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In modern data visualization applications, dynamically updating charts is a very important feature that allows users to view data changes in real-time without refreshing the entire page. In Dash, the core mechanism for dynamically updating charts is **Callback**, which allows you to dynamically update chart content when users interact with the page (such as clicking buttons, selecting dropdown menus, etc.). ### Basic Structure of Callback A typical callback consists of the following parts: 1. **Input**: Defines the component and its property that triggers the callback. 2. **Output**: Defines the component and its property that needs to be updated. 3. **Callback Body**: Calculates and returns the output value based on the input value. For detailed explanation of Dash callbacks, see: [ ### Simple Dynamically Update Chart Through callbacks, you can dynamically update the data and layout of charts. The following is a complete Dash application example, where users can select a dataset through a dropdown menu to dynamically display the corresponding line chart: ## Example from dash import Dash, html, dcc, Input, Output import plotly.express as px import pandas as pd # Create Dash app app = Dash( __name__ ) # Define sample datasets datasets ={ 'Dataset1': pd.DataFrame({ 'x': [1,2,3,4,5], 'y': [10,15,13,17,21] }), 'Dataset2': pd.DataFrame({ 'x': [1,2,3,4,5], 'y': [5,10,8,12,15] }), 'Dataset3': pd.DataFrame({ 'x': [1,2,3,4,5], 'y': [20,18,22,19,25] }) } # Define layout app.layout= html.Div([ html.H1("Dynamic Line Chart Example"),# Title dcc.Dropdown( id='dataset-dropdown',# Dropdown ID options=[{'label': name,'value': name}for name in datasets.keys()],# Dropdown options value='Dataset1'# Default selected dataset ), dcc.Graph(id='line-chart')# Graph component for displaying line chart ]) # Define callback @app.callback( Output('line-chart','figure'),# Output to figure property of Graph component with id 'line-chart' Input('dataset-dropdown','value')# Input from value property of dropdown with id 'dataset-dropdown' ) def update_line_chart(selected_dataset): # Get selected dataset df = datasets # Create line chart using Plotly Express fig = px.line(df, x='x', y='y', title=f'{selected_dataset} Line Chart') return fig # Run app if __name__ =='__main__': app.run_server(debug=True)# Start app, debug=True means enable debug mode The display is as follows: !(#) ### Code Analysis **1. Layout section**: * Use `html.H1` to create a title "Calculate Square". * Use `dcc.Input` to create a number input box, with `id` as 'number-input', type as 'number'. * Use `html.Div` to create an area for displaying results, with `id` as 'output'. **2. Callback**: * Use `@app.callback` decorator to define the callback. * Input is the `value` property of the 'number-input' input box. * Output is the `children` property of the 'output' Div. * In the callback: * Check if the input is empty. * Convert the input to a float and calculate the square. * Return the formatted result. **4. Run the app**: * Use `app.run_server(debug=True)` to start the app, `debug=True` means enable debug mode.