Letterboxd Scraper — Films, Ratings, Watchlists, Lists & More

Extract rich film data from Letterboxd — average rating, number of ratings, watches, likes, fans, genres, directors, cast, runtime, synopsis, countries, languages, studios, themes, streaming availability and poster — into clean JSON, CSV or Excel. Point it at individual films, a user's watchlist or diary, any list, a director or actor, a genre, a browse page, or just a search term. Fast and reliable.

Great for film datasets, recommendation engines, ranking & analytics, watchlist backups and research.

What you can scrape

• 🎬 Single films — letterboxd.com/film/parasite-2019/ (or a bare slug like parasite-2019)
• 👤 A user's watchlist or diary — letterboxd.com/USERNAME/watchlist/, .../films/diary/
• 📋 Any list — letterboxd.com/USERNAME/list/LIST-NAME/
• 🎬 A director or actor's films — letterboxd.com/director/greta-gerwig/, /actor/NAME/
• 🎭 A genre — letterboxd.com/films/genre/horror/, or the Genre field
• 🔥 Browse pages — popular this week, popular all-time, highest rated, newest
• 🔎 Search — pass a title or keyword and get matching films

Give it any mix as Start URLs (plus optional search/genre) and it pulls full metadata for every film.

Example input

{
  "startUrls": [
    "https://letterboxd.com/films/popular/this/week/",
    "https://letterboxd.com/schaffrillas/watchlist/",
    "https://letterboxd.com/film/parasite-2019/"
  ],
  "search": "blade runner",
  "sort": "FilmPopularityThisWeek",
  "maxFilms": 200,
  "includeStatistics": true
}

What you get

One row per film:

{
  "title": "Parasite",
  "year": 2019,
  "rating": 4.52,
  "ratingCount": 5664177,
  "watches": 8600000,
  "likes": 4200000,
  "fans": 210000,
  "reviewCount": 480000,
  "director": ["Bong Joon Ho"],
  "genres": ["Thriller", "Comedy", "Drama"],
  "runtimeMinutes": 133,
  "cast": ["Song Kang-ho", "Lee Sun-kyun", "Cho Yeo-jeong", "…"],
  "countries": ["South Korea"],
  "languages": ["Korean", "English"],
  "studios": ["Barunson E&A"],
  "themes": ["…"],
  "synopsis": "…",
  "poster": "https://a.ltrbxd.com/resized/film-poster/…jpg",
  "imdbUrl": "https://www.imdb.com/title/tt6751668/",
  "tmdbUrl": "https://www.themoviedb.org/movie/496243",
  "url": "https://letterboxd.com/film/parasite-2019/"
}

Output schema

Field	Type	Description
slug	string	Letterboxd film slug (e.g. parasite-2019)
lid	string	Letterboxd internal film ID
title	string	Film title
year	string	Release year
rating	string	Average Letterboxd rating (out of 5)
ratingCount	integer	Number of ratings
bestRating	integer	Maximum possible rating on the scale
director	array	Director(s)
genres	array	Genre tags
runtimeMinutes	string	Runtime in minutes
tagline	string	Film tagline
synopsis	string	Plot synopsis
cast	array	Cast members
countries	array	Production countries
languages	array	Spoken languages
studios	array	Production studios
poster	string	Poster image URL
imdbUrl	string	Link to the film on IMDb
tmdbUrl	string (URL)	Link to the film on TMDB
watches	integer	Number of users who logged a watch
likes	integer	Number of likes
fans	integer	Number of fans
listAppearances	integer	Number of lists the film appears on
reviewCount	integer	Number of written reviews
themes	array	Theme tags
url	string (URL)	Link to the film's Letterboxd page
streaming	array	Where the film is available to stream/rent/buy (when includeAvailability is on)

Input fields

Field	Description
startUrls	Film pages, a user's watchlist/ or films/diary/, a list/, a director//actor/ page, a films/genre/ page, or browse/popular pages. Bare film slugs also work.
search	Optional free-text film search (title or keyword).
genre	Optional genre to browse (e.g. horror, comedy, drama, science fiction, documentary).
sort	Sort order for browse/genre pages: popular this week, popular all-time, highest rated, newest, or name.
maxFilms	Max films to scrape in total across all inputs (up to 100,000).
includeStatistics	Include rating count, watches, likes, fans, review and list counts (on by default).
includeAvailability	Include where each film is available to stream/rent/buy (adds a streaming field).

Use cases

• Build a film dataset — ratings, rating counts, genres and crew for thousands of titles
• Recommendation & ranking — use real Letterboxd ratings, rating counts and popularity as signal
• Watchlist backup — export a user's watchlist to a spreadsheet
• Popularity & rating analysis — scrape a browse page and crunch the numbers
• Enrich your movie app — pull posters, runtime, cast, synopsis and IMDb/TMDB links by title or URL

FAQ

How many films can I scrape? Set maxFilms up to 100,000. Browse pages and watchlists are paged through automatically.

Can I scrape a specific user's watchlist? Yes — use their watchlist/ URL as a start URL.

How does billing work? Pay per film scraped — you only pay for the films you actually get.

Do I need any setup? No — just add your inputs and run. Fast and reliable.

Is this only public data? Yes. It returns only publicly available Letterboxd data.

Can I connect this to other tools? The Letterboxd Scraper can be connected with almost any cloud service or web app thanks to integrations on the Apify platform. It works with Make, Zapier, Slack, Airbyte, GitHub, Google Drive and many more, plus the Apify API, JavaScript/Python clients and MCP. Or use webhooks to trigger an action whenever a run finishes.

Related Actors

• TVmaze Scraper — TV shows, episodes and cast
• Steam Games Scraper — game catalog, prices and reviews
• Google Trends Scraper — interest over time for any title

Notes

Original clean-room implementation. Returns only public Letterboxd data; you are responsible for how you use the data and for complying with Letterboxd's terms. This is an independent tool and is not affiliated with or endorsed by Letterboxd.