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Java example source code file (Stream.java)

This example Java source code file (Stream.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

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Java - Java tags/keywords

biconsumer, binaryoperator, builder, doublestream, intstream, longstream, optional, override, safevarargs, spliterator, stream, suppresswarnings, threading, threads, util

The Stream.java Java example source code

/*
 * Copyright (c) 2012, 2013, Oracle and/or its affiliates. All rights reserved.
 * 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
 * particular file as subject to the "Classpath" exception as provided
 * by Oracle in the LICENSE file that accompanied this code.
 *
 * This code is distributed in the hope that it will be useful, but WITHOUT
 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
 * FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License
 * version 2 for more details (a copy is included in the LICENSE file that
 * accompanied this code).
 *
 * You should have received a copy of the GNU General Public License version
 * 2 along with this work; if not, write to the Free Software Foundation,
 * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
 *
 * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
 * or visit www.oracle.com if you need additional information or have any
 * questions.
 */
package java.util.stream;

import java.nio.charset.Charset;
import java.nio.file.Files;
import java.nio.file.Path;
import java.util.Arrays;
import java.util.Collection;
import java.util.Comparator;
import java.util.Iterator;
import java.util.Objects;
import java.util.Optional;
import java.util.Spliterator;
import java.util.Spliterators;
import java.util.concurrent.ConcurrentHashMap;
import java.util.function.BiConsumer;
import java.util.function.BiFunction;
import java.util.function.BinaryOperator;
import java.util.function.Consumer;
import java.util.function.Function;
import java.util.function.IntFunction;
import java.util.function.Predicate;
import java.util.function.Supplier;
import java.util.function.ToDoubleFunction;
import java.util.function.ToIntFunction;
import java.util.function.ToLongFunction;
import java.util.function.UnaryOperator;

