java IO之 序列流 集合对象Properties 打印流 流对象

序列流

也称为合并流。

SequenceInputStream

　　序列流，对多个流进行合并。

　　SequenceInputStream 表示其他输入流的逻辑串联。它从输入流的有序集合开始，并从

　第一个输入流开始读取，直到到达文件末尾，接着从第二个输入流读取，依次类推，直到到达

包含的最后一个输入流的文件末尾为止。

　　注意：

　　构造函数

　　SequenceInputStream(InputStream s1, InputStream s2)

　　SequenceInputStream(InputStream s1, InputStream s2)

　　合并两个流

　　使用构造函数SequenceInputStream(InputStream s1, InputStream s2)

private static void testSequenceInputStream() throws IOException {
        FileInputStream fis1 = new FileInputStream("c:\\a.txt");
        FileInputStream fis2 = new FileInputStream("c:\\b.txt");

        SequenceInputStream s1 = new SequenceInputStream(fis1, fis2);
        int len = 0;
        byte[] byt = new byte[1024];

        FileOutputStream fos = new FileOutputStream("c:\\z.txt");

        while ((len = s1.read(byt)) != -1) {
            fos.write(byt, 0, len);
        }
        s1.close();
    }

合并多个流:

public static void testSequenceInputStream() throws Exception {
        InputStream in1 = new FileInputStream("c:/a.txt");
        InputStream in2 = new FileInputStream("c:/b.txt");
        InputStream in3 = new FileInputStream("c:/c.txt");

        LinkedHashSet<InputStream> set = new LinkedHashSet<InputStream>();
        set.add(in1);
        set.add(in2);
        set.add(in3);
        final Iterator<InputStream> iter = set.iterator();

        SequenceInputStream sin = new SequenceInputStream(
                new Enumeration<InputStream>() {
                    @Override
                    public boolean hasMoreElements() {
                        return iter.hasNext();
                    }

                    @Override
                    public InputStream nextElement() {
                        return iter.next();
                    }
                });

        FileOutputStream out = new FileOutputStream("c:/z.txt");

        for (int b = -1; (b = sin.read()) != -1;) {
            out.write(b);
        }
        sin.close();
        out.close();
    }

案例:将map3歌曲文件进行切割拷贝,并合并.

public class Demo2 {
    public static void main(String[] args) throws IOException {

        split(new File("c:\\a.mp3"), 10, new File("c:\\"));
        System.out.println("切割完毕");
        LinkedHashSet<InputStream> hs = new LinkedHashSet<InputStream>();
        hs.add(new FileInputStream(new File("c:\\part.1.mp3")));
        hs.add(new FileInputStream(new File("c:\\part.2.mp3")));
        hs.add(new FileInputStream(new File("c:\\part.3.mp3")));
        hs.add(new FileInputStream(new File("c:\\part.4.mp3")));
        merage(hs, new File("c:\\merage.mp3"));
        System.out.println("合并完毕");
    }
    private static void merage(LinkedHashSet<InputStream> hs, File dest)
            throws IOException {

        final Iterator<InputStream> it = hs.iterator();
        FileOutputStream fos = new FileOutputStream(dest);
        SequenceInputStream seq = new SequenceInputStream(
                new Enumeration<InputStream>() {

                    @Override
                    public boolean hasMoreElements() {

                        return it.hasNext();
                    }

                    @Override
                    public InputStream nextElement() {
                        return it.next();
                    }
                });
        byte[] byt = new byte[1024 * 1024];
        int len = 0;
        while ((len = seq.read(byt)) != -1) {
            fos.write(byt, 0, len);
        }
        seq.close();
        fos.close();
    }

    // 1. 切割文件
    /*
     * 切割文件,切割份数, 切割后保存路径
     */
    private static void split(File src, int count, File dir) throws IOException {
        FileInputStream fis = new FileInputStream(src);
        FileOutputStream fos = null;
        byte[] byt = new byte[1024 * 1024];
        int len = 0;
        for (int i = 1; i <= count; i++) {
            len = fis.read(byt);
            if (len != -1) {
                fos = new FileOutputStream(dir + "part." + i + ".mp3");
                fos.write(byt, 0, len);
            }
            // fos.close();
        }
        fis.close();

