Before continuing, I recommend reading Part 1 and Part 2. Python Bokeh is a Data Visualization library that provides interactive charts and plots. With the above command, we created a virtual environment called interactiveplots and installed Python 3.9 along with several. Part 3 builds on the work covered in Part 1 and Part 2. The arguments to this function closely follow the ones for Bokehs. from flask import Flaskįrom flask import request, render_template, send_fileįrom bokeh. This is the third and final article in the Bokeh Interactive Plots series. Bokeh can help anyone who would like to quickly and easily make interactive plots, dashboards, and data applications. It provides elegant, concise construction of versatile graphics, and affords high-performance interactivity over large or streaming datasets. Python Flask App with Interactive Bokeh plotsĮmbedding bokeh plot and datatable in flaskīokeh plot not visible in flask applicationīelow is my current version of index.html. Bokeh is an interactive visualization library for modern web browsers. I have tried implementing the solutions at the following locations: Uncaught ReferenceError: Bokeh is not definedĪt HTMLDocument.fn (?description=blueberry+pancakes:29:5) While Matplotlib is a low-level visualization library, Bokeh offers both high-level and low-level interfaces. Bokeh stands out as the most similar library to Matplotlib when it comes to interactive visualization. I have gotten most of the way there, but I am receiving the following error: Bokeh is a highly flexible interactive visualization library designed for web browsers. I am currently trying to create a very simple app that displays a recipe and a network diagram.
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