Open Source Unix Shell Software

MagiskOnWSALocal is an open source project by LSPosed that integrates Magisk root and Google Apps (GApps) into Windows Subsystem for Android (WSA). It automates the process of building customized WSA images with root access, replacing Amazon Appstore with Google Play services. The repository includes scripts that streamline setup across Linux distributions like Ubuntu, Debian, Arch, and openSUSE, supporting both ARM64 and x64 architectures. It offers features such as unattended installation, automatic developer mode activation, and seamless updates without data loss. This project has become popular among advanced users who want more control over Android on Windows. Note: support for Magisk on WSA will end after March 5, 2025.

This repository collects practical, real-world examples of using Ansible to automate infrastructure, deployments, and configurations. Each directory demonstrates a specific use case—ranging from setting up web servers, load balancers, and databases to orchestrating multi-tier applications in cloud environments. The examples highlight common Ansible practices such as organizing inventories, writing reusable playbooks, using roles, and handling variables and templates. They’re designed to be adapted directly into your own infrastructure or to serve as reference blueprints when learning how to structure automation projects. Whether you’re managing a handful of servers or deploying at scale, this repo provides starting points that illustrate how Ansible can streamline repetitive operational tasks.

Generative AI for Beginners is a 21-lesson course by Microsoft Cloud Advocates that teaches the fundamentals of building generative AI applications in a practical, project-oriented way. Lessons are split into “Learn” modules for core concepts and “Build” modules with hands-on code in Python and TypeScript, so you can jump in at any point that matches your goals. The course covers everything from model selection, prompt engineering, and chat/text/image app patterns to secure development practices and UX for AI. It also walks through modern application techniques such as function calling, RAG with vector databases, working with open source models, agents, fine-tuning, and using SLMs. Each lesson includes a short video, a written guide, runnable samples for Azure OpenAI, the GitHub Marketplace Model Catalog, and the OpenAI API, plus a “Keep Learning” section for deeper study.

The Rust语言圣经 (Rust Language Bible) is a comprehensive, Chinese-language Rust tutorial that aims to take learners from beginner concepts to advanced mastery. The course is carefully designed with a structured catalog, vivid and approachable language, and an engaging style that avoids the dry and mechanical tone of many technical books. It covers the basics of Rust, such as ownership, borrowing, lifetimes, traits, and generics, but also dives deep into advanced topics like performance optimization, linked list implementations, async programming with Tokio, standard library internals, Cargo usage, and WebAssembly development. The project emphasizes practical learning through exercises, helping users approach Rust study as if it were a university course. It also provides a "Cookbook" section of practical code snippets for common tasks such as file operations, regex handling, and database interactions, allowing learners to quickly reference solutions without searching externally.

NxShell is a modern, Electron-based terminal emulator that works on all major operating systems out there: Windows, macOS, and Linux.

Tria O.S. detects hard & soft specs of the PC where you run it, you can load this info or specify it manually to let the program inform you what would be the best operating system for a specific PC, with the specified hardware, and then see the difference by adding RAM, a SSD hard drive, changing the graphics card ... etc. REQUIREMENTS: For Linux, you need GAMBAS 3.3 or later, so you will have to install the gambas3 package before installing. 90's EDITION needs 160 MB (192 MB on a virtual machine) of RAM and works with Windows 95 and Windows NT 4.0. BRONTOSAURUS EDITION needs DirectX 9.0c and .Net Framework 2.0 and runs on Windows 98, Windows 98 SE, Windows ME & Windows 2000. XP EDITION requires .Net Framework 4.0 or newer. Runs on Windows XP, Vista, Server 2003, 2003 R2, Home Server and Server 2008. STANDARD EDITION needs .Net Framework 4.8 or 4.8.1 and runs on Windows 7, Windows Server 2008 R2, and newer (any Windows released from 2009 until today).

The aim is to support learning withinof Hamlib-centric software . See https://hamlib-sdk.sourceforge.io . This kit is designed to support research and learning into Hamlib (https://sourceforge.net/projects/hamlib/) and WSJT-X (https://wsjt.sourceforge.io/wsjtx.html). Follow discussion at JTSDK @ GROUPS.IO . The file(s) needed to deploy the current kit are : - https://sourceforge.net/projects/hamlib-sdk/files/Windows/JTSDK-4.1-Stream/JTSDK64-4.1.0.exe Hamlib is dynamic due to the differences in hardware capabilities. See: https://sourceforge.net/projects/hamlib/ Current efforts focus on learning and compiling "JT" software. Packages are provided that enable kits to be easily maintained and updated.

Deploy Azure resources through the Azure Resource Manager with community contributed templates to get more done. Deploy, learn, fork and contribute back. Azure Resource Manager allows you to provision your applications using a declarative template. In a single template, you can deploy multiple services along with their dependencies. You use the same template to repeatedly deploy your application during every stage of the application lifecycle. Azure Resource Manager is the deployment and management service for Azure. It provides a management layer that enables you to create, update, and delete resources in your Azure account. You use management features, like access control, locks, and tags, to secure and organize your resources after deployment. To learn about Azure Resource Manager templates (ARM templates), see the template deployment overview.

Claude-Flow v2 Alpha is an advanced AI orchestration and automation framework designed for enterprise-grade, large-scale AI-driven development. It enables developers to coordinate multiple specialized AI agents in real time through a hive-mind architecture, combining swarm intelligence, neural reasoning, and a powerful set of 87 Modular Control Protocol (MCP) tools. The platform supports both quick swarm tasks and persistent multi-agent sessions known as hives, facilitating distributed AI collaboration with persistent contextual memory. At its core, Claude-Flow integrates Dynamic Agent Architecture (DAA) for self-organizing agent management, neural pattern recognition accelerated by WebAssembly SIMD, and a SQLite-based memory system for context retention and knowledge persistence across tasks. It automates development workflows via pre- and post-operation hooks, providing seamless coordination, code formatting, validation, and performance optimization.

The package 'epyunit' provides extensions for PyUnit and PyDev. * Extensions for PyUnit - Unittests for arbitrary executables. * Extensions for PyDev - Automation of search and load of pydevd.py The extensions are applicable from commandline and/or within Eclipse. Online manuals: - https://pythonhosted.org/epyunit/ PyPi repository: - https://pypi.python.org/pypi/epyunit Current application examples are: - bash-core - http://bash-core.sourceforge.net Nickname - Dromi https://en.wikipedia.org/wiki/Dromi