JackSon学习笔记(一)
概述
Jackson框架是基于Java平台的一套数据处理工具，被称为“最好的Java Json解析器”。
Jackson框架包含了3个核心库：streaming,databind,annotations.Jackson还包含了其它数据处理类库，此外不作说明。
Jackson版本： 1.x (目前版本从1.1~1.9)与2.x。1.x与2.x从包的命名上可以看出来，1.x的类库中，包命名以：org.codehaus.jackson.xxx开头，而2.x类库中包命令：com.fastxml.jackson.xxx开头
Jackson Home Page：https://github.com/FasterXML/jackson
Jackson Wiki：http://wiki.fasterxml.com/JacksonHome
Jackson doc: https://github.com/FasterXML/jackson-docs
Jackson Download Page：http://wiki.fasterxml.com/JacksonDownload
准备工作
本文所有程序都基于JDK1.7,依赖jackon的三个核心类库：
jackson-core-2.5.3.jar
jackson-annotations-2.5.3.jar
jackson-databind-2.5.3.jar
Jackson处理Json
Jackson提供了三种可选的Json处理方法：流式API(Streaming API) 、树模型(Tree Model)、数据绑定(Data Binding)。从使用角度来看，比较一下这三种处理Json的方式的特性：
Streaming API：是效率最高的处理方式(开销低、读写速度快，但程序编写复杂度高)
Tree Model：是最灵活的处理方式
Data Binding：是最常用的处理方式
下面我们通过例子程序分别使用DataBinding,TreeModel,Streaming的方式来创建和解析Json字符串
1.DataBinding处理Json
Jackson支持Java对象与Json之间的相互转化。java对象序列化为json字符串，json字符串也可以反序列化为相同的java对象。
(1)java对象转化成json:
Province.java
package com.jackson.json.databinding;
public class Province {
public String name;
public int population;
public String[] city;
}
Country.java
package com.jackson.json.databinding;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Date;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
public class Country {
// 注意：被序列化的bean的private属性字段需要创建getter方法或者属性字段应该为public
private String country_id;
private Date birthDate;
private List<String> nation = new ArrayList<String>();
private String[] lakes;
private List<Province> provinces = new ArrayList<Province>();
private Map<String, Integer> traffic = new HashMap<String, Integer>();
public Country() {
// TODO Auto-generated constructor stub
}
public Country(String countryId) {
this.country_id = countryId;
}
public String getCountry_id() {
return country_id;
}
public void setCountry_id(String country_id) {
this.country_id = country_id;
}
public Date getBirthDate() {
return birthDate;
}
public void setBirthDate(Date birthDate) {
this.birthDate = birthDate;
}
public List<String> getNation() {
return nation;
}
public void setNation(List<String> nation) {
this.nation = nation;
}
public String[] getLakes() {
return lakes;
}
public void setLakes(String[] lakes) {
this.lakes = lakes;
}
public Integer get(String key) {
return traffic.get(key);
}
public Map<String, Integer> getTraffic() {
return traffic;
}
public void setTraffic(Map<String, Integer> traffic) {
this.traffic = traffic;
}
public void addTraffic(String key, Integer value) {
traffic.put(key, value);
}
public List<Province> getProvinces() {
return provinces;
}
public void setProvinces(List<Province> provinces) {
this.provinces = provinces;
}
@Override
public String toString() {
return "Country [country_id=" + country_id + ", birthDate=" + birthDate
+ ", nation=" + nation + ", lakes=" + Arrays.toString(lakes)
+ ", province=" + provinces + ", traffic=" + traffic + "]";
}
}
JavaBeanSerializeToJson.java
package com.jackson.json.databinding;
import java.io.File;
import java.text.SimpleDateFormat;
import java.util.ArrayList;
import java.util.List;
import com.fasterxml.jackson.annotation.JsonInclude.Include;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.fasterxml.jackson.databind.SerializationFeature;
public class JavaBeanSerializeToJson {
public static void convert() throws Exception {
