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Rutgers Course Search

Overview

Rutgers Course Search is a Flask-based web application that provides real-time access to Rutgers University course information, room schedules, and instructor salary data. The application serves as a comprehensive search tool for students and faculty to explore course offerings, check room availability, and access public salary information. It features a REST API backend with automatic data updates and a responsive Bootstrap frontend with multiple search interfaces.

User Preferences

Preferred communication style: Simple, everyday language.

System Architecture

Backend Architecture

  • Framework: Flask web framework with Python 3.11
  • API Design: RESTful API endpoints for courses, rooms, and salary data
  • Data Fetching: Dedicated service classes (CourseFetcher, RoomFetcher, SalaryData) for external data integration
  • Caching Strategy: Flask-Caching with SimpleCache for performance optimization
  • Rate Limiting: Flask-Limiter with memory storage for API protection
  • Background Processing: APScheduler for automatic course data updates every 15 minutes
  • Session Management: Flask sessions with configurable secret keys

Frontend Architecture

  • UI Framework: Bootstrap 5.3 for responsive design
  • Styling: Custom CSS with Rutgers branding (scarlet red color scheme)
  • JavaScript: Vanilla JavaScript for API interactions and dynamic content
  • Template Engine: Jinja2 templates for server-side rendering
  • Icons: Bootstrap Icons for consistent iconography

Data Processing

  • Web Scraping: BeautifulSoup for parsing Rutgers course pages
  • HTTP Requests: Requests library with retry strategies and session management
  • Fuzzy Matching: RapidFuzz for intelligent search and name matching
  • Data Validation: Input sanitization and error handling throughout the pipeline

Application Structure

  • Entry Point: main.py for development server startup
  • Core Application: app.py with route definitions and middleware configuration
  • Service Layer: Separate classes for course fetching, room management, and salary data
  • Static Assets: CSS, JavaScript, and JSON files served from /static
  • Templates: HTML templates for different search interfaces and documentation

Security Features

  • CORS Configuration: Proper cross-origin resource sharing setup
  • Rate Limiting: Multiple tiers (daily, hourly, per-minute) to prevent abuse
  • Input Validation: Sanitization of user inputs and API parameters
  • Error Handling: Comprehensive exception handling with logging

External Dependencies

Third-Party Services

  • Rutgers Course API: https://classes.rutgers.edu/soc/api/courses.json for real-time course data
  • Rutgers SAS Website: Web scraping for major/minor requirements and advising information

Python Libraries

  • Flask Ecosystem: Flask, Flask-Limiter, Flask-Caching for web framework functionality
  • Web Scraping: BeautifulSoup4, Requests for data extraction from external websites
  • Data Processing: RapidFuzz for fuzzy string matching, JSON/CSV for data handling
  • Scheduling: APScheduler for background task management
  • HTTP Handling: urllib3 with retry strategies for robust API calls

Frontend Dependencies

  • Bootstrap 5.3: CSS framework from CDN for responsive UI components
  • Bootstrap Icons: Icon library for consistent visual elements
  • Google Fonts: Inter and IBM Plex Mono fonts for typography

Development Tools

  • Static Assets: Local CSS and JavaScript files for custom functionality
  • Data Storage: JSON and CSV files for salary data and course information caching
  • Configuration: Environment-based configuration for secrets and deployment settings