IntStream.java

/*
 * Copyright (c) 2012, 2016, 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
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package java.util.stream;

import java.util.Arrays;
import java.util.IntSummaryStatistics;
import java.util.Objects;
import java.util.OptionalDouble;
import java.util.OptionalInt;
import java.util.PrimitiveIterator;
import java.util.Spliterator;
import java.util.Spliterators;
import java.util.function.BiConsumer;
import java.util.function.Function;
import java.util.function.IntBinaryOperator;
import java.util.function.IntConsumer;
import java.util.function.IntFunction;
import java.util.function.IntPredicate;
import java.util.function.IntSupplier;
import java.util.function.IntToDoubleFunction;
import java.util.function.IntToLongFunction;
import java.util.function.IntUnaryOperator;
import java.util.function.ObjIntConsumer;
import java.util.function.Supplier;

/**
 * A sequence of primitive int-valued elements supporting sequential and parallel
 * aggregate operations.  This is the {@code int} primitive specialization of
 * {@link Stream}.
 *
 * <p>The following example illustrates an aggregate operation using
 * {@link Stream} and {@link IntStream}, computing the sum of the weights of the
 * red widgets:
 *
 * <pre>{@code
 *     int sum = widgets.stream()
 *                      .filter(w -> w.getColor() == RED)
 *                      .mapToInt(w -> w.getWeight())
 *                      .sum();
 * }</pre>
 *
 * See the class documentation for {@link Stream} and the package documentation
 * for <a href="package-summary.html">java.util.stream</a> for additional
 * specification of streams, stream operations, stream pipelines, and
 * parallelism.
 *
 * @see Stream
 * @see <a href="package-summary.html">java.util.stream</a>
 * @since 1.8
 */
// 流接口(int类型版本)
public interface IntStream extends BaseStream<Integer, IntStream> {
    
    /*▼ 创建流的源头阶段 ████████████████████████████████████████████████████████████████████████████████┓ */
    
    /**
     * Returns an empty sequential {@code IntStream}.
     *
     * @return an empty sequential stream
     */
    // 构造处于源头阶段的流，该流不包含任何待处理元素
    static IntStream empty() {
        return StreamSupport.intStream(Spliterators.emptyIntSpliterator(), false);
    }
    
    /**
     * Returns a sequential {@code IntStream} containing a single element.
     *
     * @param t the single element
     *
     * @return a singleton sequential stream
     */
    // 构造处于源头阶段的流，该流仅包含一个元素。当然，该元素可能是多维度的，比如数组或其他容器
    static IntStream of(int t) {
        return StreamSupport.intStream(new Streams.IntStreamBuilderImpl(t), false);
    }
    
    /**
     * Returns a sequential ordered stream whose elements are the specified values.
     *
     * @param values the elements of the new stream
     *
     * @return the new stream
     */
    // 构造处于源头阶段的流，该流包含了指定数组(或类似数组的序列)中的元素
    static IntStream of(int... values) {
        return Arrays.stream(values);
    }
    
    /**
     * Returns an infinite sequential ordered {@code IntStream} 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 IntStream} 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}.
     *
     * <p>The action of applying {@code f} for one element
     * <a href="../concurrent/package-summary.html#MemoryVisibility"><i>happens-before</i></a>
     * the action of applying {@code f} for subsequent elements.  For any given
     * element the action may be performed in whatever thread the library
     * chooses.
     *
     * @param seed the initial element
     * @param f    a function to be applied to the previous element to produce
     *             a new element
     *
     * @return a new sequential {@code IntStream}
     */
    // 构造一个包含无限元素的流，仅支持单元素访问(如果遍历，则停不下来)
    static IntStream iterate(final int seed, final IntUnaryOperator f) {
        Objects.requireNonNull(f);
    
        Spliterator.OfInt spliterator = new Spliterators.AbstractIntSpliterator(Long.MAX_VALUE, Spliterator.ORDERED | Spliterator.IMMUTABLE | Spliterator.NONNULL) {
            int prev;
            boolean started;
            
