java

jackson中objectMapper的使用

2019-04-16  本文已影响47人  谁在烽烟彼岸

Jackson可以轻松的将Java对象转换成json对象和xml文档，同样也可以将json、xml转换成Java对象
ObjectMapper类是Jackson库的主要类。它称为ObjectMapper的原因是因为它将JSON映射到Java对象（反序列化），或将Java对象映射到JSON（序列化）。它使用JsonParser和JsonGenerator的实例实现JSON实际的读/写。

maven 安装

<dependency>
  <groupId>com.fasterxml.jackson.core</groupId>
  <artifactId>jackson-core</artifactId>
  <version>2.9.6</version>
</dependency>

<dependency>
  <groupId>com.fasterxml.jackson.core</groupId>
  <artifactId>jackson-annotations</artifactId>
  <version>2.9.6</version>
</dependency>

<dependency>
  <groupId>com.fasterxml.jackson.core</groupId>
  <artifactId>jackson-databind</artifactId>
  <version>2.9.6</version>
</dependency>

Jackson ObjectMapper如何将JSON字段与Java字段匹配

三种方式
1.Jackson通过将JSON字段的名称与Java对象中的getter和setter方法相匹配，将JSON对象的字段映射到Java对象中的字段。Jackson删除了getter和setter方法名称的“get”和“set”部分，并将剩余名称的第一个字符转换为小写。
2.Jackson还可以通过java反射进行匹配
3.通过注解或者其它方式进行自定义的序列化和反序列化程序。

转Java对象

  1. Read Object From JSON String
ObjectMapper objectMapper = new ObjectMapper();
String carJson = "{ \"brand\" : \"Mercedes\", \"doors\" : 5 }";
Car car = objectMapper.readValue(carJson, Car.class);

2.Read Object From JSON Reader

ObjectMapper objectMapper = new ObjectMapper();
String carJson =  "{ \"brand\" : \"Mercedes\", \"doors\" : 4 }";
Reader reader = new StringReader(carJson);
Car car = objectMapper.readValue(reader, Car.class);

3.Read Object From JSON File

ObjectMapper objectMapper = new ObjectMapper();
File file = new File("data/car.json");
Car car = objectMapper.readValue(file, Car.class);
  1. Read Object From JSON via URL
ObjectMapper objectMapper = new ObjectMapper();
URL url = new URL("file:data/car.json");
Car car = objectMapper.readValue(url, Car.class);

本例使用的是文件URL，也可使用一个HTTP URL（如：http://jenkov.com/some-data.json ).

  1. Read Object From JSON InputStream
ObjectMapper objectMapper = new ObjectMapper();
InputStream input = new FileInputStream("data/car.json");
Car car = objectMapper.readValue(input, Car.class);

6.Read Object From JSON Byte Array

ObjectMapper objectMapper = new ObjectMapper();
String carJson =  "{ \"brand\" : \"Mercedes\", \"doors\" : 5 }";
byte[] bytes = carJson.getBytes("UTF-8");
Car car = objectMapper.readValue(bytes, Car.class);

7.Read Object Array From JSON Array String

String jsonArray = "[{\"brand\":\"ford\"}, {\"brand\":\"Fiat\"}]";
ObjectMapper objectMapper = new ObjectMapper();
Car[] cars2 = objectMapper.readValue(jsonArray, Car[].class);
  1. Read Object List From JSON Array String
String jsonArray = "[{\"brand\":\"ford\"}, {\"brand\":\"Fiat\"}]";
ObjectMapper objectMapper = new ObjectMapper();
List<Car> cars1 = objectMapper.readValue(jsonArray, new TypeReference<List<Car>>(){});
  1. Read Map from JSON String
String jsonObject = "{\"brand\":\"ford\", \"doors\":5}";
ObjectMapper objectMapper = new ObjectMapper();
Map<String, Object> jsonMap = objectMapper.readValue(jsonObject,
    new TypeReference<Map<String,Object>>(){});

转Json

ObjectMapper write有三个方法

  • writeValue()
  • writeValueAsString()
  • writeValueAsBytes()
ObjectMapper objectMapper = new ObjectMapper();
Car car = new Car();
car.brand = "BMW";
car.doors = 4;
//写到文件中
objectMapper.writeValue( new FileOutputStream("data/output-2.json"), car);
//写到字符串中
String json = objectMapper.writeValueAsString(car);

使用Jackson ObjectMapper读取和写入其他数据格式

使用Jackson可以读取和写入除JSON之外的其他数据格式：

  • CBOR
  • MessagePack
  • YAML

其中这些数据格式比JSON更紧凑，因此在存储时占用的空间更少，并且读取和写入速度比JSON更快。在以下部分中，我将向您展示如何使用Jackson读取和写入其中一些数据格式。

使用Jackson ObjectMapper读写CBOR

CBOR是一种二进制数据格式，它与JSON兼容，但比JSON更紧凑，因此读写速度更快。Jackson ObjectMapper可以像读写JSON一样读写CBOR。为了使用Jackson读取和写入CBOR，您需要为项目添加额外的Maven依赖项。介绍了添加Jackson CBOR Maven依赖关系：

import com.fasterxml.jackson.core.JsonProcessingException; 
import com.fasterxml.jackson.databind.ObjectMapper; 
import com.fasterxml.jackson.dataformat.cbor.CBORFactory; 

public class CborJacksonExample {
    public static void main(String[] args) {
        ObjectMapper objectMapper = new ObjectMapper(new CBORFactory());
        Employee employee = new Employee("John Doe", "john@doe.com");
        byte[] cborBytes = null;
        try {
            cborBytes = objectMapper.writeValueAsBytes(employee);
        } catch (JsonProcessingException e) {
            e.printStackTrace();
            // normally, rethrow exception here - or don't catch it at all.
        }
        try {
            Employee employee2 = objectMapper.readValue(cborBytes, Employee.class);
        } catch (IOException e) {
            e.printStackTrace();
        }
    }
}

