Stream流式编程详解示例（让编程变得优雅和简洁）

//?若不确定要添加多少个元素到Stream中，可用Stream.builder()来创建Stream.builder()对象。用add方法来添加元素，然后用build方法来生成Stream对象。

????????Stream.Builder<Integer> builder = Stream.builder();

????????builder.add(1);

????????builder.add(2);

????????builder.add(3);

????????Stream<Integer> build = builder.build();

1.5 I/O类Files的list、find、lines和walk方法创建Stream对象

????????Stream<Path> stream = Files.list(Paths.get("dirName"));

????????Stream<Path> matches = Files.find(inputDirs, Integer.MAX_VALUE, (path, attr) -> inputFile.equals(path), FileVisitOption.FOLLOW_LINKS);

????????Stream<String> lines = Files.lines(Paths.get("dirName"));

????????Stream<Path> paths = Files.walk(Paths.get("dirName"), 2)

1.6?通过生成器创建Stream对象

? ? ? ? //?无限流，元素都为0

????????Stream<Integer> generate = Stream.generate(() -> 1);

? ? ? ? //?无限流，从0?开始递增1

????????Stream<Integer> iterate = Stream.iterate(0, n -> n + 1);

二、操作方法

2.1?映射：map()

????????Stream<String> stream = Stream.of("1","2","3","4","5","6","7","8","9","10");

????????Stream<Integer> stream1 = stream.map(m -> Integer.valueOf(m));

2.2?排序：sorted()

????????Stream<Integer> stream = Stream.of(1,2,3,4,5,6);

? ? ? ? //?降序

????????Stream<Integer> sorted = stream.sorted((a, b) -> b - a); // 6, 5, 4, 3, 2, 1?

2.3?去重：distinct()

????????Stream<Integer> stream = Stream.of(1,1,4,4,4,4);

????????stream = stream.distinct(); // 1, 4

2.4?汇总：collect()

????????Stream<Integer> stream = Stream.of(1,1,4,4,4,4);

????????List<Integer> list = stream.collect(Collectors.toList());

2.5?过滤：filter()

????????Stream<Integer> stream = Stream.of(1,2,3,4,5,6);

????????stream = stream.filter(m -> m > 3); // 4, 5, 6

2.6?跳过：skip()

????????Stream<Integer> stream = Stream.of(1,2,3,4,5,6);

????????stream = stream.skip(4); //?截断前 4个元素，只剩 5, 6

2.7?截断：limit()

????????Stream<Integer> stream = Stream.of(1,2,3,4,5,6);

????????stream = stream.limit(4); //?只留前 4个元素，只剩 1, 2, 3, 4

2.8?扁平映射：flatMap()

????????List<List<Integer>> list = Arrays.asList(Arrays.asList(1, 2, 3), Arrays.asList(4, 5, 6)); //?二维数据

????????Stream<Integer> stream = list.stream().flatMap(List::stream); //?二维映射成一维流 1, 2, 3, 4, 5, 6

2.9?归约：reduce()

?????????// reduce()方法是对Stream流中所有元素求和

????????Stream<Integer> stream = Stream.of(1, 2, 3, 4, 5, 6);

????????Optional<Integer> reduce = stream.reduce((a, b) -> a + b); ????????

????????reduce.stream().forEach(m-> System.out.println(m)); // 21

2.10?统计：summaryStatistics()

????????IntStream intStream = IntStream.of(1, 2, 3, 4, 5, 6);

????????IntStream intStream2 = IntStream.of(5, 6, 7, 8);

????????IntSummaryStatistics stats = intStream.summaryStatistics();

????????IntSummaryStatistics stats2 = intStream2.summaryStatistics();

? ? ? ?

