Letterboxd Scraper

Scrape Letterboxd films and reviews: average rating, rating histogram, genres, cast and crew, plus member reviews with star rating, text, date and likes. Works with film URLs, slugs, lists and popular pages.

Letterboxd Scraper turns any Letterboxd film into clean JSON. In reviews mode you get every review as its own row, with the half-star rating, the full review text (long reviews are expanded automatically), the watched or published date, likes, comments, rewatch and spoiler flags and the review language. You can sort the same way the website does (popular, newest, oldest, highest or lowest rated) or keep only one star rating. Letterboxd shows at most 3,072 reviews per sort order. When a film has more, the actor carries on through each star-rating bucket, so big titles yield up to about 30,000 reviews. In films mode you get the average rating with the full 0.5-5 star histogram, ratings/reviews/watched/likes/lists/fans counts, the Letterboxd Top 500 rank, directors, top-billed cast with characters, the full crew by role, genres, themes, countries, languages, studios, runtime, tagline, synopsis, poster and backdrop, IMDb and TMDB ids and every release date per country with its certification. Lists, browse pages (popular this week, any genre, decade, year...) and film search are covered too. No Letterboxd account is needed. Download JSON, CSV or Excel, or use the API from Python, Node, n8n, Make or Google Sheets. You pay only for the items you get: $1 per 1,000 reviews.

What data does Letterboxd Scraper extract?

Every item has a type field: review, film or list_entry.

Review items (type: "review", mode reviews)

Field	Description
filmSlug, filmTitle, filmYear, filmId	The film the review belongs to
reviewId, url	Letterboxd's numeric review (viewing) id and its boxd.it short link
rating	0.5-5 in half stars, or null when the reviewer gave no rating
text, textHtml	Full review text as plain text and as HTML (truncated reviews are expanded)
isTextTruncated	true only if the full text could not be loaded or fetchFullReviewText is off
language	Language code of the review text, e.g. en, pt, ar
watchedDate	Diary date (YYYY-MM-DD) when the review is a diary entry
publishedAt	When the review was posted (ISO 8601). Always set for reviews without a diary date; for diary entries turn on fetchReviewPublishDates
likesCount, commentsCount	Likes and comments on the review
isLiked	Whether the reviewer also "liked" (hearted) the film
isRewatch	Whether the review is for a rewatch
containsSpoilers	Whether the review is marked as containing spoilers
authorName	Reviewer's display name as shown on the review ("Philbert Dy")
authorUsername	Reviewer's Letterboxd username (handle), as in their profile URL (philbertdy)
authorUrl	Reviewer's public profile page (https://letterboxd.com/philbertdy/)
scrapedAt	ISO 8601 timestamp

Reviewer avatars are not collected. Letterboxd shows no numeric member id on reviews, so there is no authorId field.

Film items (type: "film", mode films)

Field	Description
id, slug, url, shortUrl	Letterboxd film id, slug, page URL and boxd.it link
title, originalTitle, alternativeTitles, year	Titles and release year
directors, cast, crew	[{name, url}]; cast [{name, character, url}] in billing order; crew {"Writers": [...], "Composer": [...], ...}
genres, themes	Genres and Letterboxd themes/mini-themes
countries, languages, primaryLanguage, studios	Production details
runtimeMinutes, tagline, description	Runtime, tagline and synopsis
averageRating, ratingsCount, reviewsCount	Weighted average (0.5-5), number of ratings and reviews
ratingHistogram	{"0.5": n, "1": n, ..., "5": n} rating counts
watchedCount, likesCount, listsCount, fansCount, top500Rank	Member stats (exact counts) and the rank in Letterboxd's Top 500
posterUrl, backdropUrl	Poster (600x900) and backdrop (1920x1080) images
tmdbId, tmdbType, imdbId	External ids
releaseDates	[{type, date, country, certification, note}], e.g. Premiere / Theatrical / Digital / Physical / TV per country
scrapedAt	ISO 8601 timestamp

List, browse and search rows (type: "list_entry", modes list and browse)

listType (list, browse or search), listTitle, listUrl (only for official Letterboxd lists, browse pages and searches; it is left out for lists made by members because their URL contains the member's username), position, slug, title, year, url, filmId, averageRating (browse pages only), scrapedAt.