    }
}

对象的序列化

　　当创建对象时，程序运行时它就会存在，但是程序停止时，对象也就消失了。但是如果希望

对象在程序不运行的情况下仍能存在并保存其信息，将会非常有用，对象将被重建并且拥有与程

序上次运行时拥有的信息相同。可以使用对象的序列化。

　　对象的序列化：将内存中的对象直接写入到文件设备中。

　　对象的反序列化：将文件设备中持久化的数据转换为内存对象

　　基本的序列化由两个方法产生：一个方法用于序列化对象并将它们写入一个流，另一个方法

用于读取流并反序列化对象。

ObjectOutput
  writeObject(Object obj)   将对象写入底层存储或流。
ObjectInput
  readObject()    读取并返回对象。

ObjectOutputStream

ObjectInputStream

由于上述ObjectOutput和ObjectInput是接口，所以需要使用具体实现类。

ObjectOutput
  ObjectOutputStream 被写入的对象必须实现一个接口:Serializable 否则会抛出：NotSerializableException
ObjectInput
  ObjectInputStream    该方法抛出异常：ClassNotFountException 

ObjectOutputStream和ObjectInputStream 对象分别需要字节输出流和字节输入流对象来构建对象。也就是这两个流对象需要操作已有对象将对象进行本地持久化存储。

案例：

序列化和反序列化Cat对象。

public class demo3 {
    public static void main(String[] args) throws IOException,
            ClassNotFoundException {
        Cat cat = new Cat("tom", 3);
        FileOutputStream fos = new FileOutputStream(new File("c:\\Cat.txt"));
        ObjectOutputStream oos = new ObjectOutputStream(fos);
        oos.writeObject(cat);
        System.out.println("1"+cat);
        oos.close();
        // 反序列化
        FileInputStream fis = new FileInputStream(new File("c:\\Cat.txt"));
        ObjectInputStream ois = new ObjectInputStream(fis);
        Object readObject = ois.readObject();
        Cat cat2 = (Cat) readObject;
        System.out.println("2"+cat2);
        fis.close();
    }
}
    class Cat implements Serializable {
        public String name;
        public int age;
        public Cat() {
        }
        public Cat(String name, int age) {
            this.name = name;
            this.age = age;
        }
        @Override
        public String toString() {
            return "Cat [name=" + name + ", age=" + age + "]";
        }
    }

例子关键点：

1. 声明Cat类实现了Serializable接口。是一个标示器，没有要实现的方法。
2. 新建Cat对象。
3. 新建字节流对象（FileOutputStream）进序列化对象保存在本地文件中。
4. 新建ObjectOutputStream对象，调用writeObject方法序列化Cat对象。
5. writeObject方法会执行两个工作：序列化对象，然后将序列化的对象写入文件中。
6. 反序列化就是调用ObjectInputStream的readObject()方法。
7. 异常处理和流的关闭动作要执行。

Serializable：

类通过实现 java.io.Serializable 接口以启用其序列化功能。未实现此接口的类将无法使其任何状态序列化或反序列化。可序列化类的所有子类型本身都是可序列化的。序列化接口没有方法或字段，仅用于标识可序列化的语义。

所以需要被序列化的类必须是实现Serializable接口，该接口中没有描述任何的属性和方法，称之为标记接口。

如果对象没有实现接口Serializable，在进行序列化时会抛出：NotSerializableException 异常。

注意：

保存一个对象的真正含义是什么？如果对象的实例变量都是基本数据类型，那么就非常简单。但是如果实例变量是包含对象的引用，会怎么样？保存的会是什么？很显然在Java中保存引用变量的实际值没有任何意义，因为Java引用的值是通过JVM的单一实例的上下文中才有意义。通过序列化后，尝试在JVM的另一个实例中恢复对象，是没有用处的。

如下：

首先建立一个Dog对象，也建立了一个Collar对象。Dog中包含了一个Collar(项圈)

现在想要保存Dog对象，但是Dog中有一个Collar，意味着保存Dog时也应该保存Collar。假如Collar也包含了其他对象的引用，那么会发生什么？意味着保存一个Dog对象需要清楚的知道Dog对象的内部结构。会是一件很麻烦的事情。

