• 感受 lambda 之美!


    1.1 java8自带的常用函数式接口。

    public class Test {
        public static void main(String[] args) {
            Predicate<Integer> predicate = x -> x > 185;
            Student student = new Student("9龙", 23, 175);
            System.out.println(
                "9龙的身高高于185吗?:" + predicate.test(student.getStature()));
    
            Consumer<String> consumer = System.out::println;
            consumer.accept("命运由我不由天");
    
            Function<Student, String> function = Student::getName;
            String name = function.apply(student);
            System.out.println(name);
    
            Supplier<Integer> supplier = 
                () -> Integer.valueOf(BigDecimal.TEN.toString());
            System.out.println(supplier.get());
    
            UnaryOperator<Boolean> unaryOperator = uglily -> !uglily;
            Boolean apply2 = unaryOperator.apply(true);
            System.out.println(apply2);
    
            BinaryOperator<Integer> operator = (x, y) -> x * y;
            Integer integer = operator.apply(2, 3);
            System.out.println(integer);
    
            test(() -> "我是一个演示的函数式接口");
        }
    
        /**
         * 演示自定义函数式接口使用
         *
         * @param worker
         */
        public static void test(Worker worker) {
            String work = worker.work();
            System.out.println(work);
        }
    
        public interface Worker {
            String work();
        }
    }
    //9龙的身高高于185吗?:false
    //命运由我不由天
    //9龙
    //10
    //false
    //6
    //我是一个演示的函数式接口

    2、常用的流

    2.1 collect(Collectors.toList())

    将流转换为list。还有toSet(),toMap()等。及早求值。

    public class TestCase {
        public static void main(String[] args) {
            List<Student> studentList = Stream.of(new Student("路飞", 22, 175),
                    new Student("红发", 40, 180),
                    new Student("白胡子", 50, 185)).collect(Collectors.toList());
            System.out.println(studentList);
        }
    }
    //输出结果
    //[Student{name='路飞', age=22, stature=175, specialities=null}, 
    //Student{name='红发', age=40, stature=180, specialities=null}, 
    //Student{name='白胡子', age=50, stature=185, specialities=null}]

    2.2 filter

    public class TestCase {
        public static void main(String[] args) {
            List<Student> students = new ArrayList<>(3);
            students.add(new Student("路飞", 22, 175));
            students.add(new Student("红发", 40, 180));
            students.add(new Student("白胡子", 50, 185));
    
            List<Student> list = students.stream()
                .filter(stu -> stu.getStature() < 180)
                .collect(Collectors.toList());
            System.out.println(list);
        }
    }
    //输出结果
    //[Student{name='路飞', age=22, stature=175, specialities=null}]

    2.3 map

    public class TestCase {
        public static void main(String[] args) {
            List<Student> students = new ArrayList<>(3);
            students.add(new Student("路飞", 22, 175));
            students.add(new Student("红发", 40, 180));
            students.add(new Student("白胡子", 50, 185));
    
            List<String> names = students.stream().map(student -> student.getName())
                    .collect(Collectors.toList());
            System.out.println(names);
        }
    }
    //输出结果
    //[路飞, 红发, 白胡子]

    2.4 flatMap

    public class TestCase {
        public static void main(String[] args) {
            List<Student> students = new ArrayList<>(3);
            students.add(new Student("路飞", 22, 175));
            students.add(new Student("红发", 40, 180));
            students.add(new Student("白胡子", 50, 185));
    
            List<Student> studentList = Stream.of(students,
                    asList(new Student("艾斯", 25, 183),
                            new Student("雷利", 48, 176)))
                    .flatMap(students1 -> students1.stream()).collect(Collectors.toList());
            System.out.println(studentList);
        }
    }
    //输出结果
    //[Student{name='路飞', age=22, stature=175, specialities=null}, 
    //Student{name='红发', age=40, stature=180, specialities=null}, 
    //Student{name='白胡子', age=50, stature=185, specialities=null}, 
    //Student{name='艾斯', age=25, stature=183, specialities=null},
    //Student{name='雷利', age=48, stature=176, specialities=null}]

    2.5 max和min

    我们经常会在集合中求最大或最小值,使用流就很方便。及早求值。

    public class TestCase {
        public static void main(String[] args) {
            List<Student> students = new ArrayList<>(3);
            students.add(new Student("路飞", 22, 175));
            students.add(new Student("红发", 40, 180));
            students.add(new Student("白胡子", 50, 185));
    
            Optional<Student> max = students.stream()
                .max(Comparator.comparing(stu -> stu.getAge()));
            Optional<Student> min = students.stream()
                .min(Comparator.comparing(stu -> stu.getAge()));
            //判断是否有值
            if (max.isPresent()) {
                System.out.println(max.get());
            }
            if (min.isPresent()) {
                System.out.println(min.get());
            }
        }
    }
    //输出结果
    //Student{name='白胡子', age=50, stature=185, specialities=null}
    //Student{name='路飞', age=22, stature=175, specialities=null}