????????stats.getMax(); //?求最大值 6

????????stats.getMin(); //?求最小值 1

????????stats.getSum(); //?求和 21

????????stats.getCount(); //?求数量 6

????????stats.combine(stats2); //?两个stats?和 stat2?合并求以上四个参数到stats中分别得 8， 1， 47， 10

????????stats.getAverage(); //?求平均值 4.7

2.11?遍历流元素：forEach()

????????IntStream intStream = IntStream.of(1, 2, 3, 4, 5, 6);

????????intStream.forEach(m-> System.out.println(m)); //?遍历打印出 1, 2, 3, 4, 5, 6

2.12?被建议在debug中使用的：peek()

????????Stream<Integer> stream = Arrays.asList(4, 7, 9, 11, 12).stream();

????????stream.peek(n -> System.out.println(n)); //?发现，没有任何输出，说明打印逻辑未执行。（注意可能隐藏逻辑BUG）

????????

? ? ? ? 官方原文说明：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 findFirst, or in the example described in count), the action will not be invoked for those elements.（在流实现能够优化部分或所有元素的生成的情况下(例如使用像findFirst这样的短路操作，或者在count中描述的示例中)，将不会为这些元素调用操作。）

????????

2.13 匹配所有：allMatch()

????????Stream<Integer> stream = Arrays.asList(4, 7, 9, 11, 12).stream();

????????boolean b = stream.allMatch(m -> m % 2 == 1); // false。必须全部都为奇数，才为 true

2.14?匹配任务一个：anyMatch()

????????Stream<Integer> stream = Arrays.asList(4, 7, 9, 11, 12).stream();

????????System.out.println(stream.anyMatch(m -> m % 2 == 1)); // true。只要有一个为奇数，则为true

2.15?都不满足：noneMatch()

????????Stream<Integer> stream = Stream.of(1, 2, 3, 4, 5); ????????System.out.println(stream.noneMatch(m -> m > 8)); // true

????????Stream<Integer> stream1 = ????????Stream.of(1, 2, 3, 4, 5); ????????System.out.println(stream1.noneMatch(m -> m > 3)); // false

2.15?取第一个元素：findFirst()

????????Stream<Integer> stream = Stream.of(1, 2, 3, 4, 5); ????????System.out.println(stream.findFirst().get()); // 1

2.16?随机返回一个：findAny()

????????Stream<Integer> stream = Stream.of(1, 2, 3, 4, 5); ????????System.out.println(stream.findAny().get()); //?返回1，数量比较大的时候不一定是1了，取决于并行处理的结果

2.17?求最大值：max()

????????Stream<Integer> stream = Stream.of(1, 2, 3, 4, 5); ????????System.out.println(stream.max(Integer:: compareTo).get()); // 5

2.18?求最小值：min()

????????Stream<Integer> stream = Stream.of(1, 2, 3, 4, 5); ????????System.out.println(stream.min(Integer:: compareTo).get()); // 1

2.19?求元素个数：count()

????????Stream<Integer> stream = Stream.of(1, 2, 3, 4, 5);

????????System.out.println(stream.count()); // 5

2.20?并行流：parallel()

????????Stream<Integer> stream = Stream.of(1, 2, 3, 4, 5);

????????stream.parallel().forEach(m-> System.out.println(m)); // 3, 5, 4, 1, 2?每次执行输出都不一样

2.21?并行求和：parallel()和 reduce()结合使用

????????Stream<Integer> stream = Stream.of(1, 2, 3 , 4 , 5 ,6, 7, 8, 9, 10); ????????System.out.println(stream.parallel().reduce(0, Integer::sum)); // 55

2.22?转换类型流：mapToInt()、mapToDouble()、MapToLong()

????????Stream<Integer> stream = Stream.of(1, 2, 3 , 4 , 5 ,6, 7, 8, 9, 10);

????????IntStream intStream = stream.mapToInt(Integer::intValue);

? ? ? ? //?转为IntStream流，便于操作int()，如求最大值 max()，最小值 min()，求和 sum()?和转为数组 toArray()?等。

? ? ? ? mapToDouble、mapToLong?与 mapToInt?使用相似。

文章来源:https://blog.csdn.net/imwucx/article/details/134939130
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