使用Jackson ObjectMapper读取和编写MessagePack

MessagePack是一种文本数据格式，与JSON兼容，但更紧凑，因此读写速度更快。Jackson ObjectMapper可以像读写JSON一样读写MessagePack。为了使用Jackson读写MessagePack，您需要为项目添加额外的Maven依赖项：

import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.ObjectMapper;
import org.msgpack.jackson.dataformat.MessagePackFactory;

import java.io.IOException;

public class MessagePackJacksonExample {
    public static void main(String[] args) {
        ObjectMapper objectMapper = new ObjectMapper(new MessagePackFactory());

        Employee employee = new Employee("John Doe", "john@doe.com");

        byte[] messagePackBytes = null;
        try {
            messagePackBytes = objectMapper.writeValueAsBytes(employee);
        } catch (JsonProcessingException e) {
            e.printStackTrace();
            // normally, rethrow exception here - or don't catch it at all.
        }

        try {
            Employee employee2 = objectMapper.readValue(messagePackBytes, Employee.class);
            System.out.println("messagePackBytes = " + messagePackBytes);
        } catch (IOException e) {
            e.printStackTrace();
        }

    }
}

使用Jackson ObjectMapper读取和编写YAML

YAML是一种文本数据格式，类似于JSON，但使用不同的语法。Jackson ObjectMapper可以像读写JSON一样读写YAML。为了使用Jackson读取和写入YAML，您需要为项目添加额外的Maven依赖项：

import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.fasterxml.jackson.dataformat.yaml.YAMLFactory;

import java.io.IOException;

public class YamlJacksonExample {

    public static void main(String[] args) {
        ObjectMapper objectMapper = new ObjectMapper(new YAMLFactory());

        Employee employee = new Employee("John Doe", "john@doe.com");

        String yamlString = null;
        try {
            yamlString = objectMapper.writeValueAsString(employee);
        } catch (JsonProcessingException e) {
            e.printStackTrace();
            // normally, rethrow exception here - or don't catch it at all.
        }

        try {
            Employee employee2 = objectMapper.readValue(yamlString, Employee.class);

            System.out.println("Done");
        } catch (IOException e) {
            e.printStackTrace();
        }

    }
}

ObjectMapper的设置

ObjectMapper objectMapper = new ObjectMapper();
//去掉默认的时间戳格式     
objectMapper.configure(SerializationFeature.WRITE_DATES_AS_TIMESTAMPS, false);
//设置为东八区
objectMapper.setTimeZone(TimeZone.getTimeZone("GMT+8"));
// 设置输入:禁止把POJO中值为null的字段映射到json字符串中
objectMapper.configure(SerializationFeature.WRITE_NULL_MAP_VALUES, false);
 //空值不序列化
objectMapper.setSerializationInclusion(JsonInclude.Include.NON_NULL);
//反序列化时，属性不存在的兼容处理
objectMapper.getDeserializationConfig().withoutFeatures(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES);
//序列化时，日期的统一格式
objectMapper.setDateFormat(new SimpleDateFormat("yyyy-MM-dd HH:mm:ss"));
//序列化日期时以timestamps输出，默认true
objectMapper.configure(SerializationFeature.WRITE_DATES_AS_TIMESTAMPS, false);
//序列化枚举是以toString()来输出，默认false，即默认以name()来输出
objectMapper.configure(SerializationFeature.WRITE_ENUMS_USING_TO_STRING,true);
//序列化枚举是以ordinal()来输出，默认false
objectMapper.configure(SerializationFeature.WRITE_ENUMS_USING_INDEX,false);
//类为空时，不要抛异常
objectMapper.configure(SerializationFeature.FAIL_ON_EMPTY_BEANS, false);
//反序列化时,遇到未知属性时是否引起结果失败
objectMapper.configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false);
 //单引号处理
objectMapper.configure(JsonParser.Feature.ALLOW_SINGLE_QUOTES, true);
//解析器支持解析结束符
objectMapper.configure(JsonParser.Feature.ALLOW_UNQUOTED_CONTROL_CHARS, true);

自定义解析器

ObjectMapper 可以通过自定义解析器来定义解析方法
以下是自定义的反序列化的方法

import com.fasterxml.jackson.core.JsonParser;
import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.DeserializationContext;
import com.fasterxml.jackson.databind.JsonDeserializer;
import com.fasterxml.jackson.databind.JsonNode;
import org.springframework.data.geo.Point;

import java.io.IOException;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;

public class Point_Fastjson_Deserialize extends JsonDeserializer<Point> {

    @Override
    public Point deserialize(JsonParser jsonParser, DeserializationContext deserializationContext) throws IOException, JsonProcessingException {
        JsonNode node = jsonParser.getCodec().readTree(jsonParser);
        Iterator<JsonNode> iterator = node.get("coordinates").elements();
        List<Double> list = new ArrayList<>();
        while (iterator.hasNext()) {
            list.add(iterator.next().asDouble());
        }
        return new Point(list.get(0), list.get(1));
    }
}

注册到objectMapper中

ObjectMapper objectMapper = new ObjectMapper();
SimpleModule module = new SimpleModule();
module.addDeserializer(Point.class, new Point_Fastjson_Deserialize());
objectMapper.registerModule(module);
上一篇下一篇

猜你喜欢

热点阅读