Letterboxd Film Ratings & Reviews Scraper

Extract ratings, review counts, and full metadata for any film on Letterboxd. Supply a list of film slugs and get back a structured dataset covering rating scores, audience numbers, genres, directors, runtime, and external IDs — ready for recommendation engines, film-discovery apps, and audience research.

What you get

For each film slug you provide, the actor returns one record:

Field	Description
film_slug	Letterboxd URL slug (e.g. parasite-2019)
title	Film title
release_year	Year of release
director	Comma-separated list of directors
letterboxd_rating	Aggregate rating on a 0–5 scale
rating_count	Total number of ratings cast
review_count	Total number of written reviews
runtime_minutes	Runtime in minutes
genres	Comma-separated genres (e.g. Thriller, Drama)
countries	Countries of origin
languages	Spoken languages
tmdb_id	The Movie Database (TMDb) numeric ID
imdb_id	IMDb title ID (e.g. tt6751668)
letterboxd_url	Full Letterboxd URL for the film page

How to find a film slug

The slug is the last path segment in a Letterboxd film URL:

https://letterboxd.com/film/parasite-2019/
                             ^^^^^^^^^^^^
                             slug = parasite-2019

Go to any film page on Letterboxd and copy the segment after /film/.

Input

Parameter	Type	Description
filmSlugs	array	Required. List of Letterboxd film slugs to scrape
maxItems	integer	Maximum records to collect (0 = no limit)

Example input

{
  "filmSlugs": [
    "parasite-2019",
    "the-dark-knight",
    "inception",
    "spirited-away",
    "pulp-fiction"
  ],
  "maxItems": 10
}

Performance

• Processes roughly 30–60 films per minute at default concurrency
• No proxy required — Letterboxd serves film pages publicly
• Lightweight cheerio-based parsing; low memory and compute cost

Data source

All data is extracted from Letterboxd film pages (letterboxd.com/film/<slug>/), primarily from embedded JSON-LD structured data with DOM fallbacks for runtime and external ID links.