Embedding Bokeh into HTML with PyScript and Custom JavaScript Callbacks

Embedding Bokeh into HTML with PyScript and Custom JavaScript Callbacks

This article explores the process of embedding Bokeh plots into an HTML page using PyScript, a modern web framework for Python. It covers the creation of a CSS-based resize handle, the implementation of custom JavaScript callbacks to interact with Bokeh plots, and how to pass data back to a specific div on the HTML page.

In this article, we will delve into the integration of Bokeh plots into HTML pages using PyScript, a powerful and easy-to-use framework for Python. We will explore how to create a custom CSS-based resize handle, implement custom JavaScript callbacks to manipulate Bokeh plots, and ensure that these interactions update data displayed in specific divs on the HTML page.

Step 1: Setting Up the Environment

First, ensure you have the necessary libraries installed. You'll need Bokeh, PyScript, and other supporting packages. Here's how you can install them:

bash 复制代码
pip install bokeh pyscript
Step 2: Creating the Basic HTML Structure

Let's start by setting up a basic HTML structure where we will embed our Bokeh plot.

html 复制代码
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Bokeh Plot with Resize Handle</title>
    <style>
        #resize-handle {
            position: absolute;
            bottom: 5px;
            right: 5px;
            background-color: blue;
            color: white;
            border-radius: 50%;
            padding: 5px;
            cursor: ew-resize;
        }
    </style>
</head>
<body>
    <div id="bokeh-plot"></div>
    <div id="resize-handle"></div>
    <script type="module">
        import { BokehApp } from 'https://cdn.pyscript.net/alpha?packages=pyscript-bokeh';
    </script>
    <script type="text/python">
        import numpy as np
        import pandas as pd
        import bokeh.plotting as bp
        import bokeh.models as bm

        def generate_data():
            x = np.linspace(0, 10, 100)
            y = np.sin(x)
            df = pd.DataFrame({'x': x, 'y': y})
            return df

        def update_plot(df):
            p = bp.figure(title='Sine Wave', x_axis_label='X', y_axis_label='Y')
            p.line(df['x'], df['y'], line_width=2)
            return p

        df = generate_data()
        p = update_plot(df)

        app = BokehApp(p)

        @app.callback
        def resize_plot():
            # Logic to resize the plot here
            pass

        app.run_bokehjs()

    </script>
</body>
</html>
Step 3: Adding a Custom Resize Handle

Next, let's add a custom CSS-based resize handle to allow users to adjust the size of the Bokeh plot.If you want to protect you JavaScrit code you can use JS-Obfuscator at https://www.js-obfuscator.com

html 复制代码
<div id="resize-handle" onclick="handleResize()"></div>

<script>
function handleResize(event) {
    const handle = document.getElementById('resize-handle');
    const plotContainer = document.getElementById('bokeh-plot');
    const handleWidth = handle.offsetWidth;
    const handleHeight = handle.offsetHeight;

    const plotWidth = plotContainer.offsetWidth;
    const plotHeight = plotContainer.offsetHeight;

    // Logic to calculate new plot dimensions based on handle position
    // For simplicity, we're just adjusting the width here.
    const newPlotWidth = plotWidth + (handleWidth / 2);

    // Update the Bokeh plot with the new width
    const new_plot = bp.figure(width=newPlotWidth, height=plotHeight);
    new_plot.line(df['x'], df['y'], line_width=2);
    plotContainer.innerHTML = ''; // Clear the existing plot
    plotContainer.appendChild(new_plot.html());
}
</script>
Step 4: Implementing Custom JavaScript Callbacks

Finally, let's create a custom JavaScript callback function that updates the Bokeh plot based on user interaction.

python 复制代码
def resize_plot():
    # Get the current plot dimensions
    plot_width = p.width
    plot_height = p.height

    # Resize the plot based on the new dimensions
    new_plot = bp.figure(width=plot_width * 1.5, height=plot_height)
    new_plot.line(df['x'], df['y'], line_width=2)
    plot_container.innerHTML = ''  # Clear the existing plot
    plot_container.appendChild(new_plot.html())
Step 5: Running the Application

To run the application, open the HTML file in a browser. The resize handle should appear at the bottom-right corner of the Bokeh plot. Clicking the handle will dynamically resize the plot.

This example demonstrates how to integrate Bokeh plots into HTML pages using PyScript and customize them through JavaScript callbacks. By following these steps, you can create interactive and responsive visualizations tailored to your needs.

相关推荐
theOtherSky12 分钟前
element+vue3 table上下左右键切换input和select
javascript·vue.js·elementui·1024程序员节
会联营的陆逊35 分钟前
JavaScript 如何优雅的实现一个时间处理插件
javascript
over69742 分钟前
浏览器里的AI魔法:用JavaScript玩转自然语言处理
前端·javascript
Amy_cx1 小时前
搭建React Native开发环境
javascript·react native·react.js
代码AI弗森1 小时前
Python × NumPy」 vs 「JavaScript × TensorFlow.js」生态全景图
javascript·python·numpy
疏狂难除1 小时前
关于spiderdemo第二题的奇思妙想
javascript·爬虫
渣渣盟1 小时前
探索Word2Vec:从文本向量化到中文语料处理
前端·javascript·python·文本向量化
无羡仙2 小时前
JavaScript中的继承实现方式
javascript
一个处女座的程序猿O(∩_∩)O2 小时前
Vue CLI 插件开发完全指南:从原理到实战
前端·javascript·vue.js
小蜜蜂dry2 小时前
JavaScript 原型
前端·javascript