// 使用ObjectMapper来转化对象为Json
ObjectMapper mapper = new ObjectMapper();
// 添加功能，让时间格式更具有可读性
SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd");
mapper.setDateFormat(dateFormat);
Country country = new Country("China");
country.setBirthDate(dateFormat.parse("1949-10-01"));
country.setLakes(new String[] { "Qinghai Lake", "Poyang Lake",
"Dongting Lake", "Taihu Lake" });
List<String> nation = new ArrayList<String>();
nation.add("Han");
nation.add("Meng");
nation.add("Hui");
nation.add("WeiWuEr");
nation.add("Zang");
country.setNation(nation);
Province province = new Province();
province.name = "Shanxi";
province.population = 37751200;
Province province2 = new Province();
province2.name = "ZheJiang";
province2.population = 55080000;
List<Province> provinces = new ArrayList<Province>();
provinces.add(province);
provinces.add(province2);
country.setProvinces(provinces);
country.addTraffic("Train(KM)", 112000);
country.addTraffic("HighWay(KM)", 4240000);
// 为了使JSON视觉上的可读性，增加一行如下代码，注意，在生产中不需要这样，因为这样会增大Json的内容
mapper.configure(SerializationFeature.INDENT_OUTPUT, true);
// 配置mapper忽略空属性
mapper.setSerializationInclusion(Include.NON_EMPTY);
// 默认情况，Jackson使用Java属性字段名称作为 Json的属性名称,也可以使用Jackson annotations(注解)改变Json属性名称
mapper.writeValue(new File("country.json"), country);
}
public static void main(String[] args) throws Exception {
convert();
}
}
程序运行后生成country.json，内容如下：
{
"country_id" : "China",
"birthDate" : "1949-10-01",
"nation" : [ "Han", "Meng", "Hui", "WeiWuEr", "Zang" ],
"lakes" : [ "Qinghai Lake", "Poyang Lake", "Dongting Lake", "Taihu Lake" ],
"provinces" : [ {
"name" : "Shanxi",
"population" : 37751200
}, {
"name" : "ZheJiang",
"population" : 55080000
} ],
"traffic" : {
"HighWay(KM)" : 4240000,
"Train(KM)" : 112000
}
}
(2)Json字符串反序列化为java对象：
package com.jackson.json.databinding;
import java.io.File;
import java.io.IOException;
import java.text.SimpleDateFormat;
import java.util.Iterator;
import java.util.List;
import com.fasterxml.jackson.core.JsonParseException;
import com.fasterxml.jackson.databind.DeserializationFeature;
import com.fasterxml.jackson.databind.JsonMappingException;
import com.fasterxml.jackson.databind.ObjectMapper;
/**
* 将Json字符串反序列化为Java对象
*/
public class JsonDeserializeToJava {
public static void main(String[] args) throws Exception {
//ObjectMapper类用序列化与反序列化映射器
ObjectMapper mapper = new ObjectMapper();
File json = new File("country.json");
//当反序列化json时，未知属性会引起的反序列化被打断，这里我们禁用未知属性打断反序列化功能，
//因为，例如json里有10个属性，而我们的bean中只定义了2个属性，其它8个属性将被忽略
mapper.disable(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES);
//从json映射到java对象，得到country对象后就可以遍历查找,下面遍历部分内容，能说明问题就可以了
Country country = mapper.readValue(json, Country.class);
System.out.println("country_id:"+country.getCountry_id());
//设置时间格式，便于阅读
SimpleDateFormat dateformat = new SimpleDateFormat("yyyy-MM-dd");
String birthDate = dateformat.format(country.getBirthDate());
System.out.println("birthDate:"+birthDate);
List<Province> provinces = country.getProvinces();
for (Province province : provinces) {
System.out.println("province:"+province.name + "\n" + "population:"+province.population);
}
}
}
程序运行结果：
country_id:China birthDate:1949-10-01 province:Shanxi population:37751200 province:ZheJiang population:55080000
2.Tree Model处理Json
(1)tree model生成json:
