Operations 4 min read

Installing and Using Bpytop – A Beautiful Python‑Based Terminal Resource Monitor

This guide introduces Bpytop, the Python‑based, visually appealing terminal resource monitor, outlines its key features, explains the required prerequisites, and provides step‑by‑step instructions—including code snippets—for installing and operating the tool on Linux systems.

Python Programming Learning Circle
Python Programming Learning Circle
Python Programming Learning Circle
Installing and Using Bpytop – A Beautiful Python‑Based Terminal Resource Monitor

For terminal enthusiasts, monitoring system resource usage is essential, and while tools like top and htop show only basic metrics, Bpytop offers a richer, visually appealing interface as the Python implementation of bashtop.

Key features of Bpytop include:

A fast‑responsive UI with arrow navigation

In‑UI configuration options

Keyboard and mouse support with menu scrolling

Process filtering

Display of current disk read/write speeds

Ability to send SIGTERM, SIGKILL, and SIGINT to selected processes

Auto‑scaling graphs for network usage and disk I/O

Before installing Bpytop, ensure your system meets the following requirements:

Python 3.6 or newer

The psutil module (install with python3 -m pip install psutil)

Installation can be performed via package managers, but the manual method is described here:

1. Clone the repository from GitHub:

$ git clone https://github.com/aristocratos/bpytop.git

2. Change into the cloned directory: $ cd bpytop 3. Build and install the program: $ sudo make install After installation, launching bpytop displays a comprehensive view of CPU, memory, network, and disk usage. Press ESC to access the Help screen for command usage and keyboard shortcuts, and press q to quit. Configuration files can be edited in $HOME/.config/bpytop.

PythonLinuxInstallationSystem monitoringterminalbpytop
Python Programming Learning Circle
Written by

Python Programming Learning Circle

A global community of Chinese Python developers offering technical articles, columns, original video tutorials, and problem sets. Topics include web full‑stack development, web scraping, data analysis, natural language processing, image processing, machine learning, automated testing, DevOps automation, and big data.

0 followers
Reader feedback

How this landed with the community

Sign in to like

Rate this article

Was this worth your time?

Sign in to rate
Discussion

0 Comments

Thoughtful readers leave field notes, pushback, and hard-won operational detail here.