How to use Letterboxd Scraper

1. Pick a Mode: reviews (default), films, list or browse.
2. Add films as Start URLs (https://letterboxd.com/film/parasite-2019/), Film slugs (parasite-2019) or Search terms (parasite 2019). In films and reviews mode a list, browse or search URL expands to its first films (Max films per list).
3. Set Max items and, in reviews mode, Max reviews per film.
4. Optionally choose a Review order and a star rating filter.
5. Click Start. Results appear in the Dataset tab; export from there or use the API.

Input example

{
  "mode": "reviews",
  "filmSlugs": ["parasite-2019", "the-godfather"],
  "maxReviewsPerFilm": 5000,
  "maxItems": 10000,
  "reviewSort": "added"
}

{ "mode": "films", "startUrls": [{ "url": "https://letterboxd.com/films/popular/this/week/" }], "maxFilmsPerListing": 50, "maxItems": 50 }

{ "mode": "list", "startUrls": [{ "url": "https://letterboxd.com/official/list/letterboxds-top-500-films/" }], "maxItems": 500 }

{ "mode": "browse", "startUrls": [{ "url": "https://letterboxd.com/films/genre/horror/" }, { "url": "https://letterboxd.com/films/decade/1990s/" }], "maxItems": 300 }

Output example

{
  "type": "review",
  "filmSlug": "parasite-2019",
  "filmTitle": "Parasite",
  "filmYear": 2019,
  "filmId": 426406,
  "reviewId": 72286970,
  "url": "https://boxd.it/MV5qJ",
  "rating": 5.0,
  "isLiked": true,
  "text": "Update: Now in video form\n\nThere is a house on a hill, and there are people in it. And they're nice, but not really. ...",
  "textHtml": "<p>Update: <a href=\"https://youtu.be/gzu8ATxG5bk\" rel=\"nofollow\">Now in video form</a></p><p>There is a house on a hill ...</p>",
  "isTextTruncated": false,
  "language": "en",
  "watchedDate": "2019-08-14",
  "publishedAt": null,
  "likesCount": 44548,
  "commentsCount": 248,
  "isRewatch": false,
  "containsSpoilers": true,
  "authorName": "Philbert Dy",
  "authorUsername": "philbertdy",
  "authorUrl": "https://letterboxd.com/philbertdy/",
  "scrapedAt": "2026-10-05T17:03:16Z"
}

{
  "type": "film",
  "id": 426406,
  "slug": "parasite-2019",
  "url": "https://letterboxd.com/film/parasite-2019/",
  "shortUrl": "https://boxd.it/hTha",
  "title": "Parasite",
  "originalTitle": "기생충",
  "year": 2019,
  "directors": [{ "name": "Bong Joon Ho", "url": "https://letterboxd.com/director/bong-joon-ho/" }],
  "cast": [{ "name": "Song Kang-ho", "character": "Kim Ki-taek", "url": "https://letterboxd.com/actor/song-kang-ho/" }],
  "crew": { "Writers": ["Kim Dae-hwan", "Bong Joon Ho", "Han Jin-won"], "Composer": ["Jung Jae-il"] },
  "genres": ["Thriller", "Comedy", "Drama"],
  "themes": ["Intense violence and sexual transgression", "Humanity and the world around us"],
  "countries": ["South Korea"],
  "languages": ["Korean", "English", "German"],
  "studios": ["Barunson E&A"],
  "runtimeMinutes": 133,
  "averageRating": 4.52,
  "ratingsCount": 5904509,
  "ratingHistogram": { "0.5": 5624, "1": 13987, "1.5": 6569, "2": 42344, "2.5": 37615, "3": 241316, "3.5": 284194, "4": 1321126, "4.5": 1025236, "5": 2926500 },
  "reviewsCount": 794155,
  "watchedCount": 7634477,
  "likesCount": 3927747,
  "listsCount": 898946,
  "fansCount": 196844,
  "top500Rank": 16,
  "tagline": "Act like you own the place.",
  "posterUrl": "https://a.ltrbxd.com/resized/film-poster/4/2/6/4/0/6/426406-parasite-0-600-0-900-crop.jpg?v=8f5653f710",
  "tmdbId": 496243,
  "imdbId": "tt6751668",
  "releaseDates": [{ "type": "Premiere", "date": "2019-05-21", "country": "France", "certification": null, "note": "Cannes Film Festival" }]
}