package com.jackson.json.treemodel; import java.io.File; import java.io.FileWriter; import com.fasterxml.jackson.core.JsonFactory; import com.fasterxml.jackson.core.JsonGenerator; import com.fasterxml.jackson.databind.ObjectMapper; import com.fasterxml.jackson.databind.SerializationFeature; import com.fasterxml.jackson.databind.node.ArrayNode; import com.fasterxml.jackson.databind.node.JsonNodeFactory; import com.fasterxml.jackson.databind.node.ObjectNode; public class SerializationExampleTreeModel { public static void main(String[] args) throws Exception { //创建一个节点工厂,为我们提供所有节点 JsonNodeFactory factory = new JsonNodeFactory(false); //创建一个json factory来写tree modle为json JsonFactory jsonFactory = new JsonFactory(); //创建一个json生成器 JsonGenerator generator = jsonFactory.createGenerator(new FileWriter(new File("country2.json"))); //注意，默认情况下对象映射器不会指定根节点，下面设根节点为country ObjectMapper mapper = new ObjectMapper(); ObjectNode country = factory.objectNode(); country.put("country_id", "China"); country.put("birthDate", "1949-10-01"); //在Java中，List和Array转化为json后对应的格式符号都是"obj:[]" ArrayNode nation = factory.arrayNode(); nation.add("Han").add("Meng").add("Hui").add("WeiWuEr").add("Zang"); country.set("nation", nation); ArrayNode lakes = factory.arrayNode(); lakes.add("QingHai Lake").add("Poyang Lake").add("Dongting Lake").add("Taihu Lake"); country.set("lakes", lakes); ArrayNode provinces = factory.arrayNode(); ObjectNode province = factory.objectNode(); ObjectNode province2 = factory.objectNode(); province.put("name","Shanxi"); province.put("population", 37751200); province2.put("name","ZheJiang"); province2.put("population", 55080000); provinces.add(province).add(province2); country.set("provinces", provinces); ObjectNode traffic = factory.objectNode(); traffic.put("HighWay(KM)", 4240000); traffic.put("Train(KM)", 112000); country.set("traffic", traffic); mapper.configure(SerializationFeature.INDENT_OUTPUT, true); mapper.writeTree(generator, country); } }
程序运行生成country2.json,内容如下：
{"country_id":"China","birthDate":"1949-10-01","nation":["Han","Meng","Hui","WeiWuEr","Zang"],"lakes":["QingHai Lake","Poyang Lake","Dongting Lake","Taihu Lake"],"provinces":[{"name":"Shanxi","population":37751200},{"name":"ZheJiang","population":55080000}],"traffic":{"HighWay(KM)":4240000,"Train(KM)":112000}}
(2) json字符串反序列化为tree mode
DeserializationExampleTreeModel1.java,请注意观察程序中不同的JsonNode的类型变化
package com.jackson.json.treemodel; import java.io.File; import java.util.Iterator; import com.fasterxml.jackson.databind.JsonNode; import com.fasterxml.jackson.databind.ObjectMapper; public class DeserializationExampleTreeModel1 { public static void main(String[] args) throws Exception { ObjectMapper mapper = new ObjectMapper(); // Jackson提供一个树节点被称为"JsonNode",ObjectMapper提供方法来读json作为树的JsonNode根节点 JsonNode node = mapper.readTree(new File("country2.json")); // 看看根节点的类型 System.out.println("node JsonNodeType:"+node.getNodeType()); // 是不是一个容器 System.out.println("node is container Node ? "+node.isContainerNode()); // 得到所有node节点的子节点名称 System.out.println("---------得到所有node节点的子节点名称-------------------------"); Iterator<String> fieldNames = node.fieldNames(); while (fieldNames.hasNext()) { String fieldName = fieldNames.next(); System.out.print(fieldName+" "); } System.out.println("\n-----------------------------------------------------"); // as.Text的作用是有值返回值，无值返回空字符串 JsonNode country_id = node.get("country_id"); System.out.println("country_id:"+country_id.asText() + " JsonNodeType:"+country_id.getNodeType()); JsonNode birthDate = node.get("birthDate"); System.out.println("birthDate:"+birthDate.asText()+" JsonNodeType:"+birthDate.getNodeType()); JsonNode nation = node.get("nation"); System.out.println("nation:"+ nation+ " JsonNodeType:"+nation.getNodeType()); JsonNode lakes = node.get("lakes"); System.out.println("lakes:"+lakes+" JsonNodeType:"+lakes.getNodeType()); JsonNode provinces = node.get("provinces"); System.out.println("provinces JsonNodeType:"+provinces.getNodeType()); boolean flag = true; for (JsonNode provinceElements : provinces) { //为了避免provinceElements多次打印，用flag控制打印，能体现provinceElements的JsonNodeType就可以了 if(flag){ System.out.println("provinceElements JsonNodeType:"+provinceElements.getNodeType()); System.out.println("provinceElements is container node? "+provinceElements.isContainerNode()); flag = false; } Iterator<String> provinceElementFields = provinceElements.fieldNames(); while (provinceElementFields.hasNext()) { String fieldName = (String) provinceElementFields.next(); String province; if ("population".equals(fieldName)) { province = fieldName + ":" + provinceElements.get(fieldName).asInt(); }else{ province = fieldName + ":" + provinceElements.get(fieldName).asText(); } System.out.println(province); } } } }
程序运行后打印结果如下：
node JsonNodeType:OBJECT node is container Node ? true ---------得到所有node节点的子节点名称------------------------- country_id birthDate nation lakes provinces traffic ----------------------------------------------------- country_id:China JsonNodeType:STRING birthDate:1949-10-01 JsonNodeType:STRING nation:["Han","Meng","Hui","WeiWuEr","Zang"] JsonNodeType:ARRAY lakes:["QingHai Lake","Poyang Lake","Dongting Lake","Taihu Lake"] JsonNodeType:ARRAY provinces JsonNodeType:ARRAY provinceElements JsonNodeType:OBJECT provinceElements is container node? true name:Shanxi population:37751200 name:ZheJiang population:55080000
在来看一下DeserializationExampleTreeModel2.java,本例中使用JsonNode.path的方法，path方法类似于DeserializationExampleTreeModel1.java中使用的get方法，
但当node不存在时,get方法返回null,而path返回MISSING类型的JsonNode
package com.jackson.json.treemodel; import java.io.File; import java.io.IOException; import java.util.Iterator; import com.fasterxml.jackson.core.JsonProcessingException; import com.fasterxml.jackson.databind.JsonNode; import com.fasterxml.jackson.databind.ObjectMapper; public class DeserializationExampleTreeModle2 { public static void main(String[] args) throws JsonProcessingException, IOException{ ObjectMapper mapper = new ObjectMapper(); JsonNode node = mapper.readTree(new File("country2.json")); //path方法获取JsonNode时，当对象不存在时，返回MISSING类型的JsonNode JsonNode missingNode = node.path("test"); if(missingNode.isMissingNode()){ System.out.println("JsonNodeType : " + missingNode.getNodeType()); } System.out.println("country_id:"+node.path("country_id").asText()); JsonNode provinces = node.path("provinces"); for (JsonNode provinceElements : provinces) { Iterator<String> provincesFields = provinceElements.fieldNames(); while (provincesFields.hasNext()) { String fieldName = (String) provincesFields.next(); String province; if("name".equals(fieldName)){ province = fieldName +":"+ provinceElements.path(fieldName).asText(); }else{ province = fieldName +":"+ provinceElements.path(fieldName).asInt(); } System.out.println(province); } } } }