/**
 * A sequence of elements supporting sequential and parallel aggregate
 * operations.  The following example illustrates an aggregate operation using
 * {@link Stream} and {@link IntStream}:
 *
 * <pre>{@code
 *     int sum = widgets.stream()
 *                      .filter(w -> w.getColor() == RED)
 *                      .mapToInt(w -> w.getWeight())
 *                      .sum();
 * }</pre>
 *
 * In this example, {@code widgets} is a {@code Collection<Widget>}.  We create
 * a stream of {@code Widget} objects via {@link Collection#stream Collection.stream()},
 * filter it to produce a stream containing only the red widgets, and then
 * transform it into a stream of {@code int} values representing the weight of
 * each red widget. Then this stream is summed to produce a total weight.
 *
 * <p>In addition to {@code Stream}, which is a stream of object references,
 * there are primitive specializations for {@link IntStream}, {@link LongStream},
 * and {@link DoubleStream}, all of which are referred to as "streams" and
 * conform to the characteristics and restrictions described here.
 *
 * <p>To perform a computation, stream
 * <a href="package-summary.html#StreamOps">operations are composed into a
 * <em>stream pipeline.  A stream pipeline consists of a source (which
 * might be an array, a collection, a generator function, an I/O channel,
 * etc), zero or more <em>intermediate operations (which transform a
 * stream into another stream, such as {@link Stream#filter(Predicate)}), and a
 * <em>terminal operation (which produces a result or side-effect, such
 * as {@link Stream#count()} or {@link Stream#forEach(Consumer)}).
 * Streams are lazy; computation on the source data is only performed when the
 * terminal operation is initiated, and source elements are consumed only
 * as needed.
 *
 * <p>Collections and streams, while bearing some superficial similarities,
 * have different goals.  Collections are primarily concerned with the efficient
 * management of, and access to, their elements.  By contrast, streams do not
 * provide a means to directly access or manipulate their elements, and are
 * instead concerned with declaratively describing their source and the
 * computational operations which will be performed in aggregate on that source.
 * However, if the provided stream operations do not offer the desired
 * functionality, the {@link #iterator()} and {@link #spliterator()} operations
 * can be used to perform a controlled traversal.
 *
 * <p>A stream pipeline, like the "widgets" example above, can be viewed as
 * a <em>query on the stream source.  Unless the source was explicitly
 * designed for concurrent modification (such as a {@link ConcurrentHashMap}),
 * unpredictable or erroneous behavior may result from modifying the stream
 * source while it is being queried.
 *
 * <p>Most stream operations accept parameters that describe user-specified
 * behavior, such as the lambda expression {@code w -> w.getWeight()} passed to
 * {@code mapToInt} in the example above.  To preserve correct behavior,
 * these <em>behavioral parameters:
 * <ul>
 * <li>must be non-interfering
 * (they do not modify the stream source); and</li>
 * <li>in most cases must be stateless
 * (their result should not depend on any state that might change during execution
 * of the stream pipeline).</li>
 * </ul>
 *
 * <p>Such parameters are always instances of a
 * <a href="../function/package-summary.html">functional interface such
 * as {@link java.util.function.Function}, and are often lambda expressions or
 * method references.  Unless otherwise specified these parameters must be
 * <em>non-null.
 *
 * <p>A stream should be operated on (invoking an intermediate or terminal stream
 * operation) only once.  This rules out, for example, "forked" streams, where
 * the same source feeds two or more pipelines, or multiple traversals of the
 * same stream.  A stream implementation may throw {@link IllegalStateException}
 * if it detects that the stream is being reused. However, since some stream
 * operations may return their receiver rather than a new stream object, it may
 * not be possible to detect reuse in all cases.
 *
 * <p>Streams have a {@link #close()} method and implement {@link AutoCloseable},
 * but nearly all stream instances do not actually need to be closed after use.
 * Generally, only streams whose source is an IO channel (such as those returned
 * by {@link Files#lines(Path, Charset)}) will require closing.  Most streams
 * are backed by collections, arrays, or generating functions, which require no
 * special resource management.  (If a stream does require closing, it can be
 * declared as a resource in a {@code try}-with-resources statement.)
 *
 * <p>Stream pipelines may execute either sequentially or in
 * <a href="package-summary.html#Parallelism">parallel.  This
 * execution mode is a property of the stream.  Streams are created
 * with an initial choice of sequential or parallel execution.  (For example,
 * {@link Collection#stream() Collection.stream()} creates a sequential stream,
 * and {@link Collection#parallelStream() Collection.parallelStream()} creates
 * a parallel one.)  This choice of execution mode may be modified by the
 * {@link #sequential()} or {@link #parallel()} methods, and may be queried with
 * the {@link #isParallel()} method.
 *
 * @param <T> the type of the stream elements
 * @since 1.8
 * @see IntStream
 * @see LongStream
 * @see DoubleStream
 * @see <a href="package-summary.html">java.util.stream
 */
public interface Stream<T> extends BaseStream> {

    /**
     * Returns a stream consisting of the elements of this stream that match
     * the given predicate.
     *
     * <p>This is an intermediate
     * operation</a>.
     *
     * @param predicate a <a href="package-summary.html#NonInterference">non-interfering,
     *                  <a href="package-summary.html#Statelessness">stateless
     *                  predicate to apply to each element to determine if it
     *                  should be included
     * @return the new stream
     */
    Stream<T> filter(Predicate predicate);

    /**
     * Returns a stream consisting of the results of applying the given
     * function to the elements of this stream.
     *
     * <p>This is an intermediate
     * operation</a>.
     *
     * @param <R> The element type of the new stream
     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering,
     *               <a href="package-summary.html#Statelessness">stateless
     *               function to apply to each element
     * @return the new stream
     */
    <R> Stream map(Function mapper);

    /**
     * Returns an {@code IntStream} consisting of the results of applying the
     * given function to the elements of this stream.
     *
     * <p>This is an 
     *     intermediate operation</a>.
     *
     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering,
     *               <a href="package-summary.html#Statelessness">stateless
     *               function to apply to each element
     * @return the new stream
     */
    IntStream mapToInt(ToIntFunction<? super T> mapper);

    /**
     * Returns a {@code LongStream} consisting of the results of applying the
     * given function to the elements of this stream.
     *
     * <p>This is an intermediate
     * operation</a>.
     *
     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering,
     *               <a href="package-summary.html#Statelessness">stateless
     *               function to apply to each element
     * @return the new stream
     */
    LongStream mapToLong(ToLongFunction<? super T> mapper);