Java的序列化机制可以解决该类问题，当序列化一个对象时，Java的序列化机制会负责保存对象的所有关联的对象（就是对象图），反序列化时，也会恢复所有的相关内容。本例中：如果序列化Dog会自动序列化Collar。但是，只有实现了Serializable接口的类才可以序列化。如果只是Dog实现了该接口，而Collar没有实现该接口。会发生什么？

Dog类和Collar类

import java.io.Serializable;

public class Dog implements Serializable {
    private Collar collar;
    private String name;

    public Dog(Collar collar, String name) {

        this.collar = collar;
        this.name = name;
    }

    public Collar getCollar() {
        return collar;
    }

}

class Collar {
    private int size;

    public int getSize() {
        return size;
    }

    public Collar(int size) {
        this.size = size;
    }

}

序列化

import java.io.File;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.ObjectOutputStream;

public class Demo4 {
    public static void main(String[] args) throws IOException {
        Collar coll = new Collar(10);
        Dog dog = new Dog(coll, "旺财");

        FileOutputStream fis = new FileOutputStream(new File("c:\\dog.txt"));
        ObjectOutputStream os = new ObjectOutputStream(fis);
        os.writeObject(dog);
    }
}

执行程序，出现了运行时异常。

Exception in thread "main" java.io.NotSerializableException: Collar

所以我们也必须将Dog中使用的Collar序列化。但是如果我们无法访问Collar的源代码，或者无法使Collar可序列化，如何处理？

两种解决方法：

一：继承Collar类，使子类可序列化

但是：如果Collar是final类，就无法继承了。并且，如果Collar引用了其他非序列化对象，也无法解决该问题。

transient

此时就可以使用transient修饰符，可以将Dog类中的成员变量标识为transient

那么在序列化Dog对象时，序列化就会跳过Collar。

public class Demo4 {
    public static void main(String[] args) throws IOException,
            ClassNotFoundException {
        Collar coll = new Collar(10);
        Dog dog = new Dog(coll, "旺财");
        System.out.println(dog.getCollar().getSize());

        FileOutputStream fis = new FileOutputStream(new File("c:\\dog.txt"));
        ObjectOutputStream os = new ObjectOutputStream(fis);
        os.writeObject(dog);

        // 反序列化
        FileInputStream fos = new FileInputStream(new File("c:\\dog.txt"));
        ObjectInputStream ois = new ObjectInputStream(fos);
        Object readObject = ois.readObject();
        Dog dog2 = (Dog) readObject;
        // Collar未序列化。
        dog2.getCollar().getSize();
    }
}

这样我们具有一个序列化的Dog和非序列化的Collar。

此时反序列化Dog后，访问Collar，就会出现运行时异常

10
Exception in thread "main" java.lang.NullPointerException

注意：序列化不适用于静态变量，因为静态变量并不属于对象的实例变量的一部分。

静态变量随着类的加载而加载，是类变量。由于序列化只适用于对象。

基本数据类型可以被序列化

public class Demo5 {
    public static void main(String[] args) throws IOException {
        // 创建序列化流对象
        FileOutputStream fis = new FileOutputStream(new File("c:\\basic.txt"));
        ObjectOutputStream os = new ObjectOutputStream(fis);
        // 序列化基本数据类型
        os.writeDouble(3.14);
        os.writeBoolean(true);
        os.writeInt(100);
        os.writeInt(200);
        // 关闭流
        os.close();
        // 反序列化
        FileInputStream fos = new FileInputStream(new File("c:\\basic.txt"));
        ObjectInputStream ois = new ObjectInputStream(fos);
        System.out.println(ois.readDouble());
        System.out.println(ois.readBoolean());
        System.out.println(ois.readInt());
        System.out.println(ois.readInt());

        fos.close();
    }
}

serialVersionUID

用于给类指定一个UID。该UID是通过类中的可序列化成员的数字签名运算出来的一个long型的值。

只要是这些成员没有变化，那么该值每次运算都一样。

该值用于判断被序列化的对象和类文件是否兼容。

如果被序列化的对象需要被不同的类版本所兼容。可以在类中自定义UID。

定义方式：static final long serialVersionUID = 42L;

Properties.

可以和流相关联的集合对象Properties.

