# Letterboxd API Scraper (`rl1987/letterboxd-api-scraper`) Actor

Scrape Letterboxd public film data: search & browse films, full film detail (genres, directors, rating, description, poster), popular reviews, list films, and optional statistics (watches/likes/ratings/fans + rating histogram). Read-only, guest access, no account.

- **URL**: https://apify.com/rl1987/letterboxd-api-scraper.md
- **Developed by:** [R.L.](https://apify.com/rl1987) (community)
- **Categories:**
- **Stats:** 2 total users, 1 monthly users, 50.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 1,000 result rows

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Letterboxd Scraper

Scrape public film data from [Letterboxd](https://letterboxd.com) straight from its official
mobile API — **search & browse films, full film detail, popular reviews, and the films in any
list**, with optional per-film **statistics**. Read-only, **guest access, no account** (the actor
mints Letterboxd's own anonymous app token).

### Modes

| Mode | Returns | Key inputs |
|------|---------|-----------|
| **Search films** | Films matching a query | `query` |
| **Browse films (by genre)** | Films in a genre (and optional decade/year) | `genre`, `decade`, `year` |
| **Film details (by ID)** | Full records for given films | `filmIds` |
| **Film reviews (by ID)** | Popular reviews for one film | `filmId`, `reviewsSort` |
| **List films (by list ID)** | The films in a Letterboxd list | `listId` |

Turn on **Include film statistics** to add average rating and counts of watches, likes, ratings,
fans, lists and reviews (plus the rating histogram) to every film returned.

### Output

**Film rows:** `film_id`, `name`, `original_name`, `year`, `runtime`, `tagline`, `description`,
`rating`, `genres`, `directors`, `countries`, `languages`, `themes`, `top250_position`,
`poster_url`, `letterboxd_url`, `adult`. With statistics: `watches`, `likes`, `ratings_count`,
`fans`, `lists_count`, `reviews_count`, `rating_histogram`.

**Review rows:** `review_id`, `film_id`, `film_name`, `film_year`, `rating`, `review`,
`contains_spoilers`, `like_count`, `comment_count`, `when_created`, `author`, `review_url`.

### Notes

- Letterboxd film/list IDs are short base62 strings (e.g. `2a9q` = *Fight Club*). Get them from a
  Search or Browse run, then feed them into the detail / reviews / list modes.
- The API is not bot-gated; a proxy is optional.

### Pricing

**Pay per result — $1 per 1000 rows** ($0.001 each). A row is a film (search, browse, details or
list entry, including any statistics) or a review.

***

Built on the [apify-api-scraper-template](https://github.com/rl1987/apify-api-scraper-template).

# Actor input Schema

## `mode` (type: `string`):

What to scrape. Search and Browse return films; Film details fetches full records for given films; Film reviews returns popular reviews for one film; List films returns the films in a Letterboxd list. Default: Browse films (returns popular films with no other input needed).

## `includeStatistics` (type: `boolean`):

For every film returned, also fetch its statistics — average rating and counts of watches, likes, ratings, fans, lists and reviews, plus the rating histogram. Adds one request per film.

## `query` (type: `string`):

Search mode: film title or keywords (e.g. 'fight club').

## `genre` (type: `string`):

Browse mode: filter films by genre.

## `decade` (type: `string`):

Browse mode (optional): e.g. '1990' for the 1990s.

## `year` (type: `string`):

Browse mode (optional): a specific release year, e.g. '1999'.

## `films` (type: `array`):

Film details mode: one or more films by title (e.g. 'Parasite') or Letterboxd URL (e.g. https://letterboxd.com/film/parasite/).

## `film` (type: `string`):

Film reviews mode: the film whose reviews to fetch — by title or Letterboxd URL.

## `list` (type: `string`):

List films mode: the list whose films to fetch — by name or Letterboxd URL.

## `reviewsSort` (type: `string`):

Film reviews mode: how to order reviews.

## `maxItems` (type: `integer`):

Roughly how many items to return (0 = no limit). Pages are up to 100.

## `maxConcurrency` (type: `integer`):

Max requests processed in parallel.

## `maxRequestRetries` (type: `integer`):

Retries per request before it is marked failed.

## `maxSessionRotations` (type: `integer`):

Retries for a blocked/rate-limited status, each with a fresh session/proxy.

## `filmIds` (type: `array`):

Optional advanced override for Film details mode: raw Letterboxd film IDs (e.g. '2a9q'). If set, skips name/URL resolution.

## `filmId` (type: `string`):

Optional advanced override for Film reviews mode: a raw Letterboxd film ID.

## `listId` (type: `string`):

Optional advanced override for List films mode: a raw Letterboxd list ID.

## `proxyConfiguration` (type: `object`):

Optional. Letterboxd's API is not bot-gated; a proxy is not required.

## Actor input object example

```json
{
  "mode": "browse",
  "includeStatistics": false,
  "query": "Parasite",
  "films": [],
  "reviewsSort": "ReviewPopularity",
  "maxItems": 100,
  "maxConcurrency": 5,
  "maxRequestRetries": 5,
  "maxSessionRotations": 10,
  "filmIds": [],
  "filmId": "",
  "listId": "",
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "query": "Parasite",
    "decade": "",
    "year": "",
    "films": [],
    "film": "",
    "list": ""
};

// Run the Actor and wait for it to finish
const run = await client.actor("rl1987/letterboxd-api-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "query": "Parasite",
    "decade": "",
    "year": "",
    "films": [],
    "film": "",
    "list": "",
}

# Run the Actor and wait for it to finish
run = client.actor("rl1987/letterboxd-api-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "query": "Parasite",
  "decade": "",
  "year": "",
  "films": [],
  "film": "",
  "list": ""
}' |
apify call rl1987/letterboxd-api-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,rl1987/letterboxd-api-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/DotgtrEebK43S29yf/builds/nKFdwDRf7kB2RFzKJ/openapi.json