注解： 这是对《Learning Play! Framework 2》第三章的学习
本章是一个显示聊天记录的项目，只有一个页面，可以自动对聊天记录进行排序、分组和显示，并整合使用了less，其界面显示如下
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" alt="" width="510" height="425" />
一、项目结构
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" alt="" />
二、项目中使用的模型
所有的聊天记录放在models目录中Chat类中
public class Chat {
public DateTime date; // chat time
public int occurrence; // chat room
public List<Item> items; //chat content
public Chat(DateTime date, int occurrence, List<Item> items) {
this.date = date;
this.occurrence = occurrence;
this.items = items;
}
}
每一次的聊天记录的内容放在models目录中Item类中
public class Item {
public String user;
public LocalTime timestamp;
public String message;
public Item(String user, LocalTime timestampLocalTime, String message) {
this.user = user;
this.timestamp = timestampLocalTime;
this.message = message;
}
}
三、项目route
本项目只有一个页面，所有不用修改默认的route
四、项目模板
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4.1 index.scala.html模板
@(message: String)(chats:List[Chat])
@import models.Item
@import java.util.List @main("Welcome to the Packt Publishing's Play 2.0 Demo") {
<h1>@message</h1>
@chats.sortBy(_.occurrence).groupBy(_.date.toDate).toSeq.sortBy(_._1).map { dateAndChats =>
<h3>-- Chat @dateAndChats._1 --</h3>
@dateAndChats._2.map { chat =>
@listContainer{ //引用listContainer模板
<h3>-- Chat #@chat.occurrence --</h3>
}(chat) {
<hr/>
}
}
}
}
说明： 引用listContainer模板方法说明
@listContainer{
<h3>-- Chat #@chat.occurrence --</h3>
}(chat) {
<hr/>
}
- <h3>是在listContainer模板前面加入的内容
- (chat)是在listContainer模板的参数
- <hr/>是在listContainer模板前面后面的内容
- 聊天内容的分组、排序
@chats.sortBy(_.occurrence).groupBy(_.date.toDate).toSeq.sortBy(_._1).map{ dateAndChats =>这里定义了一个变量dateAndChats，该变量已经分组（按聊天室编号occurrence）和排序（按日期date）好了。
4.2 listContainer.scala.html模板
@(header:Html)(chat:Chat)(footer:Html)
@import models.Chat
<div style="margin-left:@{5*chat.occurrence}%">
@header
<ul>
@chat.items.map { item =>
@listItem(item) //引用listItem模板
}
</ul>
@footer
</div>
4.3 listItem.scala.html模板
@(item:Item)
@import models.Item
<style>
li.item span{ width:100px;display:inline-block;}
</style>
<li class="item">
<span>@item.user</span>
<span>[@item.timestamp]</span>@item.message
</li>
五、controller
本例比较简单，只有一个controller，在controllers目录中Application类
public class Application extends Controller {
public static Result index() {
DateTime today = DateTime.now();
DateTime yesterday = today.minus(Days.ONE);
//模拟数据
Chat chat11 = new Chat(yesterday, 1, asList(
new Item("me", LocalTime.now(), "Hello!"),
new Item("other", LocalTime.now(), "Hi!"),
new Item("me", LocalTime.now(), "Fine?"),
new Item("other", LocalTime.now(), "Yes")
));
Chat chat12 = new Chat(yesterday, 2, asList(
new Item("me", LocalTime.now(), "It's hot today!"),
new Item("other", LocalTime.now(), "Indeed...")
));
Chat chat21 = new Chat(today, 1, asList(
new Item("me", LocalTime.now(), "Hello!"),
new Item("me", LocalTime.now(), "Youhou?"),
new Item("no-one", LocalTime.now(), "...")
));
Chat chat22 = new Chat(today, 2, asList(
new Item("me", LocalTime.now(), "Ding ding!"),
new Item("me", LocalTime.now(), "Poueeeeeeeeeet?"),
new Item("no-one", LocalTime.now(), "...")
));
Chat chat23 = new Chat(today, 3, asList(
new Item("me", LocalTime.now(), "No one?"),
new Item("no-one", LocalTime.now(), "Yes?")
));
return ok(index.render("It Works!", asList(chat23, chat11, chat21, chat12, chat22)));
}
}
在该controller中，我们模拟了一些数据（没有使用数据库），调用index模板，并将模拟的数据传给该模板。
六、使用less美化页面
- 在app/assets目录中增加book-utils.less和book.less文件
- main.scala.html模板中加入
link rel="stylesheet" media="screen" href="@routes.Assets.at("stylesheets/book.css")">
本例中使用了两个less文件，均放入public --> sytlesheets 目录中
- book-utils.less——定义全局的变量和mixin
- book.less ——
其中book-utils.less
//VARs
@bgColor: darken(#CCC, 25%);
@baseColor: lighten(#122, 5%);
//MIXINS
.border-radius (@radius: 5px) {
border-radius: @radius;
-moz-border-radius: @radius;
-webkit-border-radius: @radius;
}
.box-shadow (@x: 0, @y: 0, @blur: 1px, @color: #000) {
box-shadow: @arguments;
-moz-box-shadow: @arguments;
-webkit-box-shadow: @arguments;
}
book.less
@import "book-utils.less";
body {
width: 960px;
margin: auto;
background-color: desaturate(lighten(@bgColor, 25%), 65%);
border: 2px @bgColor solid;
.border-radius;
padding: 0px 15px;
}
h1 { color: saturate(@baseColor, 25%);}
.date {
h2 {
border: 1px black dotted;
.border-radius(100px);
color: @baseColor;
}
.chat {
.box-shadow(-2px, -3px, 2px, fade(spin(@bgColor, 15%), 30%));
h3 {
border: 1px black solid;
.border-radius;
color: @baseColor
}
li.item span {
width: 100px;
display:inline-block;:first-child { color: lighten(@baseColor, 15%); }
.time { color: saturate(@baseColor, 85%) }
}
}
}