　　Map

　　　　|--Hashtable

　　　　|--Properties

　　Properties:该集合不需要泛型，因为该集合中的键值对都是String类型。

　　1，存入键值对：setProperty(key,value);

　　2，获取指定键对应的值：value getProperty(key);

　　3，获取集合中所有键元素：Enumeration  propertyNames();

　　　　　　在jdk1.6版本给该类提供一个新的方法。Set<String> stringPropertyNames();

　　4，列出该集合中的所有键值对，可以通过参数打印流指定列出到的目的地。

　　　　list(PrintStream);

　　　　　　list(PrintWriter);

　　　　　　例：list(System.out):将集合中的键值对打印到控制台。

　　　　　　list(new PrintStream("prop.txt")):将集合中的键值对存储到prop.txt文件中。

　　5，可以将流中的规则数据加载进行集合，并称为键值对。

　　　　load(InputStream):

　　　　jdk1.6版本。提供了新的方法。　load(Reader):

　　　　　　注意：流中的数据要是"键=值" 的规则数据。

　　6，可以将集合中的数据进行指定目的的存储。　store(OutputStram,String comment)方法。

　　jdk1.6版本。提供了新的方法。store(Writer ,String comment):

　　使用该方法存储时，会带着当时存储的时间。

　　注意：

　　Properties只加载key=value这样的键值对，与文件名无关，注释使用#

　　练习：记录一个程序运行的次数，当满足指定次数时，该程序就不可以再继续运行了。

　　通常可用于软件使用次数的限定。

public static void sysPropList() throws IOException {
        Properties prop = System.getProperties();

        // prop.list(System.out);// 目的是控制台。
        // 需求是：将jvm的属性信息存储到一个文件中。
        prop.list(new PrintStream("java.txt"));
    }

    public static void sysProp() {
        Properties prop = System.getProperties();

        Set<String> keys = prop.stringPropertyNames();

        for (String key : keys) {
            System.out.println(key + ":" + prop.getProperty(key));
        }
    }

800x600

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false
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EN-US
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MicrosoftInternetExplorer4

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mso-tstyle-rowband-size:0;
mso-tstyle-colband-size:0;
mso-style-noshow:yes;
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font-family:"Times New Roman",serif;}

Properties类与配置文件

Map

|--Hashtable

|--Properties

注意：是一个Map集合，该集合中的键值对都是字符串。该集合通常用于对键值对形式的配置文件进行操作.

配置文件：将软件中可变的部分数据可以定义到一个文件中，方便以后更改，该文件称之为配置文件。

优势: 提高代码的维护性。

　　Properties:  该类是一个Map的子类，提供了可以快速操作配置文件的方法

　　load()  :    将文件设备数据装载为Map集合数据

　　get(key):    获取Map中的数据

　　getProperty()获取Map中的数据特有方法

案例：

/*
     * 将配置文件中的数据通过流加载到集合中。
     */
    public static void loadFile() throws IOException {
        // 1,创建Properties(Map)对象
        Properties prop = new Properties();
        // 2.使用流加载配置文件。
        FileInputStream fis = new FileInputStream("c:\\qq.txt");
        // 3。使用Properties 对象的load方法将流中数据加载到集合中。
        prop.load(fis);
        // 遍历该集合
        Set<Entry<Object, Object>> entrySet = prop.entrySet();
        Iterator<Entry<Object, Object>> it = entrySet.iterator();
        while (it.hasNext()) {
            Entry<Object, Object> next = it.next();
            Object key = next.getKey();
            Object value = next.getValue();
        }
        // 通过键获取指定的值
        Object object = prop.get("jack");
        System.out.println(object);
        // 通过键修改值
        prop.setProperty("jack", "888888");
        // 将集合中的数据写入到配置文件中。
        FileOutputStream fos = new FileOutputStream("c:\\qq.txt");
        // 注释：
        prop.store(fos, "yes,qq");
        fos.close();
        fis.close();
    }

获取记录程序运行次数：

public class Demo6 {
    public static void main(String[] args) throws IOException {
        int count = 0;
        Properties pro = new Properties();