    /**
     * Returns a {@code DoubleStream} consisting of the results of applying the
     * given function to the elements of this stream.
     *
     * <p>This is an intermediate
     * operation</a>.
     *
     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering,
     *               <a href="package-summary.html#Statelessness">stateless
     *               function to apply to each element
     * @return the new stream
     */
    DoubleStream mapToDouble(ToDoubleFunction<? super T> 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 java.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.)
     *
     * <p>This is an intermediate
     * operation</a>.
     *
     * @apiNote
     * The {@code flatMap()} operation has the effect of applying a one-to-many
     * transformation to the elements of the stream, and then flattening the
     * resulting elements into a new stream.
     *
     * <p>Examples.
     *
     * <p>If {@code orders} is a stream of purchase orders, and each purchase
     * order contains a collection of line items, then the following produces a
     * stream containing all the line items in all the orders:
     * <pre>{@code
     *     orders.flatMap(order -> order.getLineItems().stream())...
     * }</pre>
     *
     * <p>If {@code path} is the path to a file, then the following produces a
     * stream of the {@code words} contained in that file:
     * <pre>{@code
     *     Stream<String> lines = Files.lines(path, StandardCharsets.UTF_8);
     *     Stream<String> words = lines.flatMap(line -> Stream.of(line.split(" +")));
     * }</pre>
     * The {@code mapper} function passed to {@code flatMap} splits a line,
     * using a simple regular expression, into an array of words, and then
     * creates a stream of words from that array.
     *
     * @param <R> The element type of the new stream
     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering,
     *               <a href="package-summary.html#Statelessness">stateless
     *               function to apply to each element which produces a stream
     *               of new values
     * @return the new stream
     */
    <R> Stream flatMap(Function> mapper);

    /**
     * Returns an {@code IntStream} 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 java.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.)
     *
     * <p>This is an intermediate
     * operation</a>.
     *
     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering,
     *               <a href="package-summary.html#Statelessness">stateless
     *               function to apply to each element which produces a stream
     *               of new values
     * @return the new stream
     * @see #flatMap(Function)
     */
    IntStream flatMapToInt(Function<? super T, ? extends IntStream> mapper);

    /**
     * Returns an {@code LongStream} 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 java.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.)
     *
     * <p>This is an intermediate
     * operation</a>.
     *
     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering,
     *               <a href="package-summary.html#Statelessness">stateless
     *               function to apply to each element which produces a stream
     *               of new values
     * @return the new stream
     * @see #flatMap(Function)
     */
    LongStream flatMapToLong(Function<? super T, ? extends LongStream> mapper);

    /**
     * Returns an {@code DoubleStream} 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 java.util.stream.BaseStream#close() closed} after its
     * contents have placed been into this stream.  (If a mapped stream is
     * {@code null} an empty stream is used, instead.)
     *
     * <p>This is an intermediate
     * operation</a>.
     *
     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering,
     *               <a href="package-summary.html#Statelessness">stateless
     *               function to apply to each element which produces a stream
     *               of new values
     * @return the new stream
     * @see #flatMap(Function)
     */
    DoubleStream flatMapToDouble(Function<? super T, ? extends DoubleStream> mapper);

    /**
     * Returns a stream consisting of the distinct elements (according to
     * {@link Object#equals(Object)}) of this stream.
     *
     * <p>For ordered streams, the selection of distinct elements is stable
     * (for duplicated elements, the element appearing first in the encounter
     * order is preserved.)  For unordered streams, no stability guarantees
     * are made.
     *
     * <p>This is a stateful
     * intermediate operation</a>.
     *
     * @apiNote
     * Preserving stability for {@code distinct()} in parallel pipelines is
     * relatively expensive (requires that the operation act as a full barrier,
     * with substantial buffering overhead), and stability is often not needed.
     * Using an unordered stream source (such as {@link #generate(Supplier)})
     * or removing the ordering constraint with {@link #unordered()} may result
     * in significantly more efficient execution for {@code distinct()} 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 distinct()} in parallel pipelines,
     * switching to sequential execution with {@link #sequential()} may improve
     * performance.
     *
     * @return the new stream
     */
    Stream<T> distinct();

