic; it is
* free to select any element in the stream. This is to allow for maximal
* performance in parallel operations; the cost is that multiple invocations
* on the same source may not return the same result. (If a stable result
* is desired, use {@link #findFirst()} instead.)
*
* @return an {@code OptionalInt} describing some element of this stream, or
* an empty {@code OptionalInt} if the stream is empty
* @see #findFirst()
*/
OptionalInt findAny();
/**
* Returns a {@code LongStream} consisting of the elements of this stream,
* converted to {@code long}.
*
*
This is an intermediate
* operation.
*
* @return a {@code LongStream} consisting of the elements of this stream,
* converted to {@code long}
*/
LongStream asLongStream();
/**
* Returns a {@code DoubleStream} consisting of the elements of this stream,
* converted to {@code double}.
*
*
This is an intermediate
* operation.
*
* @return a {@code DoubleStream} consisting of the elements of this stream,
* converted to {@code double}
*/
DoubleStream asDoubleStream();
/**
* Returns a {@code Stream} consisting of the elements of this stream,
* each boxed to an {@code Integer}.
*
*
This is an intermediate
* operation.
*
* @return a {@code Stream} consistent of the elements of this stream,
* each boxed to an {@code Integer}
*/
Stream boxed();
@Override
IntStream sequential();
@Override
IntStream parallel();
@Override
PrimitiveIterator.OfInt iterator();
@Override
Spliterator.OfInt spliterator();
/**
* A mutable builder for an {@code IntStream}.
*
* A stream builder has a lifecycle, which starts in a building
* phase, during which elements can be added, and then transitions to a built
* phase, after which elements may not be added. The built phase
* begins when the {@link #build()} method is called, which creates an
* ordered stream whose elements are the elements that were added to the
* stream builder, in the order they were added.
*
* @see IntStreams#builder()
* @since 1.8
*/
public interface Builder extends IntConsumer {
/**
* Adds an element to the stream being built.
*
* @throws IllegalStateException if the builder has already transitioned
* to the built state
*/
@Override
void accept(int t);
/**
* Adds an element to the stream being built.
*
*
Implementation Requirements:
* The default implementation behaves as if:
*
{@code
* accept(t)
* return this;
* }
*
* @param t the element to add
* @return {@code this} builder
* @throws IllegalStateException if the builder has already transitioned
* to the built state
*/
Builder add(int t);
/**
* Builds the stream, transitioning this builder to the built state.
* An {@code IllegalStateException} is thrown if there are further
* attempts to operate on the builder after it has entered the built
* state.
*
* @return the built stream
* @throws IllegalStateException if the builder has already transitioned to
* the built state
*/
IntStream build();
}
/**
* Represents an operation that accepts an {@code int}-valued argument
* and an IntConsumer, and returns no result. This functional interface is
* used by {@link IntStream#mapMulti(IntStream.IntMapMultiConsumer)
* IntStream.mapMulti} to replace an int value with zero or more int values.
*
* This is a functional interface
* whose functional method is {@link #accept(int, IntConsumer)}.
*
* @see IntStream#mapMulti
*
* @since 16
*/
interface IntMapMultiConsumer {
/**
* Replaces the given {@code value} with zero or more values by feeding the mapped
* values to the {@code ic} consumer.
*
* @param value the int value coming from upstream
* @param ic an {@code IntConsumer} accepting the mapped values
*/
void accept(int value, IntConsumer ic);
}
}