$ show DS-AI-GATE/dsai-gate
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 LLM identified 3 files worth highlighting for reuse:
The `MarkdownCurriculumRenderer` class parses subject markdown guides (with Mermaid diagrams, headings, links) into a structured curriculum data model. It uses a `SubjectConfig` dataclass for easy addition of new subjects. This component is self-contained, depends only on standard library modules (`pathlib`, `re`, `json`), and could be extracted to render any markdown-based curriculum into a JSON syllabus for a frontend application.
A script that exports the Flask application as a static site by iterating over routes, rendering templates with test client, and writing HTML, assets, and a `syllabus.json` file. This pattern allows the same Flask codebase to serve both a development server and a deployable static site, making it reusable for any Flask app that can be rendered server-side without dynamic per-request logic.
A pull-request link validation script that uses `git diff` to detect new or modified links, validates local file paths, and outputs a markdown report for external link checking via lychee. It is parameterized, idempotent, and could be adapted to any repository that needs to validate links in markdown files before merging.