        File file = new File("c:\\count.ini");
        FileInputStream fis = null;
        if (!file.exists()) {
            file.createNewFile();
        }
        fis = new FileInputStream(file);
        pro.load(fis);
        String str = pro.getProperty("count");
        if (str != null) {
            count = Integer.parseInt(str);
        }
        if (count == 3) {
            System.out.println("使用次数已到，请付费");
            System.exit(0);
        }

        count++;
        System.out.println("欢迎使用本软件" + "你已经使用了：" + count + " 次");

        pro.setProperty("count", count + "");
        FileOutputStream fos = new FileOutputStream(new File("c:\\count.ini"));
        pro.store(fos, "请保护知识产权");

        fis.close();
        fos.close();

    }
}

打印流

PrintStream可以接受文件和其他字节输出流，所以打印流是对普通字节输出流的增强，

其中定义了很多的重载的print()和println()，方便输出各种类型的数据。

PrintStream

PrintWriter

1，打印流。

PrintStream：

　　是一个字节打印流，System.out对应的类型就是PrintStream。

　　它的构造函数可以接收三种数据类型的值。

　　　　1，字符串路径。

　　　　2，File对象。

　　　　3，OutputStream。

public class pp {
    public static void main(String[] args) throws IOException {
        PrintStream ps = System.out;

        // 普通write方法需要调用flush或者close方法才会在控制台显示
        // ps.write(100);
        // ps.close();

        // 不换行打印
        ps.print(100);
        ps.print('a');
        ps.print(100.5);
        ps.print("世界");
        ps.print(new Object());
        System.out.println("--------------");
        // 换行
        ps.println(100);
        ps.println('a');
        ps.println(100.5);
        ps.println("世界");
        ps.println(new Object());

        // 重定向打印流
        PrintStream ps2 = new PrintStream(new File("c:\\a.txt"));
        System.setOut(ps2);
        // 换行
        ps2.println(100);
        ps2.println('a');
        ps2.println(100.5);
        ps2.println("世界");
        ps2.println(new Object());

        // printf(); 格式化
        ps2.printf("%d,%f,%c,%s", 100, 3.14, '中', "世界你好!!!");
        ps2.printf("%4s和%8s 打价格战", "京东", "苏宁");

    }
}

//结果：
100a100.5世界java.lang.Object@40e455bf--------------
100
a
100.5
世界
java.lang.Object@4eb98fe1

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" alt="" />

注意: 打印流的三种方法

void print(数据类型 变量)

　　println(数据类型 变量)

　　printf(String format, Object... args)

可以自定数据格式

print 和println方法的区别在于,一个换行一个不换行

print 方法和write方法的却别在于,print提供自动刷新.

普通的write方法需要调用flush或者close方法才可以看到数据.

JDK1.5之后Java对PrintStream进行了扩展，增加了格式化输出方式，可以使用printf()重载方法直接格式化输出。但是在格式化输出的时候需要指定输出的数据类型格式。

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" alt="" />

PrintWriter

是一个字符打印流。构造函数可以接收四种类型的值。

　　1，字符串路径。

　　2，File对象。

　　对于1，2类型的数据，还可以指定编码表。也就是字符集。

　　3，OutputStream

　　4，Writer

　　对于3，4类型的数据，可以指定自动刷新。

　　注意：该自动刷新值为true时，只有三个方法可以用：println,printf,format.

　　如果想要既有自动刷新，又可执行编码。如何完成流对象的包装？

　　PrintWrter pw = new PrintWriter(new OutputSteamWriter(new FileOutputStream("a.txt"),"utf-8"),true);

　　如果想要提高效率。还要使用打印方法。

　　PrintWrter pw = newPrintWriter(new  BufferdWriter(new OutputSteamWriter(

newFileOutputStream("a.txt"),"utf-8")),true);

public static void testPrintWriter() throws Exception {
        PrintWriter pw = new PrintWriter("c:/b.txt", "gbk");

        // pw.append("xxx");
        // pw.println(55);
        // pw.println('c');
        // pw.printf("%.1s与%4s打价格战, %c", "京东","苏宁", 'a');

        pw.close();

    }

Scanner

public static void testScanner() throws Exception {
        // Scanner scanner = new Scanner(new File("c:/test.txt"));
        Scanner scanner = new Scanner(System.in);

