Open Source Python Hardware Monitoring Software

jetson_stats is a Python package for monitoring and controlling NVIDIA Jetson boards. It supports Jetson platforms such as Orin, Xavier, Nano, TX, and newer Jetson families. The project includes jtop, a terminal-based dashboard that gives users a live view of CPU, GPU, memory, power, temperature, engine usage, and system status. It can also be imported into Python scripts, which makes it useful for custom monitoring, robotics dashboards, automation, and diagnostics. Developers working with embedded AI systems can use it to understand performance limits and troubleshoot hardware behavior during deployment. Its main value is giving Jetson users a practical, readable, and scriptable view of board health and resource usage.

s-tui (Stress Terminal UI) is a terminal-based performance monitoring and stress-testing tool focused specifically on CPU behavior analysis in Linux and other UNIX-like systems. It provides real-time graphical visualization of CPU temperature, frequency, power consumption, and utilization directly within a text-based interface, eliminating the need for a graphical desktop environment. The utility is particularly useful for diagnosing thermal throttling, validating cooling solutions, and evaluating system stability under heavy load conditions. In addition to passive monitoring, s-tui can integrate with external stress tools to actively push the CPU to its limits while simultaneously displaying performance metrics. The software is lightweight, scriptable, and well suited for remote environments such as SSH sessions or small devices like Raspberry Pi.

gpustat is a lightweight Python command-line utility designed to provide fast, human-readable monitoring of NVIDIA GPU status in real time. It serves as a simplified alternative to the more verbose nvidia-smi tool by presenting key GPU metrics in a compact, developer-friendly format. The utility retrieves data through NVIDIA’s NVML bindings and displays information such as temperature, utilization, memory usage, and running processes directly in the terminal. Because it is easy to install via pip and requires minimal configuration, gpustat is widely used in machine learning environments, research clusters, and shared GPU servers. The tool also supports watch mode for continuous monitoring and JSON output for integration into automation pipelines. Overall, gpustat focuses on speed, clarity, and scriptability, making it especially useful for engineers who need quick GPU visibility without heavy monitoring stacks.

Comprehensive Hardware Analysis, Monitoring and Reporting for Windows. Exhausting information about hardware components displayed in hierarchy unfolding into deep details. Useful for obtaining a detailed hardware inventory report or checking of various hardware-related parameters. Real-time monitoring of a variety of system and hardware parameters covering CPUs, GPUs, mainboards, drives, peripherals, etc. Useful for detection of overheating, overload, performance loss or failure prediction. Full hardware hierarchy, or quick summary overview.

System Resource Monitor is a lightweight, Python-based desktop application designed for real-time monitoring of CPU and Memory performance. Built with Tkinter for the GUI, Matplotlib for dynamic graphing, and Plyer for cross-platform desktop notifications, this tool empowers users to keep track of CPU and memory usage efficiently. With customizable update intervals, data exporting capabilities, and built-in alerts for resource spikes, System Resource Monitor is perfect for anyone looking to keep an eye on their computer’s health without the bloat of heavier tools. Whether you're troubleshooting a performance issue, optimizing workflows, or simply curious about your machine’s behavior, this intuitive monitoring solution gives you all the critical insights you need in one easy-to-use interface.

Linux/Windows Admin with interactive features to control Resources on a remote PC

The solution GreenHop aims to perform energy and environmental (temperature, humidity, dew point and atmospheric pressure) monitoring of the Data Center server room, providing energy efficiency indicators through green metrics for Data Centers. The GreenHop solution is based on open source software and hardware. The approach of using open source solutions enables its deployment easier and independently of suppliers at the same time makes the solution scalable to the needs of each organization. Thus, we aim to provide ambiental monitoring of the Data Center server room while we keep the system to be customizable to implement and replicate.

Program is designed to show users internal and external ip addr. Both an end user and a client-server process, depending on setup options

Mining Overlord is a Python based program that periodically tests to see if a mining application (like cgminer or bfgminer) has stopped responding. This programs sole purpose it to maximize up-time for crypto coin mining operations. If it detects a non-response, it will restart the application automatically. It also features a configurable restart timer that automatically kills and relaunches the mining process at a set interval. This program is cross-platform compatible and has been tested on: Windows XP/Vista/7 Linux (Ubuntu 12.04 and Raspian) Mac OS 12.04 It requires that Python 2.7.3 or above be installed on the host to run. Currently, Mining Overlord only supports installations where one instance of the mining software is running.

Retrieve statistics from SNMP-aware devices, store them in a database and graphically display them for monitoring and notification purposes.

PotatoFinder is a Windows Incident Correlation Engine developed by PotatoChimp Labs. It helps users investigate crashes, system instability, and unexpected behavior by reconstructing timelines of events and identifying likely root causes. PotatoFinder continuously monitors important system activity such as software installations, Windows Updates, process crashes, driver changes, service modifications, and other system events. The built-in Investigation Engine correlates events around an incident, calculates confidence scores, generates evidence for and against each possible cause, and reconstructs what changed before things broke. Historical fingerprinting allows similar incidents to be compared over time, helping users recognize recurring problems and successful fixes. Features include: • Timeline Reconstruction • Incident Correlation Engine • Historical Fingerprinting • Root Cause Analysis • Anomaly Detection • Exportable Reports • Dark Theme GUI with System Tray usage.

Scalable Cluster Environment (SCE) is a set of interoperable opensource tools that enable users to build and use Beowulf cluster effectively to solve their problems.

VOMON (Virtual Observatory Monitor) is a web application that can be configured to watch your virtual observatory services. It is a mashup of the AstroRuntime and the MARS network monitor.

This tool can be used to create a GNS3/Dynamips replica of a real network by simply connecting to the network and using SNMP. Please see the instructions in the wiki.

EyeSpy is a is a PC/Windows based internet monitoring and visualization tool. It will scan and summarize all online activity, and display a realtime, interactive map showing the geographic location of all endpoints communicating online.