Web Application Server Sgskip

Introduction

This tutorial lab will guide you through using Matplotlib in a Flask web application server. You will learn how to create figures using the .Figure constructor and save them to in-memory buffers, embed the resulting figures in HTML output, and run the Flask application using the flask command-line tool.

VM Tips

After the VM startup is done, click the top left corner to switch to the Notebook tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.

Skills Graph

Install Dependencies

Before we get started, make sure you have the necessary packages installed. You can install them using pip.

pip install matplotlib flask

Import Dependencies

In this step, we will import the necessary dependencies. We will use base64 to encode the image data, BytesIO to store the image data in memory, Flask to create the web application server, and Figure to create the figures.

import base64
from io import BytesIO

from flask import Flask

from matplotlib.figure import Figure

Create the Flask Application

In this step, we will create the Flask application. We will define a route for the home page ("/") and a function to generate and embed the Matplotlib figure.

app = Flask(__name__)

@app.route("/")
def home():
    ## Generate the figure **without using pyplot**.
    fig = Figure()
    ax = fig.subplots()
    ax.plot([1, 2])
    ## Save it to a temporary buffer.
    buf = BytesIO()
    fig.savefig(buf, format="png")
    ## Embed the result in the html output.
    data = base64.b64encode(buf.getbuffer()).decode("ascii")
    return f"<img src='data:image/png;base64,{data}'/>"

Run the Flask Application

In this step, we will run the Flask application using the flask command-line tool. Assuming that the working directory contains this script, run the following command to start the server:

FLASK_APP=matplot_lib_tutorial_lab flask run

View the Output

In this step, we will view the output of the Flask application by navigating to http://localhost:5000/ in a web browser. The Matplotlib figure should be displayed on the page.

Summary

In this tutorial lab, we learned how to use Matplotlib in a Flask web application server. We created a Flask application, generated a Matplotlib figure, embedded the figure in the HTML output, and ran the Flask application using the flask command-line tool.