    /**
     * Returns a stream consisting of the elements of this stream, sorted
     * according to natural order.  If the elements of this stream are not
     * {@code Comparable}, a {@code java.lang.ClassCastException} may be thrown
     * when the terminal operation is executed.
     *
     * <p>For ordered streams, the sort is stable.  For unordered streams, no
     * stability guarantees are made.
     *
     * <p>This is a stateful
     * intermediate operation</a>.
     *
     * @return the new stream
     */
    Stream<T> sorted();

    /**
     * Returns a stream consisting of the elements of this stream, sorted
     * according to the provided {@code Comparator}.
     *
     * <p>For ordered streams, the sort is stable.  For unordered streams, no
     * stability guarantees are made.
     *
     * <p>This is a stateful
     * intermediate operation</a>.
     *
     * @param comparator a <a href="package-summary.html#NonInterference">non-interfering,
     *                   <a href="package-summary.html#Statelessness">stateless
     *                   {@code Comparator} to be used to compare stream elements
     * @return the new stream
     */
    Stream<T> sorted(Comparator comparator);

    /**
     * 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.
     *
     * <p>This is an intermediate
     * operation</a>.
     *
     * <p>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.
     *
     * @apiNote This method exists mainly to support debugging, where you want
     * to see the elements as they flow past a certain point in a pipeline:
     * <pre>{@code
     *     Stream.of("one", "two", "three", "four")
     *         .filter(e -> e.length() > 3)
     *         .peek(e -> System.out.println("Filtered value: " + e))
     *         .map(String::toUpperCase)
     *         .peek(e -> System.out.println("Mapped value: " + e))
     *         .collect(Collectors.toList());
     * }</pre>
     *
     * @param action a <a href="package-summary.html#NonInterference">
     *                 non-interfering</a> action to perform on the elements as
     *                 they are consumed from the stream
     * @return the new stream
     */
    Stream<T> peek(Consumer action);

    /**
     * Returns a stream consisting of the elements of this stream, truncated
     * to be no longer than {@code maxSize} in length.
     *
     * <p>This is a short-circuiting
     * stateful intermediate operation</a>.
     *
     * @apiNote
     * 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 <em>n elements, but the
     * <em>first n elements in the encounter order.  Using an unordered
     * stream source (such as {@link #generate(Supplier)}) 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
     */
    Stream<T> 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.
     *
     * <p>This is a stateful
     * intermediate operation</a>.
     *
     * @apiNote
     * 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 <em>n elements, but the
     * <em>first n elements in the encounter order.  Using an unordered
     * stream source (such as {@link #generate(Supplier)}) 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
     */
    Stream<T> skip(long n);

    /**
     * Performs an action for each element of this stream.
     *
     * <p>This is a terminal
     * operation</a>.
     *
     * <p>The behavior of this operation is explicitly nondeterministic.
     * For parallel stream pipelines, this operation does <em>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 <a href="package-summary.html#NonInterference">
     *               non-interfering</a> action to perform on the elements
     */
    void forEach(Consumer<? super T> action);

    /**
     * Performs an action for each element of this stream, in the encounter
     * order of the stream if the stream has a defined encounter order.
     *
     * <p>This is a terminal
     * operation</a>.
     *
     * <p>This operation processes the elements one at a time, in encounter
     * order if one exists.  Performing the action for one element
     * <a href="../concurrent/package-summary.html#MemoryVisibility">happens-before
     * performing the action for subsequent elements, but for any given element,
     * the action may be performed in whatever thread the library chooses.
     *
     * @param action a <a href="package-summary.html#NonInterference">
     *               non-interfering</a> action to perform on the elements
     * @see #forEach(Consumer)
     */
    void forEachOrdered(Consumer<? super T> action);

    /**
     * Returns an array containing the elements of this stream.
     *
     * <p>This is a terminal
     * operation</a>.
     *
     * @return an array containing the elements of this stream
     */
    Object[] toArray();

