Lambda表达式案例

实现Runnable线程案例

使用()->{}替代匿名类:


//Before Java 8:
new Thread(new Runnable(){
      @Override
      public void run(){
            System.out.println("Before Java8.");
      }
}).start();

//Java 8 Way
new Thread(() -> System.out.println("In Java8.")).start();

你可以使用下面语法实现Lambda

()-> expression
()-> statement
()-> { statements }

如果你的方法并不改变任何方法参数,比如只是输出,那么可以简写如下

()-> System.out.println("Hello Lambda Expression");

如果你的方法接受两个方法参数,如下

(int even,int odd)-> even + odd

实现事件处理

如果曾经使用过Swing 编程,你将永远不会忘记编写时间侦听器代码。使用Lambda表达式如下所示写出更好的时间侦听器的代码。

在Java 8中你可以使用Lambda表达式替代丑陋的匿名类


// Before Java 8
JButton show = new JButton("Show");
show.addActionListener(new ActionListener(){
      @Override
      public void adtionPerformed(ActionEvent e){
            System.out.println("without lambda expression is boring");
      }
});

// Java 8 way;
show.addActionListener((e) -> {
      System.out.println("Action !! Lambda expressions Rocks");
});

使用Lambda表达式遍历List集合


//Prior Java 8 :
List features = Arrays.asList("Lambdas","Default Method","Stream API","Date and Time API");
for(String feature : features){
      System.out.println(feature);
}

//In Java 8 : 
List features = Arrays.asList("Lambdas","Default Method","Stream API","Date and Time API");
features.forEach(n -> System.out.println(n));
// 方法引用是使用两个冒号 :: 这个操作符号
features.forEach(System.out::println(n));

Output:
Lambdas
Default Method
Stream API
Date and Time API

使用Lambda表达式和函数接口

为了支持函数编程,Java 8 加入了一个新的包 java.util.function,其中有一个接口 java.util.function.Predicate 是支持 Lambda 函数变成:


public static void main(args[]){
  List languages = Arrays.asList("Java", "Scala", "C++", "Haskell", "Lisp");

  System.out.println("Languages which starts with J :");
  filter(languages, (str)->str.startsWith("J"));

  System.out.println("Languages which ends with a ");
  filter(languages, (str)->str.endsWith("a"));

  System.out.println("Print all languages :");
  filter(languages, (str)->true);

   System.out.println("Print no language : ");
   filter(languages, (str)->false);

   System.out.println("Print language whose length greater than 4:");
   filter(languages, (str)->str.length() > 4);
}

 public static void filter(List names, Predicate condition) {
    for(String name: names)  {
       if(condition.test(name)) {
          System.out.println(name + " ");
       }
    }
  }
}

Output:
Languages which starts with J :
Java
Languages which ends with a
Java
Scala
Print all languages :
Java
Scala
C++
Haskell
Lisp
Print no language :
Print language whose length greater than 4:
Scala
Haskell

//Even better
 public static void filter(List names, Predicate condition) {
    names.stream().filter((name) -> (condition.test(name)))
        .forEach((name) -> {System.out.println(name + " ");
    });
 }

你能看到来自Stream API 的filter 方法能够接受 Predicate参数,能够允许测试多个条件

复杂Predicate 使用

java.util.function.Predicate 提供and(),or() 和 xor() 可以进行逻辑操作,比如为了得到遗传字符串以"J"开头的4个长度:

Predicate<String> startsWithJ = (n) -> n.startsWith("J");
Predicate<String> fourLetterLong = (n) -> n.length() == 4;
   
 names.stream()
      .filter(startsWithJ.and(fourLetterLong))
      .forEach((n) -> System.out.print("\nName, which starts with
            'J' and four letter long is : " + n));

其中startsWithJ.and(fourLetterLong)是使用了AND逻辑操作

使用Lambda 实现Map 和 Reduce

最流行的函数编程概念是map,它允许你改变你的对象,在这个案例中,我们将costBeforeTeax集合中每个元素改变了增加一定的数值,我们将Lambda表达式 x -> x*x 传送map()方法,这将应用到 stream中所有元素。然后我们使用forEach() 打印出这个集合的元素。