            @Override
            public boolean tryAdvance(IntConsumer action) {
                Objects.requireNonNull(action);
                int t;
                if(started)
                    t = f.applyAsInt(prev);
                else {
                    t = seed;
                    started = true;
                }
                action.accept(prev = t);
                return true;
            }
        };
    
        return StreamSupport.intStream(spliterator, false);
    }
    
    /**
     * Returns a sequential ordered {@code IntStream} produced by iterative
     * application of the given {@code next} function to an initial element,
     * conditioned on satisfying the given {@code hasNext} predicate.  The
     * stream terminates as soon as the {@code hasNext} predicate returns false.
     *
     * <p>{@code IntStream.iterate} should produce the same sequence of elements as
     * produced by the corresponding for-loop:
     * <pre>{@code
     *     for (int index=seed; hasNext.test(index); index = next.applyAsInt(index)) {
     *         ...
     *     }
     * }</pre>
     *
     * <p>The resulting sequence may be empty if the {@code hasNext} predicate
     * does not hold on the seed value.  Otherwise the first element will be the
     * supplied {@code seed} value, the next element (if present) will be the
     * result of applying the {@code next} function to the {@code seed} value,
     * and so on iteratively until the {@code hasNext} predicate indicates that
     * the stream should terminate.
     *
     * <p>The action of applying the {@code hasNext} predicate to an element
     * <a href="../concurrent/package-summary.html#MemoryVisibility"><i>happens-before</i></a>
     * the action of applying the {@code next} function to that element.  The
     * action of applying the {@code next} function for one element
     * <i>happens-before</i> the action of applying the {@code hasNext}
     * predicate for subsequent elements.  For any given element an action may
     * be performed in whatever thread the library chooses.
     *
     * @param seed    the initial element
     * @param hasNext a predicate to apply to elements to determine when the
     *                stream must terminate.
     * @param next    a function to be applied to the previous element to produce
     *                a new element
     *
     * @return a new sequential {@code IntStream}
     *
     * @since 9
     */
    /*
     * 构造一个包含有限元素的流，既支持单元素访问，也支持批量访问(可以遍历)
     * 如果由next处理生成的新元素被hasNext识别为终止元素，则需要关闭访问
     */
    static IntStream iterate(int seed, IntPredicate hasNext, IntUnaryOperator next) {
        Objects.requireNonNull(next);
        Objects.requireNonNull(hasNext);
    
        Spliterator.OfInt spliterator = new Spliterators.AbstractIntSpliterator(Long.MAX_VALUE, Spliterator.ORDERED | Spliterator.IMMUTABLE | Spliterator.NONNULL) {
            int prev;
            boolean started, finished;
        
            @Override
            public boolean tryAdvance(IntConsumer action) {
                Objects.requireNonNull(action);
                if(finished)
                    return false;
                int t;
                if(started)
                    t = next.applyAsInt(prev);
                else {
                    t = seed;
                    started = true;
                }
                if(!hasNext.test(t)) {
                    finished = true;
                    return false;
                }
                action.accept(prev = t);
                return true;
            }
            
            @Override
            public void forEachRemaining(IntConsumer action) {
                Objects.requireNonNull(action);
                if(finished)
                    return;
                finished = true;
                int t = started ? next.applyAsInt(prev) : seed;
                while(hasNext.test(t)) {
                    action.accept(t);
                    t = next.applyAsInt(t);
                }
            }
        };
        return StreamSupport.intStream(spliterator, false);
    }
    
    /**
     * Returns an infinite sequential unordered stream where each element is
     * generated by the provided {@code IntSupplier}.  This is suitable for
     * generating constant streams, streams of random elements, etc.
     *
     * @param s the {@code IntSupplier} for generated elements
     *
     * @return a new infinite sequential unordered {@code IntStream}
     */
    // 构造一个包含无限元素的流，元素由supplier提供
    static IntStream generate(IntSupplier supplier) {
        Objects.requireNonNull(supplier);
        
