Lindholmen Lunch – Your daily lunch overview for Gothenburg's Lindholmen district.

Lindholmen Lunch is a Python project that fetches, parses, and summarizes lunch menus from various restaurants in Lindholmen, Gothenburg. It scrapes menus from multiple restaurant websites, organizes the data by weekday, and generates user-friendly HTML summaries for easy viewing.

• Scrapes lunch menus from several Lindholmen restaurants using dedicated scrapers.
• Stores daily menu data in JSON files under the data/ directory.
• Generates summary HTML pages for each weekday and a weekly overview.
• Modular scraper architecture for easy extension to new restaurants.
• Includes sample HTML files and test data for development and testing.

.
├── main.py                  # Main entry point for scraping and HTML generation
├── generate_html.py         # Functions to generate HTML summaries from JSON data
├── utils.py                 # Utility functions (e.g., date helpers)
├── scrapers/                # Individual restaurant scrapers (one per restaurant)
├── data/                    # Cached JSON data and generated HTML summaries
├── docs/                  # Generated HTML files for each weekday and index
├── templates/               # Jinja2 HTML templates for rendering summaries
├── tests/                   # Test scripts and sample HTML files for development
├── requirements.txt         # Python dependencies
├── README.md                # Project documentation
└── .gitignore

• Python 3.10+
• Google Chrome (for Selenium-based scrapers)
• ChromeDriver installed and in your PATH

1. Install dependencies:

   pip install -r requirements.txt

2. Scrape menus and generate HTML:

   Scraped data is cached in data/lunch_data_.json and reused unless --refresh is passed.

   • To scrape and generate the summary for today:

     python main.py

   • To scrape for a specific day (e.g., "monday"):

     python main.py --day monday

   • Force refresh for a specific day (e.g., "monday"):

     python main.py --day monday --refresh

   • Force refresh for all days:

     python main.py --all --refresh

3. View results:

   • Open the generated HTML files in your browser (e.g., docs/index.html, docs/lunch_monday.html).

1. Create a new scraper in the scrapers/ directory by subclassing LunchScraper.
2. Implement the scraping logic for the restaurant's website.
3. Add the new scraper to the SCRAPERS list in main.py.

• Run or adapt tests as needed to verify scraper correctness.

This project is for educational and personal use. Please respect the terms of use of the restaurant websites being scraped.