Python Flask和HTML：重定向json响应以显示在同一页面的底部，而不是在单独的页面上显示响应_Python_Html_Python 3.x_Flask_Response

Python Flask和HTML：重定向json响应以显示在同一页面的底部，而不是在单独的页面上显示响应

python html python-3.x flask

Python Flask和HTML：重定向json响应以显示在同一页面的底部，而不是在单独的页面上显示响应,python,html,python-3.x,flask,response,Python,Html,Python 3.x,Flask,Response,网络开发的新概念。。我正在使用Flask部署一个sklearn机器学习模型我能够正确地将响应预测作为JSON返回，但它显示在单独的页面上。。我想修改我的HTML和Flaskapp.py，以使预测响应显示在HTML中表单底部新创建的容器元素中这是我的index.html <!DOCTYPE html> <html> <head> <meta name="viewport" content="width=device-width, initial-s

网络开发的新概念。。我正在使用Flask部署一个sklearn机器学习模型

我能够正确地将响应预测作为JSON返回，但它显示在单独的页面上。。我想修改我的HTML和Flask

app.py

，以使预测响应显示在HTML中

表单

底部新创建的容器元素中

这是我的

index.html

<!DOCTYPE html>
<html>
<head>
  <meta name="viewport" content="width=device-width, initial-scale=1">
  <link rel="stylesheet" href= "{{ url_for('static',filename='css/style.css') }}">


</head>
<body>
<div class = 'intro'>
  This is a simple website that hosts a Machine Learning model trained using <i>sklearn</i> to predict one of three authors:
  <b>HP Lovecraft</b>, <b>Edgar Allan Poe</b> and <b>Mary Shelley</b>. Simply enter a passage of one of those three authors and you will get a prediction.


</div>

<div class="authorimage">
  <div class="row">
  <div class="column">
    <h2>Mary Shelley</h2>
    <p><img src = "{{ url_for('static',filename='img/mary.jpeg') }}"></p>
  </div>
  <div class="column">
    <h2>H.P Lovecraft</h2>

    <p><img src = "{{ url_for('static',filename='img/lovecraft.jpeg') }}"></p>
  </div>
  <div class="column">
    <h2>Edgar Allan Poe</h2>
    <p><img src = "{{ url_for('static',filename='img/eap.jpeg') }}"></p>
  </div>
</div>


</div>


<div class = 'input'>
  <form action="/api" method="POST">
    <textarea name = "passage_input" cols="35" wrap="soft"></textarea>
    <input type="submit">
</form>
</div>


<div class = "prediction">
Not sure how to collect the response from app.py into a box here..
</div>

</body>
</html>

您可以在jinja中使用for以html格式解析json结果，如：

{% for key, value in results %}        
  <span>{{key}} : {{value}}</span>
{% endfor %}

您必须使用

jquery

动态更新页面：

<!DOCTYPE html>
<html>
<head>
 <meta name="viewport" content="width=device-width, initial-scale=1">
 <link rel="stylesheet" href= "{{ url_for('static',filename='css/style.css') }}">
 <script src="https://ajax.googleapis.com/ajax/libs/jquery/3.1.1/jquery.min.js"></script>
</head>
 <body>
   ...
 <div class = 'input_wrapper'>
    <textarea name = "passage_input" cols="35" wrap="soft" class="paragraph"></textarea>
    <button class='predict'>Predict</button>
 </form>
 </div>
<div class = "prediction"></div>
</body>
<script> 
$(document).ready(function(){
   $('.input_wrapper').on('click', '.predict', function(){
      var data = $('.paragraph').val();
      $.ajax({
       url: "/api",
      type: "get",
      data: {text:data},
      success: function(response) {
        $(".prediction").html(response.name);
       }
    });
   });
});
</script>
</html>

现在，当单击“预测”按钮时，javascript从

文本区域

获取输入的文本，并动态调用路由

'/api'

，并用结果更新

预测

div。

不确定为什么会有否决票。。

return render_template("index.html", results = your result)

<!DOCTYPE html>
<html>
<head>
 <meta name="viewport" content="width=device-width, initial-scale=1">
 <link rel="stylesheet" href= "{{ url_for('static',filename='css/style.css') }}">
 <script src="https://ajax.googleapis.com/ajax/libs/jquery/3.1.1/jquery.min.js"></script>
</head>
 <body>
   ...
 <div class = 'input_wrapper'>
    <textarea name = "passage_input" cols="35" wrap="soft" class="paragraph"></textarea>
    <button class='predict'>Predict</button>
 </form>
 </div>
<div class = "prediction"></div>
</body>
<script> 
$(document).ready(function(){
   $('.input_wrapper').on('click', '.predict', function(){
      var data = $('.paragraph').val();
      $.ajax({
       url: "/api",
      type: "get",
      data: {text:data},
      success: function(response) {
        $(".prediction").html(response.name);
       }
    });
   });
});
</script>
</html>

@app.route('/api')
def predict():
  text_input = request.args.get('text')
  return flask.jsonify({'name':parse(pd.Series([text_input]))})