EnrollAlert is a website and notification service that tracks seat availability for UW-Madison courses and allows users to be notified the moment a seat opens up.

It is powered by a scheduled Go scraper that grabs real time course seat info which is made available on a React/Next.js frontend hosted with Vercel, which you can find at enrollalert.com. Data is stored in a Supabase PostgreSQL database and project operations including emailing and automated scraping are supported by AWS services.

EnrollAlert is inspired by Madgrades and strives to make the course enrollment process easier and stress-free for UW-Madison students.

• Real-time seat tracking: Scrapes UW-Madison's Course Search & Enroll API on a configurable schedule and dynamically updates the course database.
• Customizable alerts: Allows users to specify when they would like to be notified of seat availability in specific courses and specific subsections.
• Instant notifications: Email (and in the future SMS) alerts are sent to users as soon as their selected alerts go off.
• Filtered search: Users can search for courses by name, subject, and the specific degree credits that they satisfy.
• Course dashboard: The My Courses page shows users' active alerts, seat info for selected courses, and allows for alert removal with the click of a button.
• Account security: Firebase authentication and Supabase Row-Level-Security protect user info and requests.

This diagram gives an overview of the project architecture (warning: I am not artistically inclined) and below is a brief summary of the different project components.

• Scraper: Go program that can be run via AWS Lambda cmd/lambda/main.go or locally cmd/main.go. On initial run it grabs course ID's from UW-Madison's general search API and uploads them to DB. On subsequent runs it grabs course ID's and uses them to access APIs for individual UW-Madison courses, requesting seat info for lectures and subsections before uploading to DB. Uses batching and goroutines to quickly scrape 5000+ course pages without stressing API.

• Notifier: Go program run after scraper checks newly updated courses to see if any user alerts have been set off. Emails users via AWS SES and deletes alerts after notification.

• Database: PostgreSQL database hosted on Supabase. Contains course information (course ID's, subject ID's, breadths, etc.), course section information (seat info, professor, section number), user information (specified course alerts), and a course cache that tracks which courses have available sections (updated after each scrape).

• Frontend: Built with Next.js, React, and Typescript with Shadcn components, deployed via Vercel. Next.js API endpoints are called with user actions, retrieving from and updating PostgreSQL database. Firebase used for authentication.

DISCLAIMER: This project scrapes data from a public, university site whose purpose is to serve UW-Madison students. Please obtain permission before use and employ best practices.

A Dockerfile will be provided in future commits, but for now this serves as a somewhat simple guide to run the scraper locally.

To run the course scraper locally, git clone and spin up a PostgreSQL database and save the connection string as an environment variable POSTGRES_URL. Run go build -o scraper backend/cmd/main.go (not backend/cmd/lambda/main.go), and once built run ./scraper -init. For subsequent runs, just do ./scraper. Currently, the scraper is set to scrape Fall 2025 courses by default, but term can be specified by running ./scraper -term <term-number>, with the term number you want being found via the Course Search & Enroll API. If you've configured your courses and course_sections tables correctly, both should be populated with current course info. Happy scraping!

Contributions are welcome and encouraged. Feel free to fork and open PR's as you please, any improvements will be greatly appreciated. If you want to make suggestions, feel free to open an issue or fill out the feedback form on the site. Future updates and improvements are always in the works. Contributions made that support the Roadmap below are incredibly helpful!

• Better UI support on mobile
• Persistent data storage and tracking to show past enrollment trends
• SMS notification options
• Higher user tiers for incrased scrape frequency
• FAQ section once user feedback is gathered

Developed by Blaize Lahman

Course data gathered from UW-Madison Course Search & Enroll

Project inspired by Madgrades

Project unaffiliated with the University of Wisconsin-Madison