資訊專欄INFORMATION COLUMN
摘要：感冒指數(shù)易發(fā)感冒容易發(fā)生，少去人群密集的場所有利于降低感冒的幾率。穿衣指數(shù)舒適白天溫度適中，但早晚涼，易穿脫的便攜外套很實用。運動指數(shù)不適宜受到陣雨天氣的影響，不宜在戶外運動。
個人博客同步文章 https://mr-houzi.com/2018/06/...
根據(jù)一段天氣API來說一下JSONObject如何解析json數(shù)據(jù)，盡管現(xiàn)在在開發(fā)中使用Gson等，對于像我這樣初次使用Java做開發(fā)的小白，說一下也是好的。JSON數(shù)據(jù)
選取這段json數(shù)據(jù)是因為這段數(shù)據(jù)還是比較復雜的，能涵蓋要說的關鍵點
{
"data": {
"city": "深圳",
"temphigh": "25",
"templow": "19",
"updatetime": "2017-11-04 13:23:00",
"tempnow": "24",
"sendibletemp": "27",
"winddirect": "東北風",
"windpower": "2級",
"humidity": "42",
"sunrise": "06:29",
"sunset": "17:45",
"weather": "多云",
"week": "星期六",
"nl": null,
"date": "2017-11-04",
"index": [
{
"name": "化妝指數(shù)",
"level": "控油",
"msg": "建議用露質面霜打底，水質無油粉底霜，透明粉餅，粉質胭脂。"
},
{
"name": "感冒指數(shù)",
"level": "易發(fā)",
"msg": "感冒容易發(fā)生，少去人群密集的場所有利于降低感冒的幾率。"
},
{
"name": "洗車指數(shù)",
"level": "不宜",
"msg": "雨(雪)水和泥水會弄臟您的愛車，不適宜清洗車輛。"
},
{
"name": "穿衣指數(shù)",
"level": "舒適",
"msg": "白天溫度適中，但早晚涼，易穿脫的便攜外套很實用。"
},
{
"name": "紫外線強度指數(shù)",
"level": "弱",
"msg": "輻射較弱，涂擦SPF12-15、PA+護膚品。"
},
{
"name": "運動指數(shù)",
"level": "不適宜",
"msg": "受到陣雨天氣的影響，不宜在戶外運動。"
}
],
"pm25": {
"aqi": 0,
"co": 8,
"o3": 42,
"pm10": 63,
"pm2_5": 64,
"quality": "良",
"so2": 4,
"no2": 11,
"updatetime": "2017-11-04 13:00:00"
},
"daily": [
{
"date": "2017-11-04",
"week": "星期六",
"sunrise": "06:29",
"sunset": "17:45",
"temphigh": "25",
"templow": "19",
"weather": "多云"
},
{
"date": "2017-11-05",
"week": "星期日",
"sunrise": "06:29",
"sunset": "17:45",
"temphigh": "26",
"templow": "19",
"weather": "多云"
},
{
"date": "2017-11-06",
"week": "星期一",
"sunrise": "06:29",
"sunset": "17:45",
"temphigh": "27",
"templow": "20",
"weather": "多云"
},
{
"date": "2017-11-07",
"week": "星期二",
"sunrise": "06:29",
"sunset": "17:45",
"temphigh": "28",
"templow": "21",
"weather": "多云"
},
{
"date": "2017-11-08",
"week": "星期三",
"sunrise": "06:29",
"sunset": "17:45",
"temphigh": "29",
"templow": "22",
"weather": "多云"
},
{
"date": "2017-11-09",
"week": "星期四",
"sunrise": "06:29",
"sunset": "17:45",
"temphigh": "28",
"templow": "22",
"weather": "多云"
},
{
"date": "2017-11-03",
"week": "星期五",
"sunrise": "06:29",
"sunset": "17:45",
"temphigh": "28",
"templow": "18",
"weather": "晴"
}
]
},
"status": 0,
"msg": "ok"
}
解析JSON
利用JSONString進行簡單解析
我利用了RxVolley進行數(shù)據(jù)通信，t為API返回的數(shù)據(jù)
RxVolley.get("https://chkj02.market.alicloudapi.com/qgtq?city="+city, params, new HttpCallback() {
@Override
public void onSuccess(String t) {