        System.out.println(scanner.nextInt());
        System.out.println(scanner.nextBoolean());

        scanner.close();
    }

操作数组的流对象

操作字节数组

　　ByteArrayInputStream 以及ByteArrayOutputStream

　　toByteArray();

　　toString();

　　writeTo(OutputStream);

public static void testByteArrayInputStream() throws Exception {
        InputStream in = new ByteArrayInputStream(new byte[] { 65, 66, 67 });
        ByteArrayOutputStream out = new ByteArrayOutputStream();

        for (int b = -1; (b = in.read()) != -1;) {
            out.write(b);
        }

        in.close();
        out.close();

        System.out.println(Arrays.toString(out.toByteArray()));
        System.out.println(out);
    }

操作字符数组

CharArrayReader

CharArrayWriter

对于这些流，源是内存。目的也是内存。

而且这些流并未调用系统资源。使用的就是内存中的数组。

所以这些在使用的时候不需要close。

操作数组的读取流在构造时，必须要明确一个数据源。所以要传入相对应的数组。

对于操作数组的写入流，在构造函数可以使用空参数。因为它内置了一个可变长度数组作为缓冲区。

public static void testCharArrayReader() throws Exception {
        CharArrayReader reader = new CharArrayReader(new char[] { 'A', 'b', 'c' });
        CharArrayWriter writer = new CharArrayWriter();

        for (int b = -1; (b = reader.read()) != -1;) {
            writer.write(b);
        }

        reader.close();
        writer.close();

        System.out.println(writer.toCharArray());
    }

这几个流的出现其实就是通过流的读写思想在操作数组。

类似的对象同理：

StringReader

StringWriter。

public static void testStringReader() throws Exception {
        StringReader reader = new StringReader("test 中国");
        StringWriter writer = new StringWriter();

        for (int b = -1; (b = reader.read()) != -1;) {
            writer.write(b);
        }

        reader.close();
        writer.close();

        System.out.println(writer.toString());
    }

操作基本数据类型的流对象

DataInputStream

以及DataOutputStream

查看API文档DataInputStream的信息。发现从底层输入流中读取基本 Java 数据类型。查看方法,有读一个字节,读一个char读一个double 的方法,

DataInputStream 从数据流读取字节，并将它们转换为正确的基本数据类型值或字符串。

该流有操作基本数据类型的方法.

有读的,那么必定有对应的写的就是DataOutputStream 将基本类型的值或字符串转换为字节，并且将字节输出到数据流。

DataInputStream类继承FilterInputStream类，并实现了DataInput接口。DataOutputStream

类继承FilterOutputStream 并实现了DataOutput 接口。

例如：

DataInputStream
操作基本数据类型的方法：
int readInt():一次读取四个字节，并将其转成int值。
boolean readBoolean():一次读取一个字节。
short readShort();
long readLong();
剩下的数据类型一样。
String readUTF():按照utf-8修改版读取字符。注意，它只能读writeUTF()写入的字符数据。
DataOutputStream
DataOutputStream(OutputStream):
操作基本数据类型的方法:
writeInt(int)：一次写入四个字节。
注意和write(int)不同。write(int)只将该整数的最低一个8位写入。剩余三个8位丢弃。
writeBoolean(boolean);
writeShort(short);
writeLong(long);
剩下是数据类型也也一样。
writeUTF(String):按照utf-8修改版将字符数据进行存储。只能通过readUTF读取。

测试:   DataOutputStream

使用DataOutputStream写数据文件。

public static void testDataInputStream() throws Exception {
        DataOutputStream out = new DataOutputStream(new FileOutputStream(
                "c:/a.txt"));
        out.writeBoolean(true);
        out.writeByte(15); // 0x05 1 个字节
        out.writeBytes("abc"); // 0x 0041 2个字节
        out.writeChar('X'); // ??
        out.writeChars("xyz");
        out.writeLong(111);
        out.writeUTF("中国");

        out.close();

        DataInputStream in = new DataInputStream(
                new FileInputStream("c:/a.txt"));
        System.out.println(in.readBoolean());
        System.out.println(in.readByte());

        System.out.println(in.readByte());
        System.out.println(in.readByte());
        System.out.println(in.readByte());

        System.out.println(in.readChar());

        System.out.println(in.readChar());
        System.out.println(in.readChar());
        System.out.println(in.readChar());

        System.out.println(in.readLong());

        System.out.println(in.readUTF());
        in.close();
    }

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false
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false

EN-US
ZH-CN
X-NONE

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