js如何比较两个日期之间相差数（天、时、分、秒）
首先，我们模拟一个例子
引入js文件
<script type="text/javascript" src="jquery.min.js"></script>
html页面如下：
<body>
<div>
请输入第一个日期：<input type="date" id="Date1" /> <br/>
请输入第二个日期：<input type="date" id="Date2" /> <br/>
请输入日期相差数： <input type="text" id="differ" />(参数：1：相差天数，2：相差小时数，3：相差分钟数，4：相差毫秒数) <br/>
<input type="button" value="调用测试" onclick="TestClick()" />
</div>
</body>
js中的方法如下：
<script>
//获取当前日期
var getNowDate = function () {
var d = new Date();
var year = d.getFullYear();
var month = d.getMonth() + 1;
var day = d.getDate();
var dateStr = year + '-' + getFormatDate(month) + '-' + getFormatDate(day);
return dateStr;
} //格式化日期的月份或天数的显示（小于10，在前面增加0）
function getFormatDate(value) {
var result;
result = value < 10 ? ("0" + value) : value;
return result;
} //获取与毫秒数的转化比例（相差天数：1，相差小时数：2，相差分钟数：3，相差秒数：4）
var getDifferScale = function (value) {
var format;
//获取转化比（天数跟毫秒数的比例）
if (value == 1) {
format = parseFloat(24 * 60 * 60 * 1000);
}
//获取转化比（小时数跟毫秒数的比例）
else if (value == 2) {
format = parseFloat(60 * 60 * 1000);
}
//获取转化比（分钟数跟毫秒数的比例）
else if (value == 3) {
format = parseFloat(60 * 1000);
}
//获取转化比（秒数跟毫秒数的比例）
else if (value == 4) {
format = parseFloat(1000);
}
return format;
} //获取两个日期的相差日期数(differ 相差天数：1、相差小时数：2、相差分钟数：3、相差秒数：4)
var getDifferDate = function (firstDate, secondDate, differ) {
//1)将两个日期字符串转化为日期对象
var startDate = new Date(firstDate);
var endDate = new Date(secondDate);
//2)计算两个日期相差的毫秒数
var msecNum = endDate.getTime() - startDate.getTime();
//3)计算两个日期相差的天数
var dayNum = Math.floor(msecNum /getDifferScale(differ));
return dayNum;
} //测试方法
var TestClick = function(){
var date1 = $("#Date1").val();
var date2 = $("#Date2").val();
var differ = $("#differ").val();
if(date1 == "" || date1==null){
alert("第一个日期不能为空");
}
else if(date2 == "" || date2==null){
alert("第二个日期不能为空");
}
else if(differ == "" || differ==null ){
alert("日期相差数不能为空");
}
var result = getDifferDate(date1,date2,differ);
console.log("输出结果："+ result);
} </script>
注：原先测试是测试日期和当前日期比较，所以有前面两个方法（获取当前日期和格式化日期）
运行结果如图：
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" alt="" width="680" height="115" />
调用输出结果：
aaarticlea/png;base64,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" alt="" width="631" height="149" />
Ps: 两个日期比较，重要的是他们之间转化率（天与毫秒的转化，时与毫秒的转化，..等）和计算方法
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