        return StreamSupport.intStream(new StreamSpliterators.InfiniteSupplyingSpliterator.OfInt(Long.MAX_VALUE, supplier), 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.
     *
     * <p>This method operates on the two input streams and binds each stream
     * to its source.  As a result subsequent modifications to an input stream
     * source may not be reflected in the concatenated stream result.
     *
     * @param a the first stream
     * @param b the second stream
     *
     * @return the concatenation of the two input streams
     *
     * @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 StackOverflowError}.
     * @apiNote To preserve optimization opportunities this method binds each stream to
     * its source and accepts only two streams as parameters.  For example, the
     * exact size of the concatenated stream source can be computed if the exact
     * size of each input stream source is known.
     * To concatenate more streams without binding, or without nested calls to
     * this method, try creating a stream of streams and flat-mapping with the
     * identity function, for example:
     * <pre>{@code
     *     IntStream concat = Stream.of(s1, s2, s3, s4).flatMapToInt(s -> s);
     * }</pre>
     */
    // 构造一个由s1和s2拼接而成的流
    static IntStream concat(IntStream s1, IntStream s2) {
        Objects.requireNonNull(s1);
        Objects.requireNonNull(s2);
        
        Spliterator.OfInt split = new Streams.ConcatSpliterator.OfInt(s1.spliterator(), s2.spliterator());
        IntStream stream = StreamSupport.intStream(split, s1.isParallel() || s2.isParallel());
        return stream.onClose(Streams.composedClose(s1, s2));
    }
    
    /**
     * Returns a sequential ordered {@code IntStream} from {@code startInclusive}
     * (inclusive) to {@code endExclusive} (exclusive) by an incremental step of
     * {@code 1}.
     *
     * @param startInclusive the (inclusive) initial value
     * @param endExclusive   the exclusive upper bound
     *
     * @return a sequential {@code IntStream} for the range of {@code int}
     * elements
     *
     * @apiNote <p>An equivalent sequence of increasing values can be produced
     * sequentially using a {@code for} loop as follows:
     * <pre>{@code
     *     for (int i = startInclusive; i < endExclusive ; i++) { ... }
     * }</pre>
     */
    // 构造一个包含有限元素的流，其区间为[startInclusive, endExclusive)（右区间开放）
    static IntStream range(int startInclusive, int endExclusive) {
        if(startInclusive >= endExclusive) {
            return empty();
        }
    
        return StreamSupport.intStream(new Streams.RangeIntSpliterator(startInclusive, endExclusive, false), false);
    }
    
    /**
     * Returns a sequential ordered {@code IntStream} from {@code startInclusive}
     * (inclusive) to {@code endInclusive} (inclusive) by an incremental step of
     * {@code 1}.
     *
     * @param startInclusive the (inclusive) initial value
     * @param endInclusive   the inclusive upper bound
     *
     * @return a sequential {@code IntStream} for the range of {@code int}
     * elements
     *
     * @apiNote <p>An equivalent sequence of increasing values can be produced
     * sequentially using a {@code for} loop as follows:
     * <pre>{@code
     *     for (int i = startInclusive; i <= endInclusive ; i++) { ... }
     * }</pre>
     */
    // 构造一个包含有限元素的流，其区间为[startInclusive, endExclusive]（右区间封闭）
    static IntStream rangeClosed(int startInclusive, int endInclusive) {
        if(startInclusive>endInclusive) {
            return empty();
        }
    
        return StreamSupport.intStream(new Streams.RangeIntSpliterator(startInclusive, endInclusive, true), false);
    }
    
    /*▲ 创建流的源头阶段 ████████████████████████████████████████████████████████████████████████████████┛ */
    
    
    
    /*▼ 流迭代器 ████████████████████████████████████████████████████████████████████████████████┓ */
    
    // 返回当前阶段的流的流迭代器；如果遇到并行流的有状态的中间阶段，则需要特殊处理
    @Override
    Spliterator.OfInt spliterator();
    
    // 将当前阶段的流的Spliterator适配为Iterator
    @Override
    PrimitiveIterator.OfInt iterator();
    
    /*▲ 流迭代器 ████████████████████████████████████████████████████████████████████████████████┛ */
    
    
    
