Letterboxd Scraper 🎬

Scrape any Letterboxd user's diary — watched films, star ratings, reviews, rewatch flags, watched dates, posters and TMDB IDs — straight from their public RSS feed. No API key, no login, no cookies.

Fast, lightweight and datacenter-proxy friendly. Point it at one or more usernames and get clean, structured JSON of everything in their recent film diary.

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What it does

Give the actor a list of Letterboxd usernames (e.g. dave, davidehrlich) and it returns every recent diary entry as a structured record:

• 🎞️ Film title & year
• ⭐ Star rating (numeric, e.g. 4.5)
• 📝 Review text (HTML stripped, capped at 5,000 chars)
• 🔁 Rewatch flag (true/false)
• 📅 Watched date and original publish date (ISO 8601)
• 🖼️ Poster image URL
• 🎬 TMDB movie ID — join directly to The Movie Database
• 🔗 Direct Letterboxd URL and stable GUID

Because it reads the official public RSS feed, it is quick, reliable and gentle on resources.

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Example output

{
  "username": "dave",
  "film_title": "Obsession",
  "film_year": "2025",
  "rating": 3.5,
  "rewatch": false,
  "watched_date": "2026-07-09",
  "review": "A genuinely great thriller.",
  "poster": "https://a.ltrbxd.com/resized/film-poster/1/2/3/obsession.jpg",
  "tmdb_id": "1339713",
  "url": "https://letterboxd.com/dave/film/obsession-2025/",
  "published": "2026-07-09T16:55:16+00:00",
  "source": "letterboxd",
  "guid": "letterboxd-watch-1388436545",
  "scraped_at": "2026-07-20T00:00:00+00:00"
}

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Input

Field	Type	Description
mode	select	diary — fetch each username's recent diary/review entries.
usernames	array	Letterboxd usernames (part after letterboxd.com/). Full profile URLs are accepted too. Prefilled with ["dave", "davidehrlich"].
maxItems	integer	Max entries across all usernames (default 100, max 1000). RSS exposes ~50 most recent per user.

{
  "mode": "diary",
  "usernames": ["dave", "davidehrlich"],
  "maxItems": 100
}

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Use cases

• Film data — build a dataset of films, ratings and metadata linked to TMDB.
• Critic & creator tracking — monitor what film critics and creators are watching and rating over time.
• Recommendation datasets — feed ratings and rewatch signals into recommender models.
• Taste analysis — analyze a user's viewing habits, rating distribution and rewatch patterns.

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Pricing

Roughly $0.5 per 1,000 entries — one of the cheapest ways to pull structured film-diary data at scale. Pay-as-you-go on the Apify platform.

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Related actors

• TVmaze TV Scraper
• Anime Scraper
• MusicBrainz Scraper
• Reddit Scraper

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Notes & FAQ

• No API key required. The actor reads each user's public RSS feed (letterboxd.com/{username}/rss/).
• Private diaries and unknown usernames are skipped with a warning.
• How many entries per user? Letterboxd RSS exposes roughly the 50 most recent diary items.
• Ethics & compliance. Only publicly available data is collected. Respect Letterboxd's terms and applicable laws.

Keywords: letterboxd scraper, film diary, movie ratings, film reviews, letterboxd api, tmdb, movie data, film critic tracking, watched films, cinema dataset, recommendation data, taste analysis.