问题描述：后台需要传递给前台一些数据，用于页面数据显示，因为是一些Lable标签，所以数据传递到前台需要解析。

思路：因为数据比较杂乱，所以我选择传递的数据类型是Json格式，但是数据展示时需要解析成单个的字符串，赋值给Lable标签

一、JSON字符串解析

Json格式字符串（键/值）

{"lblTime":"2016-11-04 14:15:26","lblArea":"B包头地区（新）","lblTelevisionLogStoreName":"","lblRecordCount":""}

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KADEBVAJABqAoAMgBVAUAGoCoAyABUBQAZgKoAIANQFQBkwP8BDF3sYVhdBzoAAAAASUVORK5CYII=" alt="" />

主要用函数eval对json格式字符串进行反序列化操作,然后获取节点对应的值

  var obj = eval("(" + result + ")");//eval函数对json格式字符串进行反序列化

  document.getElementById("lblTime").innerText = obj["lblTime"];//obj["lblTime"]获取值

  document.getElementById("lblArea").innerText = obj["lblArea"];

  document.getElementById("lblTelevisionLogStoreName").innerText = obj["lblTelevisionLogStoreName"];

  document.getElementById("lblRecordCount").innerText = obj["lblRecordCount"];

二、JSON字符串解析

Json格式字符串（键/[]）,这种是一个键对应一个数组

{"Category":[{"categoryId":,"categoryName":"饮品","categoryImage":"/upload/yinpin.jpg"},{"categoryId":,"categoryName":"食品","categoryImage":"/upload/shiping.jpg"},{"categoryId":,"categoryName":"酒类","categoryImage":"/upload/jiullei.jpg"}]}

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" alt="" />

数据取值：

var result = eval("(" + result + ")");
result.Category[].categoryId;

result.Category[].categoryName;

result.Category[].categoryImage;

result.Category[].categoryId;

result.Category[].categoryName;

result.Category[].categoryImage;

result.Category[].categoryId;

result.Category[].categoryName;

result.Category[].categoryImage;

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