    /*▼ 中间操作-无状态 ████████████████████████████████████████████████████████████████████████████████┓ */
    
    /**
     * Returns a stream consisting of the elements of this stream that match
     * the given predicate.
     *
     * <p>This is an <a href="package-summary.html#StreamOps">intermediate
     * operation</a>.
     *
     * @param predicate a <a href="package-summary.html#NonInterference">non-interfering</a>,
     *                  <a href="package-summary.html#Statelessness">stateless</a>
     *                  predicate to apply to each element to determine if it
     *                  should be included
     *
     * @return the new stream
     */
    // 筛选数据
    IntStream filter(IntPredicate predicate);
    
    /**
     * Returns a stream consisting of the results of applying the given
     * function to the elements of this stream.
     *
     * <p>This is an <a href="package-summary.html#StreamOps">intermediate
     * operation</a>.
     *
     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering</a>,
     *               <a href="package-summary.html#Statelessness">stateless</a>
     *               function to apply to each element
     *
     * @return the new stream
     */
    // 映射数据
    IntStream map(IntUnaryOperator mapper);
    
    /**
     * Returns a {@code LongStream} consisting of the results of applying the
     * given function to the elements of this stream.
     *
     * <p>This is an <a href="package-summary.html#StreamOps">intermediate
     * operation</a>.
     *
     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering</a>,
     *               <a href="package-summary.html#Statelessness">stateless</a>
     *               function to apply to each element
     *
     * @return the new stream
     */
    // 映射数据
    LongStream mapToLong(IntToLongFunction mapper);
    
    /**
     * Returns a {@code DoubleStream} consisting of the results of applying the
     * given function to the elements of this stream.
     *
     * <p>This is an <a href="package-summary.html#StreamOps">intermediate
     * operation</a>.
     *
     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering</a>,
     *               <a href="package-summary.html#Statelessness">stateless</a>
     *               function to apply to each element
     *
     * @return the new stream
     */
    // 映射数据
    DoubleStream mapToDouble(IntToDoubleFunction mapper);
    
    /**
     * Returns an object-valued {@code Stream} consisting of the results of
     * applying the given function to the elements of this stream.
     *
     * <p>This is an <a href="package-summary.html#StreamOps">
     * intermediate operation</a>.
     *
     * @param <U>    the element type of the new stream
     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering</a>,
     *               <a href="package-summary.html#Statelessness">stateless</a>
     *               function to apply to each element
     *
     * @return the new stream
     */
    // 映射数据
    <U> Stream<U> mapToObj(IntFunction<? extends U> 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 <a href="package-summary.html#StreamOps">intermediate
     * operation</a>.
     *
     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering</a>,
     *               <a href="package-summary.html#Statelessness">stateless</a>
     *               function to apply to each element which produces an
     *               {@code IntStream} of new values
     *
     * @return the new stream
     *
     * @see Stream#flatMap(Function)
     */
    // 数据降维
    IntStream flatMap(IntFunction<? extends IntStream> mapper);
    
    /**
     * 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 <a href="package-summary.html#StreamOps">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.
     *
     * @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
     *
     * @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
     *     IntStream.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();
     * }</pre>
     *
     * <p>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.
     */
    // 用于查看流的内部结构，不会对流的结构产生影响
    IntStream peek(IntConsumer action);
    
    /**
     * Returns a {@code Stream} consisting of the elements of this stream,
     * each boxed to an {@code Integer}.
     *
     * <p>This is an <a href="package-summary.html#StreamOps">intermediate
     * operation</a>.
     *
     * @return a {@code Stream} consistent of the elements of this stream,
     * each boxed to an {@code Integer}
     */
    // 装箱
    Stream<Integer> boxed();
    
    /**
     * Returns a {@code LongStream} consisting of the elements of this stream,
     * converted to {@code long}.
     *
     * <p>This is an <a href="package-summary.html#StreamOps">intermediate
     * operation</a>.
     *
     * @return a {@code LongStream} consisting of the elements of this stream,
     * converted to {@code long}
     */
    // 转换为LongStream
    LongStream asLongStream();
    