    /**
     * Returns an array containing the elements of this stream, using the
     * provided {@code generator} function to allocate the returned array, as
     * well as any additional arrays that might be required for a partitioned
     * execution or for resizing.
     *
     * <p>This is a terminal
     * operation</a>.
     *
     * @apiNote
     * The generator function takes an integer, which is the size of the
     * desired array, and produces an array of the desired size.  This can be
     * concisely expressed with an array constructor reference:
     * <pre>{@code
     *     Person[] men = people.stream()
     *                          .filter(p -> p.getGender() == MALE)
     *                          .toArray(Person[]::new);
     * }</pre>
     *
     * @param <A> the element type of the resulting array
     * @param generator a function which produces a new array of the desired
     *                  type and the provided length
     * @return an array containing the elements in this stream
     * @throws ArrayStoreException if the runtime type of the array returned
     * from the array generator is not a supertype of the runtime type of every
     * element in this stream
     */
    <A> A[] toArray(IntFunction generator);

    /**
     * Performs a <a href="package-summary.html#Reduction">reduction on the
     * elements of this stream, using the provided identity value and an
     * <a href="package-summary.html#Associativity">associative
     * accumulation function, and returns the reduced value.  This is equivalent
     * to:
     * <pre>{@code
     *     T result = identity;
     *     for (T element : this stream)
     *         result = accumulator.apply(result, element)
     *     return result;
     * }</pre>
     *
     * but is not constrained to execute sequentially.
     *
     * <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
     * <a href="package-summary.html#Associativity">associative function.
     *
     * <p>This is a terminal
     * operation</a>.
     *
     * @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 identity the identity value for the accumulating function
     * @param accumulator an <a href="package-summary.html#Associativity">associative,
     *                    <a href="package-summary.html#NonInterference">non-interfering,
     *                    <a href="package-summary.html#Statelessness">stateless
     *                    function for combining two values
     * @return the result of the reduction
     */
    T reduce(T identity, BinaryOperator<T> accumulator);

    /**
     * Performs a <a href="package-summary.html#Reduction">reduction on the
     * elements of this stream, using an
     * <a href="package-summary.html#Associativity">associative accumulation
     * function, and returns an {@code Optional} describing the reduced value,
     * if any. This is equivalent to:
     * <pre>{@code
     *     boolean foundAny = false;
     *     T result = null;
     *     for (T element : this stream) {
     *         if (!foundAny) {
     *             foundAny = true;
     *             result = element;
     *         }
     *         else
     *             result = accumulator.apply(result, element);
     *     }
     *     return foundAny ? Optional.of(result) : Optional.empty();
     * }</pre>
     *
     * but is not constrained to execute sequentially.
     *
     * <p>The {@code accumulator} function must be an
     * <a href="package-summary.html#Associativity">associative function.
     *
     * <p>This is a terminal
     * operation</a>.
     *
     * @param accumulator an <a href="package-summary.html#Associativity">associative,
     *                    <a href="package-summary.html#NonInterference">non-interfering,
     *                    <a href="package-summary.html#Statelessness">stateless
     *                    function for combining two values
     * @return an {@link Optional} describing the result of the reduction
     * @throws NullPointerException if the result of the reduction is null
     * @see #reduce(Object, BinaryOperator)
     * @see #min(Comparator)
     * @see #max(Comparator)
     */
    Optional<T> reduce(BinaryOperator accumulator);

    /**
     * Performs a <a href="package-summary.html#Reduction">reduction on the
     * elements of this stream, using the provided identity, accumulation and
     * combining functions.  This is equivalent to:
     * <pre>{@code
     *     U result = identity;
     *     for (T element : this stream)
     *         result = accumulator.apply(result, element)
     *     return result;
     * }</pre>
     *
     * but is not constrained to execute sequentially.
     *
     * <p>The {@code identity} value must be an identity for the combiner
     * function.  This means that for all {@code u}, {@code combiner(identity, u)}
     * is equal to {@code u}.  Additionally, the {@code combiner} function
     * must be compatible with the {@code accumulator} function; for all
     * {@code u} and {@code t}, the following must hold:
     * <pre>{@code
     *     combiner.apply(u, accumulator.apply(identity, t)) == accumulator.apply(u, t)
     * }</pre>
     *
     * <p>This is a terminal
     * operation</a>.
     *
     * @apiNote Many reductions using this form can be represented more simply
     * by an explicit combination of {@code map} and {@code reduce} operations.
     * The {@code accumulator} function acts as a fused mapper and accumulator,
     * which can sometimes be more efficient than separate mapping and reduction,
     * such as when knowing the previously reduced value allows you to avoid
     * some computation.
     *
     * @param <U> The type of the result
     * @param identity the identity value for the combiner function
     * @param accumulator an <a href="package-summary.html#Associativity">associative,
     *                    <a href="package-summary.html#NonInterference">non-interfering,
     *                    <a href="package-summary.html#Statelessness">stateless
     *                    function for incorporating an additional element into a result
     * @param combiner an <a href="package-summary.html#Associativity">associative,
     *                    <a href="package-summary.html#NonInterference">non-interfering,
     *                    <a href="package-summary.html#Statelessness">stateless
     *                    function for combining two values, which must be
     *                    compatible with the accumulator function
     * @return the result of the reduction
     * @see #reduce(BinaryOperator)
     * @see #reduce(Object, BinaryOperator)
     */
    <U> U reduce(U identity,
                 BiFunction<U, ? super T, U> accumulator,
                 BinaryOperator<U> combiner);