// Without lambda expressions:
List costBeforeTax = Arrays.asList(100, 200, 300, 400, 500);
for (Integer cost : costBeforeTax) {
      double price = cost + .12*cost;
      System.out.println(price);
}

// With Lambda expression:
List costBeforeTax = Arrays.asList(100, 200, 300, 400, 500);
costBeforeTax.stream().map((cost) -> cost + .12*cost)
                      .forEach(System.out::println);

Output
112.0
224.0
336.0
448.0
560.0
112.0
224.0
336.0
448.0
560.0

reduce() 是将集合中所有值结合进一个,Reduce类似SQL语句中的 sum(),avg()或count()

// Old way:
List costBeforeTax = Arrays.asList(100, 200, 300, 400, 500);
double total = 0;
for (Integer cost : costBeforeTax) {
 double price = cost + .12*cost;
 total = total + price;
 
}
System.out.println("Total : " + total);

// New way:
List costBeforeTax = Arrays.asList(100, 200, 300, 400, 500);
double bill = costBeforeTax.stream().map((cost) -> cost + .12*cost)
                                    .reduce((sum, cost) -> sum + cost)
                                    .get();
System.out.println("Total : " + bill);

Output
Total : 1680.0
Total : 1680.0

通过filtering 创建一个字符串String的集合

Filtering是面向大型Collection的一个通用操作,Stream 提供filter() 方法,接受一个Predicate对象,意味着你能传送Lambda表达式作为一个过滤逻辑进入这个方法:

List<String> filtered = strList.stream().filter(x -> x.length()> 2)
                                        .collect(Collectors.toList());
System.out.printf("Original List : %s, filtered list : %s %n", 
                  strList, filtered);

Output :
Original List : [abc, , bcd, , defg, jk], filtered list : [abc, bcd, defg]

对集合中每个元素应用函数

我们经常需要对集合中元素运用一定的功能,如表中的每个元素乘以或除以一个值等等
下面是将字符串转换为大写,然后使用逗号串起来

List<String> G7 = Arrays.asList("USA", "Japan", "France", "Germany", 
                                "Italy", "U.K.","Canada");
String G7Countries = G7.stream().map(x -> x.toUpperCase())
                                .collect(Collectors.joining(", "));
System.out.println(G7Countries);

Output : 
USA, JAPAN, FRANCE, GERMANY, ITALY, U.K., CANADA

通过赋值不同的值创建一个子列表

使用Stream()的distinct()方法过滤集合中重复元素

List<Integer> numbers = Arrays.asList(9, 10, 3, 4, 7, 3, 4);
List<Integer> distinct = numbers.stream().map( i -> i*i).distinct()
                                         .collect(Collectors.toList());
System.out.printf("Original List : %s,  Square Without duplicates :
                   %s %n", numbers, distinct);

Output :
Original List : [9, 10, 3, 4, 7, 3, 4],  Square Without 
                                         duplicates : [81, 100, 9, 16, 49]

计算List中元素的最大值,最小值,总和及平均值

List<Integer> primes = Arrays.asList(2, 3, 5, 7, 11, 13, 17, 19, 23, 29);
IntSummaryStatistics stats = primes.stream().mapToInt((x) -> x)
                                            .summaryStatistics();
System.out.println("Highest prime number in List : " + stats.getMax());
System.out.println("Lowest prime number in List : " + stats.getMin());
System.out.println("Sum of all prime numbers : " + stats.getSum());
System.out.println("Average of all prime numbers : " + stats.getAverage());

Output : 
Highest prime number in List : 29
Lowest prime number in List : 2
Sum of all prime numbers : 129
Average of all prime numbers : 12.9
posted @ 2020-10-22 15:58  九角冰山  阅读(201)  评论(0编辑  收藏  举报