    /**
     * Returns a {@code DoubleStream} consisting of the elements of this stream,
     * converted to {@code double}.
     *
     * <p>This is an <a href="package-summary.html#StreamOps">intermediate
     * operation</a>.
     *
     * @return a {@code DoubleStream} consisting of the elements of this stream,
     * converted to {@code double}
     */
    // 转换为DoubleStream
    DoubleStream asDoubleStream();
    
    // 中间操作，返回顺序的等效流
    @Override
    IntStream sequential();
    
    // 中间操作，返回并行的等效流
    @Override
    IntStream parallel();
    
    /*▲ 中间操作-无状态 ████████████████████████████████████████████████████████████████████████████████┛ */
    
    
    
    /*▼ 中间操作-有状态 ████████████████████████████████████████████████████████████████████████████████┓ */
    
    /**
     * Returns a stream consisting of the distinct elements of this stream.
     *
     * <p>This is a <a href="package-summary.html#StreamOps">stateful
     * intermediate operation</a>.
     *
     * @return the new stream
     */
    // 去重
    IntStream distinct();
    
    /**
     * Returns a stream consisting of the elements of this stream in sorted
     * order.
     *
     * <p>This is a <a href="package-summary.html#StreamOps">stateful
     * intermediate operation</a>.
     *
     * @return the new stream
     */
    // 排序（默认升序）
    IntStream sorted();
    
    /**
     * Returns a stream consisting of the elements of this stream, truncated
     * to be no longer than {@code maxSize} in length.
     *
     * <p>This is a <a href="package-summary.html#StreamOps">short-circuiting
     * stateful intermediate operation</a>.
     *
     * @param maxSize the number of elements the stream should be limited to
     *
     * @return the new stream
     *
     * @throws IllegalArgumentException if {@code maxSize} is negative
     * @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</em> elements, but the
     * <em>first n</em> elements in the encounter order.  Using an unordered
     * stream source (such as {@link #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.
     */
    // 只显示前maxSize个元素
    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.
     *
     * <p>This is a <a href="package-summary.html#StreamOps">stateful
     * intermediate operation</a>.
     *
     * @param n the number of leading elements to skip
     *
     * @return the new stream
     *
     * @throws IllegalArgumentException if {@code n} is negative
     * @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</em> elements, but the
     * <em>first n</em> elements in the encounter order.  Using an unordered
     * stream source (such as {@link #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.
     */
    // 跳过前n个元素
    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.
     *
     * <p>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.
     *
     * <p>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).
     *
     * <p>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).
     *
     * <p>This is a <a href="package-summary.html#StreamOps">short-circuiting
     * stateful intermediate operation</a>.
     *
     * @param predicate a <a href="package-summary.html#NonInterference">non-interfering</a>,
     *                  <a href="package-summary.html#Statelessness">stateless</a>
     *                  predicate to apply to elements to determine the longest
     *                  prefix of elements.
     *
     * @return the new stream
     *
     * @implSpec 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.
     * @apiNote 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 #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.
     * @since 9
     */
    // "保存前缀"：保存起初遇到的满足predicate条件的元素；只要遇到首个不满足条件的元素，就结束后续的保存动作
    default IntStream takeWhile(IntPredicate predicate) {
        Objects.requireNonNull(predicate);
        // Reuses the unordered spliterator, which, when encounter is present,
        // is safe to use as long as it configured not to split
        return StreamSupport.intStream(new WhileOps.UnorderedWhileSpliterator.OfInt.Taking(spliterator(), true, predicate), isParallel()).onClose(this::close);
    }
    