    /**
     * Performs a <a href="package-summary.html#MutableReduction">mutable
     * reduction</a> 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:
     * <pre>{@code
     *     R result = supplier.get();
     *     for (T element : this stream)
     *         accumulator.accept(result, element);
     *     return result;
     * }</pre>
     *
     * <p>Like {@link #reduce(Object, BinaryOperator)}, {@code collect} operations
     * can be parallelized without requiring additional synchronization.
     *
     * <p>This is a terminal
     * operation</a>.
     *
     * @apiNote There are many existing classes in the JDK whose signatures are
     * well-suited for use with method references as arguments to {@code collect()}.
     * For example, the following will accumulate strings into an {@code ArrayList}:
     * <pre>{@code
     *     List<String> asList = stringStream.collect(ArrayList::new, ArrayList::add,
     *                                                ArrayList::addAll);
     * }</pre>
     *
     * <p>The following will take a stream of strings and concatenates them into a
     * single string:
     * <pre>{@code
     *     String concat = stringStream.collect(StringBuilder::new, StringBuilder::append,
     *                                          StringBuilder::append)
     *                                 .toString();
     * }</pre>
     *
     * @param <R> type of the result
     * @param supplier a function that creates a new result container. For a
     *                 parallel execution, this function may be called
     *                 multiple times and must return a fresh value each time.
     * @param accumulator an <a href="package-summary.html#Associativity">associative,
     *                    <a href="package-summary.html#NonInterference">non-interfering,
     *                    <a href="package-summary.html#Statelessness">stateless
     *                    function for incorporating an additional element into a result
     * @param combiner an <a href="package-summary.html#Associativity">associative,
     *                    <a href="package-summary.html#NonInterference">non-interfering,
     *                    <a href="package-summary.html#Statelessness">stateless
     *                    function for combining two values, which must be
     *                    compatible with the accumulator function
     * @return the result of the reduction
     */
    <R> R collect(Supplier supplier,
                  BiConsumer<R, ? super T> accumulator,
                  BiConsumer<R, R> combiner);

    /**
     * Performs a <a href="package-summary.html#MutableReduction">mutable
     * reduction</a> 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 stream is parallel, and the {@code Collector}
     * is {@link Collector.Characteristics#CONCURRENT concurrent}, and
     * either the stream is unordered or the collector is
     * {@link Collector.Characteristics#UNORDERED unordered},
     * then a concurrent reduction will be performed (see {@link Collector} for
     * details on concurrent reduction.)
     *
     * <p>This is a terminal
     * operation</a>.
     *
     * <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 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> 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 collector the {@code Collector} describing the reduction
     * @return the result of the reduction
     * @see #collect(Supplier, BiConsumer, BiConsumer)
     * @see Collectors
     */
    <R, A> R collect(Collector collector);

    /**
     * Returns the minimum element of this stream according to the provided
     * {@code Comparator}.  This is a special case of a
     * <a href="package-summary.html#Reduction">reduction.
     *
     * <p>This is a terminal operation.
     *
     * @param comparator a <a href="package-summary.html#NonInterference">non-interfering,
     *                   <a href="package-summary.html#Statelessness">stateless
     *                   {@code Comparator} to compare elements of this stream
     * @return an {@code Optional} describing the minimum element of this stream,
     * or an empty {@code Optional} if the stream is empty
     * @throws NullPointerException if the minimum element is null
     */
    Optional<T> min(Comparator comparator);

