How to implement asynchronous loading in HTML5+JS+JQuery+ECharts

This article mainly introduces the asynchronous loading problem of HTML5 JS JQuery ECharts. Friends who need it can refer to it

In the past few days, I looked at the API and Demo of ECharts official website and found it very interesting, so I used The data generated by the model prediction is displayed as a pseudo-real-time dynamic data.

First, create an index.html file. I open it with vscode and write it.

1. Insert a tag

<p id="main" style="width:600px;height:400px;"></p>

to set some of his styles (you can beautify it yourself, I am lazy!!!).

2. Create a 3f1c4e4b6b16bbbd69b2ee476dc4f83a script under the body (Why write a js script under the body? Because this is to improve the user experience and you can go deep into Baidu~~~).

3. What to write in the script? Don’t worry, take your time~~

(1) First, let’s build an echarts object, let’s call it MyChart

 var myChart = echarts.init(document.getElementById('main'));

(2) Create a setoption. This is the initialization diagram Yes, fill in some basic parameters (you can fly to the Echarts official website through this link for configuration reference)

(3) After initialization, we can read local files asynchronously with ajax~~~~

Among them, those who don’t understand the stack (the link here is from my Google, it may be blocked~~) and those who don’t understand push and shift to operate data (the link here should not be blocked~~)

$.ajax({
    type:"get",
    // async:true,
    url:"test_data.json",
    data:{},
    dataType:"json",
    success:function(result){
      var datas=result
      if(result){
        var m=0;
        for(var i=0;i<result.length;i++){ 
          if(m<1000){
            datas.shift();      
            date.push(result[i]["time"]);
            data.push(result[i]["AM23SIG0206.AV"]);
            m+=1;
          }
          else{       
            break;
          }
        myChart.hideLoading();
        setInterval(function(){
          for(var n=0;n<2;n++){
            date.shift();
            date.push(datas[n]["time"]);
            data.shift();
            data.push(datas[n]["AM23SIG0206.AV"]);
          }                         
          myChart.setOption({
          xAxis:{
            data:date
          },
          series:[
            {
              name:"参数",
              data:data
            }
          ]});
          for(var nn=0;nn<2;nn++){
            datas.shift()
            }
          },2000);
        }
      }
    },
    error:function(errorMsg){
      alert("图表请求数据失败！");
      myChart.hideLoading();
      myChart_2.hideLoading();
    }
  })

Let me explain, the principle of this asynchronous loading is like this:

(1) We now load a .json file, which is stored in a variable result, and start to operate the data, using the stack The concept is to first store the amount of data to be displayed on a graph, assuming it is 1000 points, and store it in data (this is a queue). If you want to achieve dynamic real-time data, it will move when you look at the data~~~~You need Save a piece of data, but the queue only has a capacity of 1,000. What if you can’t fit it in? It doesn’t matter. You can just take one out first, and the cycle will continue like this~~~~

(2) But ah , it is too troublesome to take one and save one. We are setting a timer setInterval() in this to update 2 points every 2 seconds (how to update, it is data.shift()

data.push( )

Simulating the stack~~~~

This way we can achieve dynamic data~~~~

Okay, if it’s just like this, it’s too low, I want Realize the movement of real data in the front end of a framework database~~~~Let me study for a few days~~~~~~

Okay, no more nonsense, here is the source code, if you need it, you can run it yourself Give it a try and see if you can move~~~~~

  
  
  
  


  <p id="main" style="width:600px;height:400px;"></p>
  

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    "time": "2016-05-01 00:08:01"
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    "time": "2016-05-01 00:08:07"
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    "time": "2016-05-01 00:08:10"
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    "time": "2016-05-01 00:08:13"
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    "time": "2016-05-01 00:08:16"
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    "time": "2016-05-01 00:08:19"
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    "AM23SIG0206.AV": "593.5944",
    "time": "2016-05-01 00:08:22"
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    "AM23SIG0206.AV": "593.5944",
    "time": "2016-05-01 00:08:25"
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    "time": "2016-05-01 00:08:28"
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    "time": "2016-05-01 00:08:40"
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    "time": "2016-05-01 00:08:49"
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    "time": "2016-05-01 00:10:07"
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    "time": "2016-05-01 00:10:19"
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    "time": "2016-05-01 00:10:22"
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    "AM23SIG0206.AV": "593.297",
    "time": "2016-05-01 00:10:31"
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    "AM23SIG0206.AV": "593.297",
    "time": "2016-05-01 00:10:34"
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    "AM23SIG0206.AV": "593.3293",
    "time": "2016-05-01 00:10:37"
  },
  {
    "AM23SIG0206.AV": "593.3131",
    "time": "2016-05-01 00:10:40"
  },
  {
    "AM23SIG0206.AV": "593.3293",
    "time": "2016-05-01 00:10:43"
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  {
    "AM23SIG0206.AV": "593.3293",
    "time": "2016-05-01 00:10:46"
  }
]

The above is what I compiled for everyone. I hope it will be helpful to everyone in the future.

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