    /**
     * 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.
     *
     * <p>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.
     *
     * <p>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).
     *
     * <p>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).
     *
     * <p>This is a <a href="package-summary.html#StreamOps">stateful
     * intermediate operation</a>.
     *
     * @param predicate a <a href="package-summary.html#NonInterference">non-interfering</a>,
     *                  <a href="package-summary.html#Statelessness">stateless</a>
     *                  predicate to apply to elements to determine the longest
     *                  prefix of elements.
     *
     * @return the new stream
     *
     * @implSpec 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.
     * @apiNote 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 #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.
     * @since 9
     */
    // "丢弃前缀"：丢弃起初遇到的满足predicate条件的元素；只要遇到首个不满足条件的元素，就开始保存它后及其后面的元素
    default IntStream dropWhile(IntPredicate predicate) {
        Objects.requireNonNull(predicate);
        // Reuses the unordered spliterator, which, when encounter is present,
        // is safe to use as long as it configured not to split
        return StreamSupport.intStream(new WhileOps.UnorderedWhileSpliterator.OfInt.Dropping(spliterator(), true, predicate), isParallel()).onClose(this::close);
    }
    
    /*▲ 中间操作-有状态 ████████████████████████████████████████████████████████████████████████████████┛ */
    
    
    
    /*▼ 终端操作-非短路操作 ████████████████████████████████████████████████████████████████████████████████┓ */
    
    /**
     * Returns an array containing the elements of this stream.
     *
     * <p>This is a <a href="package-summary.html#StreamOps">terminal
     * operation</a>.
     *
     * @return an array containing the elements of this stream
     */
    // 将数据存入int数组返回
    int[] toArray();
    
    /**
     * Performs an action for each element of this stream.
     *
     * <p>This is a <a href="package-summary.html#StreamOps">terminal
     * operation</a>.
     *
     * <p>For parallel stream pipelines, this operation does <em>not</em>
     * 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
     */
    // 遍历，并执行action操作
    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.
     *
     * <p>This is a <a href="package-summary.html#StreamOps">terminal
     * operation</a>.
     *
     * @param action a <a href="package-summary.html#NonInterference">
     *               non-interfering</a> action to perform on the elements
     *
     * @see #forEach(IntConsumer)
     */
    // 按遭遇顺序遍历，并执行action操作
    void forEachOrdered(IntConsumer action);
    
    /**
     * 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 <a href="package-summary.html#Reduction">reduction</a>
     * and is equivalent to:
     * <pre>{@code
     *     return reduce(Integer::min);
     * }</pre>
     *
     * <p>This is a <a href="package-summary.html#StreamOps">terminal operation</a>.
     *
     * @return an {@code OptionalInt} containing the minimum element of this
     * stream, or an empty {@code OptionalInt} if the stream is empty
     */
    // 求最小值
    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 <a href="package-summary.html#Reduction">reduction</a>
     * and is equivalent to:
     * <pre>{@code
     *     return reduce(Integer::max);
     * }</pre>
     *
     * <p>This is a <a href="package-summary.html#StreamOps">terminal
     * operation</a>.
     *
     * @return an {@code OptionalInt} containing the maximum element of this
     * stream, or an empty {@code OptionalInt} if the stream is empty
     */
    // 求最大值
    OptionalInt max();
    
    /**
     * Performs a <a href="package-summary.html#Reduction">reduction</a> on the
     * elements of this stream, using an
     * <a href="package-summary.html#Associativity">associative</a> accumulation
     * function, and returns an {@code OptionalInt} describing the reduced value,
     * if any. This is equivalent to:
     * <pre>{@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();
     * }</pre>
     *
     * but is not constrained to execute sequentially.
     *
     * <p>The {@code accumulator} function must be an
     * <a href="package-summary.html#Associativity">associative</a> function.
     *
     * <p>This is a <a href="package-summary.html#StreamOps">terminal
     * operation</a>.
     *
     * @param op an <a href="package-summary.html#Associativity">associative</a>,
     *           <a href="package-summary.html#NonInterference">non-interfering</a>,
     *           <a href="package-summary.html#Statelessness">stateless</a>
     *           function for combining two values
     *
     * @return the result of the reduction
     *
     * @see #reduce(int, IntBinaryOperator)
     */
    // 无初始状态的汇总操作(int类型版本)
    OptionalInt reduce(IntBinaryOperator op);
    