    /**
     * Returns the maximum element of this stream according to the provided
     * {@code Comparator}.  This is a special case of a
     * <a href="package-summary.html#Reduction">reduction.
     *
     * <p>This is a terminal
     * operation</a>.
     *
     * @param comparator a <a href="package-summary.html#NonInterference">non-interfering,
     *                   <a href="package-summary.html#Statelessness">stateless
     *                   {@code Comparator} to compare elements of this stream
     * @return an {@code Optional} describing the maximum element of this stream,
     * or an empty {@code Optional} if the stream is empty
     * @throws NullPointerException if the maximum element is null
     */
    Optional<T> max(Comparator comparator);

    /**
     * Returns the count of elements in this stream.  This is a special case of
     * a <a href="package-summary.html#Reduction">reduction and is
     * equivalent to:
     * <pre>{@code
     *     return mapToLong(e -> 1L).sum();
     * }</pre>
     *
     * <p>This is a terminal operation.
     *
     * @return the count of elements in this stream
     */
    long count();

    /**
     * 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</a>.
     *
     * @apiNote
     * This method evaluates the <em>existential quantification of the
     * predicate over the elements of the stream (for some x P(x)).
     *
     * @param predicate a <a href="package-summary.html#NonInterference">non-interfering,
     *                  <a href="package-summary.html#Statelessness">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(Predicate<? super T> 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.
     *
     * <p>This is a short-circuiting
     * terminal operation</a>.
     *
     * @apiNote
     * This method evaluates the <em>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 <em>vacuously
     * satisfied</em> and is always {@code true} (regardless of P(x)).
     *
     * @param predicate a <a href="package-summary.html#NonInterference">non-interfering,
     *                  <a href="package-summary.html#Statelessness">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(Predicate<? super T> 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.
     *
     * <p>This is a short-circuiting
     * terminal operation</a>.
     *
     * @apiNote
     * This method evaluates the <em>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 <a href="package-summary.html#NonInterference">non-interfering,
     *                  <a href="package-summary.html#Statelessness">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(Predicate<? super T> predicate);

    /**
     * Returns an {@link Optional} describing the first element of this stream,
     * or an empty {@code Optional} if the stream is empty.  If the stream has
     * no encounter order, then any element may be returned.
     *
     * <p>This is a short-circuiting
     * terminal operation</a>.
     *
     * @return an {@code Optional} describing the first element of this stream,
     * or an empty {@code Optional} if the stream is empty
     * @throws NullPointerException if the element selected is null
     */
    Optional<T> findFirst();

    /**
     * Returns an {@link Optional} describing some element of the stream, or an
     * empty {@code Optional} if the stream is empty.
     *
     * <p>This is a short-circuiting
     * terminal operation</a>.
     *
     * <p>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 Optional} describing some element of this stream, or an
     * empty {@code Optional} if the stream is empty
     * @throws NullPointerException if the element selected is null
     * @see #findFirst()
     */
    Optional<T> findAny();

    // Static factories

    /**
     * Returns a builder for a {@code Stream}.
     *
     * @param <T> type of elements
     * @return a stream builder
     */
    public static<T> Builder builder() {
        return new Streams.StreamBuilderImpl<>();
    }

    /**
     * Returns an empty sequential {@code Stream}.
     *
     * @param <T> the type of stream elements
     * @return an empty sequential stream
     */
    public static<T> Stream empty() {
        return StreamSupport.stream(Spliterators.<T>emptySpliterator(), false);
    }

    /**
     * Returns a sequential {@code Stream} containing a single element.
     *
     * @param t the single element
     * @param <T> the type of stream elements
     * @return a singleton sequential stream
     */
    public static<T> Stream of(T t) {
        return StreamSupport.stream(new Streams.StreamBuilderImpl<>(t), false);
    }

    /**
     * Returns a sequential ordered stream whose elements are the specified values.
     *
     * @param <T> the type of stream elements
     * @param values the elements of the new stream
     * @return the new stream
     */
    @SafeVarargs
    @SuppressWarnings("varargs") // Creating a stream from an array is safe
    public static<T> Stream of(T... values) {
        return Arrays.stream(values);
    }

