mdless is a Ruby-based command-line utility that renders Markdown files with syntax highlighting, formatting, and pager functionality. It acts as a 'less' replacement for Markdown, offering features like syntax highlighting via Pygments, image rendering with imgcat/chafa, table formatting, and support for TaskPaper syntax. The application processes input from files or stdin, applies Markdown parsing via Redcarpet, and outputs formatted terminal-ready text with ANSI color codes. It includes configurable themes, optional pager usage, and various output customization options. The codebase shows consistent maintenance with recent commits and demonstrates thoughtful handling of terminal rendering complexities.
This repository is a community-maintained study hub for the GATE Data Science and Artificial Intelligence (DA) exam. It provides syllabus-aligned resources including detailed markdown guides for seven core subjects (Probability & Statistics, Linear Algebra, Calculus & Optimization, Programming & Algorithms, Database Management, Machine Learning, Artificial Intelligence), verified previous-year question papers (2024–2026) with checksums, and focused Jupyter notebooks for practice. The primary delivery mechanism is a Flask web application that renders the markdown guides into an interactive curriculum explorer with topic checklists, progress tracking, presentation mode, and a radial memory map. The webapp can be exported as a static site for GitHub Pages deployment, and a CI/CD pipeline (GitHub Actions) runs tests, link audits, and checksum verification on each push. The repository also includes link validation scripts for pull requests and a set of deterministic example notebooks generated programmatically. While the core is an application, it also contains research-like elements such as exam pattern analysis, stale-link audits, and educational notebooks, but these are secondary to the main purpose of providing a structured, browsable study resource.
The repository maintains a curated list of Persian-language YouTube channels organized by topic. It stores channel data as JSON files in the subjects/ directory, each file representing a category (e.g., technology, programming, education). A Node.js script (scripts/index.js) reads these JSON files, combines them with static header and footer templates, and generates a formatted README.md file using the json2md library. The generated README.md is served via GitHub Pages, and a single HTML file (index.html) fetches the markdown, parses it with a custom, scoped markdown parser, and renders an interactive, searchable interface. The client-side code includes language‑agnostic search (with Persian/Arabic normalization), dynamic section navigation, and responsive UI built with vanilla JavaScript and CSS. The project is kept up to date through GitHub Actions workflows that validate the JSON data, regenerate the README, and run code formatting on every push to master. This ensures the list stays accurate and the generated documentation reflects the latest contributions.