    /**
     * Performs a <a href="package-summary.html#Reduction">reduction</a> on the
     * elements of this stream, using the provided identity value and an
     * <a href="package-summary.html#Associativity">associative</a>
     * accumulation function, and returns the reduced value.  This is equivalent
     * to:
     * <pre>{@code
     *     int result = identity;
     *     for (int element : this stream)
     *         result = accumulator.applyAsInt(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 x},
     * {@code accumulator.apply(identity, x)} is equal to {@code x}.
     * The {@code accumulator} function must be an
     * <a href="package-summary.html#Associativity">associative</a> function.
     *
     * <p>This is a <a href="package-summary.html#StreamOps">terminal
     * operation</a>.
     *
     * @param identity the identity value for the accumulating function
     * @param op       an <a href="package-summary.html#Associativity">associative</a>,
     *                 <a href="package-summary.html#NonInterference">non-interfering</a>,
     *                 <a href="package-summary.html#Statelessness">stateless</a>
     *                 function for combining two values
     *
     * @return the result of the reduction
     *
     * @apiNote Sum, min, max, and average are all special cases of reduction.
     * Summing a stream of numbers can be expressed as:
     *
     * <pre>{@code
     *     int sum = integers.reduce(0, (a, b) -> a+b);
     * }</pre>
     *
     * or more compactly:
     *
     * <pre>{@code
     *     int 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.
     * @see #sum()
     * @see #min()
     * @see #max()
     * @see #average()
     */
    // 有初始状态的汇总操作(int类型版本)
    int reduce(int identity, IntBinaryOperator op);
    
    /**
     * 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 (int element : this stream)
     *         accumulator.accept(result, element);
     *     return result;
     * }</pre>
     *
     * <p>Like {@link #reduce(int, IntBinaryOperator)}, {@code collect} operations
     * can be parallelized without requiring additional synchronization.
     *
     * <p>This is a <a href="package-summary.html#StreamOps">terminal
     * operation</a>.
     *
     * @param <R>         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 <a href="package-summary.html#Associativity">associative</a>,
     *                    <a href="package-summary.html#NonInterference">non-interfering</a>,
     *                    <a href="package-summary.html#Statelessness">stateless</a>
     *                    function that must fold an element into a result
     *                    container.
     * @param combiner    an <a href="package-summary.html#Associativity">associative</a>,
     *                    <a href="package-summary.html#NonInterference">non-interfering</a>,
     *                    <a href="package-summary.html#Statelessness">stateless</a>
     *                    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)
     */
    // 有初始状态的消费操作(int类型版本)
    <R> R collect(Supplier<R> supplier, ObjIntConsumer<R> accumulator, BiConsumer<R, R> combiner);
    
    /**
     * Returns the count of elements in this stream.  This is a special case of
     * a <a href="package-summary.html#Reduction">reduction</a> and is
     * equivalent to:
     * <pre>{@code
     *     return mapToLong(e -> 1L).sum();
     * }</pre>
     *
     * <p>This is a <a href="package-summary.html#StreamOps">terminal operation</a>.
     *
     * @return the count of elements in this stream
     *
     * @apiNote 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:
     * <pre>{@code
     *     IntStream s = IntStream.of(1, 2, 3, 4);
     *     long count = s.peek(System.out::println).count();
     * }</pre>
     * 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.
     */
    // 计数
    long count();
    
    /**
     * Returns the sum of elements in this stream.  This is a special case
     * of a <a href="package-summary.html#Reduction">reduction</a>
     * and is equivalent to:
     * <pre>{@code
     *     return reduce(0, Integer::sum);
     * }</pre>
     *
     * <p>This is a <a href="package-summary.html#StreamOps">terminal
     * operation</a>.
     *
     * @return the sum of elements in this stream
     */
    // 求和
    int sum();
    
    /**
     * 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
     * <a href="package-summary.html#Reduction">reduction</a>.
     *
     * <p>This is a <a href="package-summary.html#StreamOps">terminal
     * operation</a>.
     *
     * @return an {@code OptionalDouble} containing the average element of this
     * stream, or an empty optional if the stream is empty
     */
    // 求平均值
    OptionalDouble average();
    