    /**
     * Returns an infinite sequential ordered {@code Stream} produced by iterative
     * application of a function {@code f} to an initial element {@code seed},
     * producing a {@code Stream} consisting of {@code seed}, {@code f(seed)},
     * {@code f(f(seed))}, etc.
     *
     * <p>The first element (position {@code 0}) in the {@code Stream} will be
     * the provided {@code seed}.  For {@code n > 0}, the element at position
     * {@code n}, will be the result of applying the function {@code f} to the
     * element at position {@code n - 1}.
     *
     * @param <T> the type of stream elements
     * @param seed the initial element
     * @param f a function to be applied to to the previous element to produce
     *          a new element
     * @return a new sequential {@code Stream}
     */
    public static<T> Stream iterate(final T seed, final UnaryOperator f) {
        Objects.requireNonNull(f);
        final Iterator<T> iterator = new Iterator() {
            @SuppressWarnings("unchecked")
            T t = (T) Streams.NONE;

            @Override
            public boolean hasNext() {
                return true;
            }

            @Override
            public T next() {
                return t = (t == Streams.NONE) ? seed : f.apply(t);
            }
        };
        return StreamSupport.stream(Spliterators.spliteratorUnknownSize(
                iterator,
                Spliterator.ORDERED | Spliterator.IMMUTABLE), false);
    }

    /**
     * Returns an infinite sequential unordered stream where each element is
     * generated by the provided {@code Supplier}.  This is suitable for
     * generating constant streams, streams of random elements, etc.
     *
     * @param <T> the type of stream elements
     * @param s the {@code Supplier} of generated elements
     * @return a new infinite sequential unordered {@code Stream}
     */
    public static<T> Stream generate(Supplier s) {
        Objects.requireNonNull(s);
        return StreamSupport.stream(
                new StreamSpliterators.InfiniteSupplyingSpliterator.OfRef<>(Long.MAX_VALUE, s), false);
    }

    /**
     * Creates a lazily concatenated stream whose elements are all the
     * elements of the first stream followed by all the elements of the
     * second stream.  The resulting stream is ordered if both
     * of the input streams are ordered, and parallel if either of the input
     * streams is parallel.  When the resulting stream is closed, the close
     * handlers for both input streams are invoked.
     *
     * @implNote
     * Use caution when constructing streams from repeated concatenation.
     * Accessing an element of a deeply concatenated stream can result in deep
     * call chains, or even {@code StackOverflowException}.
     *
     * @param <T> The type of stream elements
     * @param a the first stream
     * @param b the second stream
     * @return the concatenation of the two input streams
     */
    public static <T> Stream concat(Stream a, Stream b) {
        Objects.requireNonNull(a);
        Objects.requireNonNull(b);

        @SuppressWarnings("unchecked")
        Spliterator<T> split = new Streams.ConcatSpliterator.OfRef<>(
                (Spliterator<T>) a.spliterator(), (Spliterator) b.spliterator());
        Stream<T> stream = StreamSupport.stream(split, a.isParallel() || b.isParallel());
        return stream.onClose(Streams.composedClose(a, b));
    }

    /**
     * A mutable builder for a {@code Stream}.  This allows the creation of a
     * {@code Stream} by generating elements individually and adding them to the
     * {@code Builder} (without the copying overhead that comes from using
     * an {@code ArrayList} as a temporary buffer.)
     *
     * <p>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
     * {@code Stream} whose elements are the elements that were added to the stream
     * builder, in the order they were added.
     *
     * @param <T> the type of stream elements
     * @see Stream#builder()
     * @since 1.8
     */
    public interface Builder<T> extends Consumer {

        /**
         * Adds an element to the stream being built.
         *
         * @throws IllegalStateException if the builder has already transitioned to
         * the built state
         */
        @Override
        void accept(T t);

        /**
         * Adds an element to the stream being built.
         *
         * @implSpec
         * The default implementation behaves as if:
         * <pre>{@code
         *     accept(t)
         *     return this;
         * }</pre>
         *
         * @param t the element to add
         * @return {@code this} builder
         * @throws IllegalStateException if the builder has already transitioned to
         * the built state
         */
        default Builder<T> add(T t) {
            accept(t);
            return this;
        }

        /**
         * 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
         */
        Stream<T> build();

    }
}
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