    2.6 count

    统计功能,一般都是结合filter使用,因为先筛选出我们需要的再统计即可。及早求值

    public class TestCase {
        public static void main(String[] args) {
            List<Student> students = new ArrayList<>(3);
            students.add(new Student("路飞", 22, 175));
            students.add(new Student("红发", 40, 180));
            students.add(new Student("白胡子", 50, 185));
    
            long count = students.stream().filter(s1 -> s1.getAge() < 45).count();
            System.out.println("年龄小于45岁的人数是:" + count);
        }
    }
    //输出结果
    //年龄小于45岁的人数是:2

    2.7 reduce

    reduce 操作可以实现从一组值中生成一个值。在上述例子中用到的 count 、 min 和 max 方法,因为常用而被纳入标准库中。事实上,这些方法都是 reduce 操作。及早求值。

    public class TestCase {
        public static void main(String[] args) {
            Integer reduce = Stream.of(1, 2, 3, 4).reduce(0, (acc, x) -> acc+ x);
            System.out.println(reduce);
        }
    }
    //输出结果
    //10

    三、高级集合类及收集器

    3.1 转换成值

    收集器,一种通用的、从流生成复杂值的结构。只要将它传给 collect 方法,所有的流就都可以使用它了。标准类库已经提供了一些有用的收集器,以下示例代码中的收集器都是从 java.util.stream.Collectors 类中静态导入的。

    public class CollectorsTest {
        public static void main(String[] args) {
            List<Student> students1 = new ArrayList<>(3);
            students1.add(new Student("路飞", 23, 175));
            students1.add(new Student("红发", 40, 180));
            students1.add(new Student("白胡子", 50, 185));
    
            OutstandingClass ostClass1 = new OutstandingClass("一班", students1);
            //复制students1,并移除一个学生
            List<Student> students2 = new ArrayList<>(students1);
            students2.remove(1);
            OutstandingClass ostClass2 = new OutstandingClass("二班", students2);
            //将ostClass1、ostClass2转换为Stream
            Stream<OutstandingClass> classStream = Stream.of(ostClass1, ostClass2);
            OutstandingClass outstandingClass = biggestGroup(classStream);
            System.out.println("人数最多的班级是:" + outstandingClass.getName());
    
            System.out.println("一班平均年龄是:" + averageNumberOfStudent(students1));
        }
    
        /**
         * 获取人数最多的班级
         */
        private static OutstandingClass biggestGroup(Stream<OutstandingClass> outstandingClasses) {
            return outstandingClasses.collect(
                    maxBy(comparing(ostClass -> ostClass.getStudents().size())))
                    .orElseGet(OutstandingClass::new);
        }
    
        /**
         * 计算平均年龄
         */
        private static double averageNumberOfStudent(List<Student> students) {
            return students.stream().collect(averagingInt(Student::getAge));
        }
    }
    //输出结果
    //人数最多的班级是:一班
    //一班平均年龄是:37.666666666666664

    maxBy或者minBy就是求最大值与最小值。

    3.2 转换成块

    常用的流操作是将其分解成两个集合,Collectors.partitioningBy帮我们实现了,接收一个Predicate函数式接口。

    将示例学生分为会唱歌与不会唱歌的两个集合。

    public class PartitioningByTest {
        public static void main(String[] args) {
            //省略List<student> students的初始化
            Map<Boolean, List<Student>> listMap = students.stream().collect(
                Collectors.partitioningBy(student -> student.getSpecialities().
                                          contains(SpecialityEnum.SING)));
        }
    }

    3.3 数据分组

    数据分组是一种更自然的分割数据操作,与将数据分成 ture 和 false 两部分不同,可以使用任意值对数据分组。Collectors.groupingBy接收一个Function做转换。

    例子:根据学生第一个特长进行分组

    public class GroupingByTest {
        public static void main(String[] args) {
            //省略List<student> students的初始化
             Map<SpecialityEnum, List<Student>> listMap = 
                 students.stream().collect(
                 Collectors.groupingBy(student -> student.getSpecialities().get(0)));
        }
    }

    Collectors.groupingBy与SQL 中的 group by 操作是一样的。

    3.4 字符串拼接

    如果将所有学生的名字拼接起来,怎么做呢?通常只能创建一个StringBuilder,循环拼接。使用Stream,使用Collectors.joining()简单容易。

    public class JoiningTest {
        public static void main(String[] args) {
            List<Student> students = new ArrayList<>(3);
            students.add(new Student("路飞", 22, 175));
            students.add(new Student("红发", 40, 180));
            students.add(new Student("白胡子", 50, 185));
    
             String names = students.stream()
                 .map(Student::getName).collect(Collectors.joining(",","[","]"));
            System.out.println(names);
        }
    }
    //输出结果
    //[路飞,红发,白胡子]

    joining接收三个参数,第一个是分界符,第二个是前缀符,第三个是结束符。也可以不传入参数Collectors.joining(),这样就是直接拼接。

    https://mp.weixin.qq.com/s/O3uiIJ6vRNWth0RLwEo_0w

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  • 原文地址:https://www.cnblogs.com/luweiweicode/p/14212397.html
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