How to scrape all Letterboxd reviews of a film

Use reviews mode with the film URL or slug and set Max reviews per film high. Reviews are read 12 per page, the same pages the website shows. Letterboxd stops every sort order at page 256 (3,072 reviews), so for bigger films the actor continues with the 5-star, 4.5-star, ... and unrated buckets and drops duplicates. That way a film with hundreds of thousands of reviews still gives up to about 30,000 unique reviews. Only reviews whose text is shortened on the listing cost an extra small request (typically 1-2 per 24 reviews).

Can I get only negative (or positive) reviews?

Yes. Set Only reviews with this rating to a value from 0.5 to 5, or none for unrated reviews. You can also paste a filtered reviews URL from the website, such as https://letterboxd.com/film/parasite-2019/reviews/rated/1/by/added/, and the actor keeps that filter and order.

How to scrape Letterboxd popular films, genres and lists

Use browse mode with any /films/... page: /films/popular/this/week/, /films/genre/horror/, /films/decade/1990s/, /films/year/2024/ and so on (72 films per page, in the page's order). Use list mode with an official list such as /official/list/letterboxds-top-500-films/ or any member list (100 films per page). Switch to films mode with the same URLs to get the full film item for each film.

Monitor changes on a schedule

Turn on Only new or changed items and save the input as a task with a Schedule (Apify Console: Saved tasks -> Schedule, for example daily). Each run then remembers what earlier runs of the same input returned and outputs only what is new: new reviews in reviews mode (read newest first; full texts are loaded only for new reviews), films whose average rating or Top 500 rank changed in films mode, and new list or browse rows or rows whose average rating changed. Unchanged items are skipped before they are saved, so they are not charged. Add Only reviews newer than (7 days, 24 hours or a date like 2026-10-01) to limit the first run to recent reviews; paging stops as soon as a page reaches older or already-seen reviews. Monitored items carry changeType (new or changed) and, for changed films and rows, previousValues with the old values of the fields that changed (e.g. {"averageRating": 4.52}); Monitoring key keeps several schedules on the same input apart.

Does it work without a Letterboxd account?

Yes. The actor only reads pages Letterboxd serves to logged-out visitors over plain HTTP: no login, account cookies or browser. It never reads private data, diaries or profiles.

Which proxy should I use?

Keep the default (Apify Proxy). Letterboxd's Cloudflare protection challenges Apify datacenter IPs on deeper pages (review pages 2+, full review texts, rating fragments) at times. The actor then retries the request through Apify's residential proxy automatically and, once that has happened twice in a run, uses residential IPs for the rest of the run. Residential traffic is billed by Apify per GB on your account: a review page is about 30 KB on the wire, so it adds roughly $0.00003 per review. The run summary (SUMMARY in the key-value store) reports residentialFallbacks and okByProxy. If your plan has no residential proxy, the actor stays on datacenter IPs and retries more.

Is scraping Letterboxd legal?

This actor collects only data Letterboxd shows publicly to logged-out visitors: film metadata, aggregate statistics, public review texts with the reviewer's display name, username and public profile link as shown next to the review, and public lists. It does not collect avatars, does not scrape member profiles, diaries or watchlists, and reads nothing behind a login. Reviewer names, usernames and profile links are personal data under GDPR and similar laws: make sure you have a lawful basis for processing them, and do not use them to contact or profile individuals. You are responsible for how you use the data and for following Letterboxd's terms and applicable law (GDPR/CCPA).

Pricing

Pay per item: review $0.001, film $0.003, list/browse/search row $0.001. There is no start fee and no subscription. 10,000 reviews cost $10.

Integrations and API

Use the run in Zapier, Make, n8n, Google Sheets, or call it from Python/Node with the Apify client. See the API tab for ready-made snippets.

See also: Goodreads Scraper for book ratings and reviews.

Support

Found a bug or need a field added? Open an issue in the Issues tab; it is usually answered within a day.