feat: multi-platform support for fav.py and new categories

[asboyer]

Summary

• Refactor fav.py into a data-driven category system for easy addition of new categories
• Add multi-platform support (Spotify, YouTube, SoundCloud, arbitrary URLs) for music categories
• Add new categories: books (Goodreads), episodes (IMDB), articles, videos, podcasts (og: meta scraping)
• Add reusable platform-icon.liquid include for platform detection
• Add show/show_link display for episodes, publication display for articles/podcasts
• Hide score circle when no score is present
• Content: add The Millionaire Next Door book

fav.py Documentation

Usage

python fav.py <url> <category> [field=value ...]

Supported Categories

Category	Source	Auto-scraped fields
albums	Spotify, YouTube, SoundCloud, other	title, creator, image, release year
songs	Spotify, YouTube, SoundCloud, other	title, creator, album, album_link, image, release year
playlists	Spotify, YouTube, SoundCloud, other	title, creator, image
artists	Spotify, YouTube, SoundCloud, other	title, image
movies	IMDB	title, director, image, release year
shows	IMDB	title, director, image, release year
episodes	IMDB	title, director, season/episode, show name, show_link, parent show image, air year
books	Goodreads	title, author(s), image, publication year
articles	Any URL (og: tags)	title, author, image, publication name, published date
podcasts	Apple Podcasts / any URL	title, show name, image, publication name, published date
videos	Any URL (og: tags)	title, image

Field Overrides

Override any auto-scraped or template field by appending key=value args:

python fav.py "https://example.com" articles title="Custom Title" creator="Custom Author"
python fav.py "https://example.com" albums redirect="https://other-url.com" score=9.5
python fav.py "https://example.com" videos img_url="https://image-url.com/img.jpg"

Adding a New Category

1. Add an entry to CATEGORY_FIELDS dict with the frontmatter fields for that category
2. Add the category to the appropriate scraping group (SPOTIFY_CATEGORIES, IMDB_CATEGORIES, GOODREADS_CATEGORIES, OG_SCRAPE_CATEGORIES) or add a new elif block
3. Optionally add to SQUARE_CROP_CATEGORIES if images should be square-cropped
4. Optionally add to PERFECT_THRESHOLDS with (field_name, threshold) for auto-perfect detection
5. Add an icon entry in _includes/scripts/category-icon.liquid

Configuration Constants

• CATEGORY_FIELDS — Maps each category to its extra frontmatter fields
• SQUARE_CROP_CATEGORIES — Categories with square-cropped images (music)
• SPOTIFY_CATEGORIES — Categories using the Spotify API
• IMDB_CATEGORIES — Categories scraped from IMDB (movies, shows, episodes)
• GOODREADS_CATEGORIES — Categories scraped from Goodreads (books)
• OG_SCRAPE_CATEGORIES — Categories using generic og: meta tag scraping
• PERFECT_THRESHOLDS — Auto-set perfect: true when score/stars meet threshold

Examples

# Spotify album
python fav.py "https://open.spotify.com/album/..." albums

# YouTube album with redirect
python fav.py "https://www.youtube.com/watch?v=..." albums redirect="https://open.spotify.com/..."

# IMDB movie
python fav.py "https://www.imdb.com/title/tt1234567/" movies

# IMDB TV episode (uses parent show image)
python fav.py "https://www.imdb.com/title/tt2301451/" episodes

# Goodreads book
python fav.py "https://www.goodreads.com/book/show/998" books

# Article from any site
python fav.py "https://www.wsj.com/some-article" articles

# Apple Podcasts episode
python fav.py "https://podcasts.apple.com/us/podcast/..." podcasts

# Song with score override
python fav.py "https://open.spotify.com/track/..." songs score=96

Test plan

• Tested Goodreads book scraping (The Millionaire Next Door)
• Tested IMDB episode scraping (Ozymandias - Breaking Bad)
• Tested YouTube album with redirect override
• Tested article scraping (WSJ)
• Tested Apple Podcasts scraping
• Verify Spotify categories still work as before
• Verify IMDB movies/shows still work as before