Java 8十个lambda表达式案例

java

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("\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

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

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