在日常的编码中,经常会遇到JSON类型的数据,有简单的,也有复杂的。对于简单的,我们可以用正则等匹配,但是一旦遇到复杂的,就比较难办了。

数据分析

目前手头上需要制作一个天气预报功能,现成的接口已经有了。我随便输入一个城市,然后出现了如下的信息:

{"wdata":{"cityName":"鹤壁",
          "location":{"lat":"35.62",
                      "lng":"114.18"},
          "today":"2013-9-12 10:30:00",
          "sevDays":[{"date":"2013-9-12 20:00:00","Tmax":"28","weatherID":"02转01","windDir":"0","windPower":"0","Tmin":"18"},
                     {"date":"2013-9-13 20:00:00","Tmax":"33","weatherID":"00","windDir":"0","windPower":"0","Tmin":"18"},
                     {"date":"2013-9-14 20:00:00","Tmax":"35","weatherID":"00","windDir":"0","windPower":"0","Tmin":"19"},
                     {"date":"2013-9-15 20:00:00","Tmax":"27","weatherID":"01","windDir":"0","windPower":"0","Tmin":"16"},
                     {"date":"2013-9-16 20:00:00","Tmax":"25","weatherID":"01","windDir":"0","windPower":"0","Tmin":"17"},
                     {"date":"2013-9-17 20:00:00","Tmax":"26","weatherID":"02","windDir":"0","windPower":"0","Tmin":"18"},
                     {"date":"2013-9-18 20:00:00","Tmax":"27","weatherID":"02转07","windDir":"0","windPower":"0","Tmin":"16"}],
          "zhishu":[{"value":"2","name":"CY"},
                              {"value":"0","name":"ZS"},
                              {"value":"8","name":"FH"},
                              {"value":"2","name":"ZWX"},
                              {"value":"4","name":"KQWR"},
                              {"value":"2","name":"LY"},
                              {"value":"1","name":"JT"},
                              {"value":"1","name":"GM"},
                              {"value":"1","name":"SSD"}],
          "currentMessage":{"reportTime":"2013-9-12 13:00:00",
                                            "weatherID":"02",
                                            "temperature":"27",
                                            "windDir":"4",
                                            "windPower":"0",
                                            "humidity":"69.0",
                                            "visibility":"8",
                                            "pressure":"1012.2",
                                            "sunrise":"6:01",
                                            "sunset":"18:38"}
          }
}

这段JSON数据结构比一般的要复杂那么一点,不过从其结构来看:

第一层应该是wdata。

第二层是cityName(城市名称),location(经纬度),today(当前时间),sevDays(后续天气),zhishu(指数),currentMessage(当前预报信息)。

第三层是:location下面的lat,lng;sevDays下面的date,Tmax,weatherID,windDir,windPower,Tmin; 然后是zhishu下面的value 和 name;最后是currentMessage下面的reportTime,weatherID,temperature,windDir,windPower,humidity,visibility,pressure,sunrise,sunset信息:

所以,总共说来,这个JSON数据总共就三层。

解析方式

那么,如何来解析呢?

其实,我们完全可以从最底层的结构分析起来,然后简历相关的类,最后把这些建立的类组合成类似json数据的结构就可以了。

这里,最底层就是第三层,我们开始建立起相关的类对象:

对于sevDays下的项目, 建立如下类:

using System;

namespace Nxt.Common.Weather
{
   public  class DateReleation
    {
        //sevDays
        public DateTime date { get; set; }
        public int Tmax { get; set; }
        public string weatherID { get; set; }
        public int windDir { get; set; }
        public int windPower { get; set; }
        public int Tmin { get; set; }
    }
}

对于zhishu下的项目,建立的类如下:

namespace Nxt.Common.Weather
{
    public class IndexPoint
    {
        //zhishu
        public int value { get; set; }
        public string name { get; set; }
    }
}

对于currentMessage下的项目,建立的类如下:

using System;

namespace Nxt.Common.Weather
{
    public class CurrentMessage
    {
        //currentMessage
        public DateTime reportTime { get; set; }
        public string weatherID {get;set;}
        public double temperature { get; set; }
        public string windDir { get; set; }
        public string windPower { get; set; }
        public double humidity { get; set; }
        public string visibility { get; set; }
        public double pressure { get; set; }
        public string sunrise { get; set; }
        public string sunset { get; set; }
    }
}

对于location下面的项目,建立的类如下:

namespace Nxt.Common.Weather
{
   public  class Location
    {
        //location
        public string lat { get; set; }
        public string lng { get; set; }
    }
}

 

当第三层的都建立完毕后,现在来建立第二层,第二层的对象如上面所述,但是需要注意的是,sevDays,zhishu都是可以有多条记录的 ,所以我们得用List对象来保存。

using System;
using System.Collections.Generic;

namespace Nxt.Common.Weather
{
    public class WeatherMain
    {
        //wdata
        public string cityName { get; set; }
        public Location location { get; set; }
        public DateTime today { get; set; }
        public List<DateReleation> sevDays { get; set; }
        public List<IndexPoint> zhishu { get; set; }
        public CurrentMessage currentMessage { get; set; }

        public WeatherMain()
        {
            sevDays = new List<DateReleation>();
            zhishu = new List<IndexPoint>();
        }
    }
}

上面的代码是依据JSON数据的结构而建立的,这样能够最大程度避免数据的不准确性。
最后,建立顶层的类:

namespace Nxt.Common.Weather
{
    public class Daemon
    {
        public WeatherMain wdata { get; set; }
     }
}

这样,我们的类结构就建立完毕了。

最后审查一下我们建立的类结构,是不是和JSON数据的组织结构是一样的呢?

如果是一样的,让我们进入下一步:

using System;
using System.IO;
using System.Net;
using System.Web.Script.Serialization;
using Nxt.Common.Weather;
using System.Text;

namespace Nxt.Web.Code
{
    public class WeatherDaemon
    {
        public Daemon GetWeather(string areaName)
        {
            string url = "http://weather.****.net/Weather/getWeather.php?area=" + areaName;
            WebRequest request = WebRequest.Create(url);
            HttpWebResponse response = (HttpWebResponse)request.GetResponse();
            Stream dataStream = response.GetResponseStream();

            string weatherData = string.Empty;
            if (dataStream != null)
            {
                try
                {
                    using (StreamReader reader = new StreamReader(dataStream, Encoding.UTF8))
                    {
                        weatherData = reader.ReadToEnd();
                    }
                }
                catch (OutOfMemoryException oe)
                {
                    throw new Exception(oe.Data.ToString());
                }
                catch (IOException ie)
                {
                    throw new Exception(ie.Data.ToString());
                }
            }

            if (!String.IsNullOrEmpty(weatherData))
            {
                JavaScriptSerializer ser = new JavaScriptSerializer();
                Daemon main = ser.Deserialize<Daemon>(weatherData);
                return main;
            }
            return null;
        }
    }
}

请注意图中黄色部分,(使用JavaScriptSerializer,我们需要引用System.web.extensions.)
最后看看结果,我们是不是得到了想要的数据呢?

posted on 2013-09-12 17:18  程序诗人  阅读(13232)  评论(45编辑  收藏  举报