程序运行打印结果：
JsonNodeType : MISSING country_id:China name:Shanxi population:37751200 name:ZheJiang population:55080000
3.Stream处理Json
(1)stream生成json
package com.jackson.json.streaming; import java.io.File; import java.io.FileWriter; import java.io.Exception; import com.fasterxml.jackson.core.JsonFactory; import com.fasterxml.jackson.core.JsonGenerator; public class StreamGeneratorJson { public static void main(String[] args) throws Exception { JsonFactory factory = new JsonFactory(); //从JsonFactory创建一个JsonGenerator生成器的实例 JsonGenerator generator = factory.createGenerator(new FileWriter(new File("country3.json"))); generator.writeStartObject(); generator.writeFieldName("country_id"); generator.writeString("China"); generator.writeFieldName("provinces"); generator.writeStartArray(); generator.writeStartObject(); generator.writeStringField("name", "Shanxi"); generator.writeNumberField("population", 33750000); generator.writeEndObject(); generator.writeEndArray(); generator.writeEndObject(); generator.close(); } }
程序运行后生成country3.json文件内容：
{"country_id":"China","provinces":[{"name":"Shanxi","population":33750000}]}
(2)stream解析json:
现在adgcountry3.json，我们用Streaming API的方式来解析上面的Json,并查找json中population的值。
package com.jackson.json.streaming; import java.io.File; import java.io.IOException; import com.fasterxml.jackson.core.JsonFactory; import com.fasterxml.jackson.core.JsonParseException; import com.fasterxml.jackson.core.JsonParser; import com.fasterxml.jackson.core.JsonToken; /*Jackson API提供了token对每个Json对象，例如，Json开始符号“{”是token指向的第一个解析的对象， key:value键值对是另一个单独的对象。这个API很强大，但也需要编写大量代码。不推荐使用，平时更多的是使用DataBinding和TreeModel来处理json */ public class StreamParserJson { public static void main(String[] args) throws JsonParseException, IOException { JsonFactory factory = new JsonFactory(); // 从JsonFactory创建JsonParser解析器的实例 JsonParser parser = factory.createParser(new File("country3.json")); while (!parser.isClosed()) { // 得到一个token,第一次遍历时，token指向json文件中第一个符号"{" JsonToken token = parser.nextToken(); if (token == null) { break; } // 我们只查找 country3.json中的"population"字段的值，能体现解析的流程就可以了 // 当key是provinces时，我们进入provinces,查找population if (JsonToken.FIELD_NAME.equals(token) && "provinces".equals(parser.getCurrentName())) { token = parser.nextToken(); if (!JsonToken.START_ARRAY.equals(token)) { break; } // 此时，token指向的应该是"{" token = parser.nextToken(); if (!JsonToken.START_OBJECT.equals(token)) { break; } while (true) { token = parser.nextToken(); if (token == null) { break; } if (JsonToken.FIELD_NAME.equals(token) && "population".equals(parser.getCurrentName())) { token = parser.nextToken(); System.out.println(parser.getCurrentName() + " : " + parser.getIntValue()); } } } } } }
程序运行后，在控制台打印结果如下：
population : 33750000
总结
上面的例子中，分别用3种方式处理Json，我的体会大致如下：
Stream API方式是开销最低、效率最高，但编写代码复杂度也最高，在生成Json时，需要逐步编写符号和字段拼接json,在解析Json时，需要根据token指向也查找json值，生成和解析json都不是很方便，代码可读性也很低。
Databinding处理Json是最常用的json处理方式，生成json时，创建相关的java对象，并根据json内容结构把java对象组装起来，最后调用writeValue方法即可生成json,
解析时，就更简单了，直接把json映射到相关的java对象，然后就可以遍历java对象来获取值了。
TreeModel处理Json，是以树型结构来生成和解析json，生成json时，根据json内容结构，我们创建不同类型的节点对象，组装这些节点生成json。解析json时，它不需要绑定json到java bean，根据json结构，使用path或get方法轻松查找内容。
学习参考：http://www.cnblogs.com/lee0oo0/articles/2652528.html
转载来源：http://blog.csdn.net/java_huashan/article/details/46375857
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