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How to use Layui to implement drag-and-drop data visualization dashboard function

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Release: 2023-10-26 11:27:24
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How to use Layui to implement drag-and-drop data visualization dashboard function

How to use Layui to implement drag-and-drop data visualization dashboard function

Introduction:
Data visualization is increasingly used in modern life, and Dashboard development is an important part of this. This article mainly introduces how to use the Layui framework to implement a drag-and-drop data visualization dashboard function, allowing users to flexibly customize their own data display modules.

1. Preparation

  1. Download the Layui framework
    First, we need to download and configure the Layui framework. You can find related download and configuration tutorials on Layui's official website (https://www.layui.com/).
  2. Introduce related library files
    Introduce Layui related library files in the HTML file, as shown below:

    <link rel="stylesheet" href="path/to/layui/css/layui.css">
    <script src="path/to/layui/layui.js"></script>
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2. Implement drag and drop function

  1. Create HTML container
    Create a container in the HTML file to host the content of the dashboard.

    <div id="dashboard"></div>
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  2. Set the dashboard style
    Set the style of the dashboard in the CSS style file, which can be adjusted according to actual needs. Here is an example:

    #dashboard {
      width: 1000px;
      height: 600px;
      border: 1px solid #ccc;
    }
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  3. Use Layui's laytpl module to render the dashboard
    Use Layui's laytpl module in a JavaScript file to render the content of the dashboard through the template engine. First introduce the laytpl library file into the HTML file:

    <script src="path/to/layui/lay/modules/laytpl.js"></script>
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    Then, we can use the following code to render the content of the dashboard:

    layui.use(['laytpl'], function(){
      var laytpl = layui.laytpl;
      
      // 定义仪表盘的数据
      var data = [
     {name: '模块1', x: 0, y: 0, width: 200, height: 200},
     {name: '模块2', x: 300, y: 0, width: 300, height: 200},
     // 其他模块的定义...
      ];
    
      // 渲染仪表盘的模板
      var getTpl = dashboard.tpl;
      laytpl(getTpl).render(data, function(html){
     // 将渲染后的模板插入到HTML容器中
     document.getElementById('dashboard').innerHTML = html;
      });
    });
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  4. Write the dashboard template
    Define the template of the dashboard in a JavaScript file. Different modules can be rendered in the template according to different data to achieve flexible customization. The following is an example:

    dashboard.tpl = `
    {{# layui.each(d, function(index, item){ }}
      <div class="module" style="position:absolute; left:{{item.x}}px; top:{{item.y}}px; width:{{item.width}}px; height:{{item.height}}px;">
     {{item.name}}
      </div>
    {{# }); }}
    `;
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  5. Implementing the drag and drop function
    In order to realize the drag and drop function, we need to introduce the draggable module of Layui. First, introduce the draggable library file in the HTML file:

    <script src="path/to/layui/lay/modules/draggable.js"></script>
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    Then, use the draggable module in the JavaScript file, as shown below:

    layui.use(['draggable'], function(){
      var draggable = layui.draggable;
    
      // 获取仪表盘容器
      var dashboardElement = document.getElementById('dashboard');
    
      // 启用拖拽功能
      draggable.set({
     elem: dashboardElement,
     target: '.module' // 可拖拽的目标元素
      });
    });
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So far, we have Completed all the steps to implement drag-and-drop data visualization dashboard function using Layui. Users can adjust the layout of the dashboard by dragging and dropping modules to display different data according to their needs.

Summary:
This article introduces how to use the Layui framework to implement a drag-and-drop data visualization dashboard function. Through Layui's laytpl module and draggable module, we can flexibly customize the layout of the dashboard and implement the drag and drop function. I hope this article can help readers better understand and use the Layui framework and improve the efficiency and quality of data visualization development.

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