    /**
     * Returns an {@code IntSummaryStatistics} describing various
     * summary data about the elements of this stream.  This is a special
     * case of a <a href="package-summary.html#Reduction">reduction</a>.
     *
     * <p>This is a <a href="package-summary.html#StreamOps">terminal
     * operation</a>.
     *
     * @return an {@code IntSummaryStatistics} describing various summary data
     * about the elements of this stream
     */
    // 信息统计
    IntSummaryStatistics summaryStatistics();
    
    /*▲ 终端操作-非短路操作 ████████████████████████████████████████████████████████████████████████████████┛ */
    
    
    
    /*▼ 终端操作-短路操作 ████████████████████████████████████████████████████████████████████████████████┓ */
    
    /**
     * 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.
     *
     * <p>This is a <a href="package-summary.html#StreamOps">short-circuiting
     * terminal operation</a>.
     *
     * @return an {@code OptionalInt} describing the first element of this stream,
     * or an empty {@code OptionalInt} if the stream is empty
     */
    // 找出第一个元素
    OptionalInt findFirst();
    
    /**
     * Returns an {@link OptionalInt} describing some element of the stream, or
     * an empty {@code OptionalInt} if the stream is empty.
     *
     * <p>This is a <a href="package-summary.html#StreamOps">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 OptionalInt} describing some element of this stream, or
     * an empty {@code OptionalInt} if the stream is empty
     *
     * @see #findFirst()
     */
    // 找到一个元素就返回，不管是不是第一个元素
    OptionalInt findAny();
    
    /**
     * 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 <a href="package-summary.html#StreamOps">short-circuiting
     * terminal operation</a>.
     *
     * @param predicate a <a href="package-summary.html#NonInterference">non-interfering</a>,
     *                  <a href="package-summary.html#Statelessness">stateless</a>
     *                  predicate to apply to elements of this stream
     *
     * @return {@code true} if any elements of the stream match the provided
     * predicate, otherwise {@code false}
     *
     * @apiNote This method evaluates the <em>existential quantification</em> of the
     * predicate over the elements of the stream (for some x P(x)).
     */
    // 判断是否存在元素满足predicate条件
    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.
     *
     * <p>This is a <a href="package-summary.html#StreamOps">short-circuiting
     * terminal operation</a>.
     *
     * @param predicate a <a href="package-summary.html#NonInterference">non-interfering</a>,
     *                  <a href="package-summary.html#Statelessness">stateless</a>
     *                  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}
     *
     * @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)).
     */
    // 判断是否所有元素满足predicate条件
    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.
     *
     * <p>This is a <a href="package-summary.html#StreamOps">short-circuiting
     * terminal operation</a>.
     *
     * @param predicate a <a href="package-summary.html#NonInterference">non-interfering</a>,
     *                  <a href="package-summary.html#Statelessness">stateless</a>
     *                  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}
     *
     * @apiNote This method evaluates the <em>universal quantification</em> 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).
     */
    // 判断是否没有元素满足predicate条件
    boolean noneMatch(IntPredicate predicate);
    
    /*▲ 终端操作-短路操作 ████████████████████████████████████████████████████████████████████████████████┛ */
    
    
    /**
     * Returns a builder for an {@code IntStream}.
     *
     * @return a stream builder
     */
    // 返回一个Stream构建器
    static Builder builder() {
        return new Streams.IntStreamBuilderImpl();
    }
    
    /**
     * A mutable builder for an {@code IntStream}.
     *
     * <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 stream whose elements are the elements that were added to the
     * stream builder, in the order they were added.
     *
     * @see IntStream#builder()
     * @since 1.8
     */
    // Stream构建器接口，允许创建单元素流或多元素流。
    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);
        
        /**
         * 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();
        
        /**
         * Adds an element to the stream being built.
         *
         * @param t the element to add
         *
         * @return {@code this} builder
         *
         * @throws IllegalStateException if the builder has already transitioned
         *                               to the built state
         * @implSpec The default implementation behaves as if:
         * <pre>{@code
         *     accept(t)
         *     return this;
         * }</pre>
         */
        default Builder add(int t) {
            accept(t);
            return this;
        }
    
    }
    
}