This article provides comprehensive Python scripts for system administration tasks including CPU monitoring, memory usage tracking, log analysis, file backup, system updates, network monitoring, service management, user administration, and system information collection.
When testing Linux server performance, you should monitor key metrics such as CPU usage, memory consumption, disk I/O, network bandwidth, process information, file system usage, system logs, boot and response times, context switches, and interrupts, using tools like top, vmstat, iostat, netstat, and custom Python scripts.
This guide explains why and how to monitor CPU, memory, and disk I/O on macOS or Windows using Python's psutil, matplotlib, and numpy libraries, covering performance analysis, troubleshooting, capacity planning, automated alerts, and includes a complete example script that visualizes resource usage over time.
This article demonstrates how to install the psutil Python library and use it to gather detailed CPU, memory, disk, network, and process information on a system, providing code examples and explanations for each type of metric.
This article explains how the Python subprocess module is employed in a data construction platform, compares run and Popen methods, discusses challenges such as incomplete log capture and process termination, and presents three practical solutions to ensure reliable execution and logging.
This step‑by‑step guide shows how to create a Windows‑like Task Manager using Python's Tkinter GUI library and the psutil module, covering project setup, menu creation, button layout, real‑time system metrics, and code snippets for full implementation.
This article introduces the powerful cross‑platform psutil module, explains how to install it, demonstrates basic commands to list processes, retrieve CPU usage, and explore various useful methods, all illustrated with clear code snippets and screenshots.
This guide explains why terminal enthusiasts need a visual resource monitor, introduces bpytop, and provides step‑by‑step instructions for installing it via source, package managers, or snap on various Linux distributions, plus usage tips and configuration details.
This article introduces five practical Python libraries—yagmail, requests, psutil, BeautifulSoup, and a collection of useful utils—explaining how each can dramatically reduce code complexity for sending emails, making HTTP calls, monitoring system resources, and parsing HTML.
This article introduces five highly practical Python packages—yagmail, requests, psutil, BeautifulSoup, and a collection of utility scripts—explaining how each simplifies common tasks such as sending emails, making HTTP calls, system monitoring, web scraping, and code reuse, complete with concise code examples.
