Скачать или смотреть Creating a Live Graph with CPU Data in Tkinter

Learn how to create a dynamic `live graph` displaying CPU usage in Tkinter by utilizing matplotlib and psutil. Improve your data visualization skills with this step-by-step guide!
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Creating a Live Graph with CPU Data in Tkinter

Are you looking to create a live graph that displays CPU usage in a Tkinter application? You’re in the right place! This guide will lead you through the steps required to display real-time CPU data using the psutil and matplotlib libraries within a Tkinter interface.

Problem Overview

You may want to plot CPU usage data over time, but simply plotting one dot every second won't give you a complete picture. Instead, you need to maintain a "history" of usage values without bogging down your system with an ever-expanding dataframe. The solution involves dynamically updating a graph with points that represent CPU usage collected at regular intervals.

Solution: Implementing a Live Graph

The process can be broken down into several clear steps. Let’s walk through each of them.

Step 1: Set Up Your Environment

To start, ensure you have the necessary libraries installed. You can install them using pip:

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Step 2: Create Lists for X and Y Data

For our graph, we will maintain two lists: one for the x-axis (time) and one for the y-axis (CPU usage). At each interval, we will add new data points and remove the oldest ones to keep the length of the data consistent.

Here's how you create these lists:

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Step 3: Define the Animation Function

Next, we need to define a function that will update our graph. In this function, we will append the new CPU usage value fetched from psutil.cpu_percent(), and manage our data lists:

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Step 4: Initialize the Tkinter Application

Now we need to create our Tkinter application and integrate the matplotlib graph into it. Below is a simplified version of how to set up this graphical interface and display the live graph:

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Step 5: Running the Application

Just run your application, and you should see a window that updates every second with the current CPU usage data! It dynamically displays the usage history while keeping the list sizes manageable.

Conclusion

By utilizing Tkinter and matplotlib together with psutil, you can create powerful and informative live graphs displaying CPU usage data. This guide has broken down the process into manageable steps, making it easy for you to implement and customize as needed.

Feel free to modify the canvas size and graph aesthetic to better fit your application design. Happy coding!