Loger.debug("請求到的數(shù)據(jù):" + t);
}
});
我們現(xiàn)在要獲取這部分數(shù)據(jù)，該如何進行解析呢？
首先，將t中的數(shù)據(jù)傳到JSONObject類型的jsonObject中，再通過getJSONObject獲取到data下的數(shù)據(jù)。
//解析數(shù)據(jù)
JSONObject jsonObject = new JSONObject(t);
JSONObject jsonData = jsonObject.getJSONObject("data");
此時，jsonData中數(shù)據(jù)為
{
"city": "深圳",
"temphigh": "25",
"templow": "19",
"updatetime": "2017-11-04 13:23:00",
"tempnow": "24",
"sendibletemp": "27",
"winddirect": "東北風",
"windpower": "2級",
"humidity": "42",
"sunrise": "06:29",
"sunset": "17:45",
"weather": "多云",
"week": "星期六",
"nl": null,
"date": "2017-11-04"
}
然后通過getString進行讀值即可
//解析天氣
String jsonTemplow = jsonData.getString("templow");
String jsonTempHigh = jsonData.getString("temphigh");
String jsonWeather = jsonData.getString("weather");
String jsonTempnow = jsonData.getString("tempnow");
String jsonWinddirect = jsonData.getString("winddirect");
String jsonWindpower = jsonData.getString("windpower");
String jsonHumidity = jsonData.getString("humidity");
利用JSONArray進行復雜解析
這次，我們要獲取這部分數(shù)據(jù)
首先，將t中的數(shù)據(jù)傳到JSONObject類型的jsonObject中，再通過getJSONObject獲取到data下的數(shù)據(jù)。然后jsonArray通過getJSONArray獲得index下的數(shù)據(jù)
//解析數(shù)據(jù)
JSONObject jsonObject = new JSONObject(t);
JSONObject jsonData = jsonObject.getJSONObject("data");
JSONArray jsonIndex =jsonData.getJSONArray("index");
JSONArray jsonDaily =jsonData.getJSONArray("daily");
方法一
此時，jsonDaily中數(shù)據(jù)為
[
{
"date": "2017-11-04",
"week": "星期六",
"sunrise": "06:29",
"sunset": "17:45",
"temphigh": "25",
"templow": "19",
"weather": "多云"
},
{
"date": "2017-11-05",
"week": "星期日",
"sunrise": "06:29",
"sunset": "17:45",
"temphigh": "26",
"templow": "19",
"weather": "多云"
},
{
"date": "2017-11-06",
"week": "星期一",
"sunrise": "06:29",
"sunset": "17:45",
"temphigh": "27",
"templow": "20",
"weather": "多云"
},
{
"date": "2017-11-07",
"week": "星期二",
"sunrise": "06:29",
"sunset": "17:45",
"temphigh": "28",
"templow": "21",
"weather": "多云"
},
{
"date": "2017-11-08",
"week": "星期三",
"sunrise": "06:29",
"sunset": "17:45",
"temphigh": "29",
"templow": "22",
"weather": "多云"
},
{
"date": "2017-11-09",
"week": "星期四",
"sunrise": "06:29",
"sunset": "17:45",
"temphigh": "28",
"templow": "22",
"weather": "多云"
},
{
"date": "2017-11-03",
"week": "星期五",
"sunrise": "06:29",
"sunset": "17:45",
"temphigh": "28",
"templow": "18",
"weather": "晴"
}
]
把jsonDaily中按分類進行解析，分為幾個ArrayList<>,dates、weeks、weathers等，然后進行for循環(huán)。
