Java 8十个lambda表达式案例

1. 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:

(params) -> expression
(params) -> statement
(params) -> { 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 Expressions");

如果你的方法接受两个方法参数，如下：

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

2.实现事件处理

如果你曾经做过Swing 编程，你将永远不会忘记编写事件侦听器代码。使用lambda表达式如下所示写出更好的事件侦听器的代码

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 actionPerformed(ActionEvent e) {
           System.out.println("without lambda expression is boring");
        }
     });


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

3.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);

Output:
Lambdas
Default Method
Stream API
Date and Time API

4.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函数编程：

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

5.复杂的结合Predicate 使用

java.util.function.Predicate提供and(), or() 和 xor()可以进行逻辑操作，比如为了得到一串字符串中以"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("
Name, which starts with
            'J' and four letter long is : " + n));

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

6.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

7.通过filtering 创建一个字符串String的集合

Filtering是对大型Collection操作的一个通用操作，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]

8.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

9.通过复制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]

10.计算List中的元素的最大值，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