# Letterboxd Film Scraper (`masked_hacker/letterboxd-scraper`) Actor

Scrape structured film data (rating, cast, crew, genres) from Letterboxd.

- **URL**: https://apify.com/masked\_hacker/letterboxd-scraper.md
- **Developed by:** [Masked Hacker](https://apify.com/masked_hacker) (community)
- **Categories:** Videos
- **Stats:** 3 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.00 / 1,000 films

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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 Film Scraper: Ratings, Cast, Crew & Metadata

Turn [Letterboxd](https://letterboxd.com) search terms or film URLs into a clean, structured
dataset of film metadata: rating, cast, crew, genres, studios, runtime, and cross-references to
TMDB and IMDB.

Perfect for **film research, recommendation engines, content analytics, and ratings datasets**
across any title on Letterboxd.

### What you get

- 🔎 **Search by title**, or paste your own Letterboxd film URLs.
- ⭐ **Rating data:** average rating, rating count and review count straight from the film page.
- 🎬 **Full credits:** director(s) and cast.
- 🏷️ **Genres, countries, studios and languages** for every film.
- 🆔 **Cross-platform IDs:** TMDB and IMDB, ready to join with other datasets.
- 📄 Clean JSON / CSV / Excel export, ready for a spreadsheet or a pipeline.

### Pricing

**Pay per event:** **$0.006 per film returned**, plus a small per-run start fee. You only pay
for films you actually receive; no monthly subscription.

### Input

| Field | Type | Description |
|---|---|---|
| `searchTerms` | string\[] | Film titles to search; each term's top results are scraped. |
| `startUrls` | url\[] | Direct Letterboxd film URLs, e.g. `https://letterboxd.com/film/parasite-2019/`. |
| `maxItems` | int | Stop after this many films (default 100). |
| `resultsPerSearch` | int | Films taken per search term (default 10). |
| `proxyConfiguration` | proxy | Residential proxy recommended. Letterboxd blocks datacenter IPs. |

Provide at least one of `searchTerms` or `startUrls`.

#### Example input

```json
{
  "searchTerms": ["parasite", "the substance"],
  "maxItems": 50
}
```

### Output

One record per film.

| Field | Description |
|---|---|
| `title`, `year`, `releaseDate` | Film identity. |
| `runtimeMinutes` | Runtime in minutes. |
| `director`, `cast` | Credits. |
| `genres`, `countries`, `studios`, `languages` | Classification and production metadata. |
| `averageRating`, `ratingCount`, `reviewCount` | Letterboxd member rating data. |
| `description`, `posterUrl` | Synopsis and poster image. |
| `tmdbId`, `imdbId` | Cross-platform identifiers. |
| `url`, `slug`, `scrapedAt` | Film URL, slug and scrape time. |

#### Example output

```json
{
  "title": "Parasite",
  "year": 2019,
  "runtimeMinutes": 132,
  "director": ["Bong Joon-ho"],
  "genres": ["Comedy", "Drama", "Thriller"],
  "averageRating": 4.57,
  "ratingCount": 1218453,
  "tmdbId": "496243",
  "imdbId": "tt6751668",
  "url": "https://letterboxd.com/film/parasite-2019/"
}
```

### FAQ

**Do I need a Letterboxd account or API key?** No. Just provide a search term or a film URL.

**Does this include user reviews?** No, only the aggregate rating and review count shown on the
film page, not individual review text.

**Is this legal?** The actor collects only publicly available film data. You are responsible for
complying with Letterboxd's terms and applicable law in your use of the data.

# Actor input Schema

## `searchTerms` (type: `array`):

Film titles to search on Letterboxd. Each term's top results are scraped.

## `startUrls` (type: `array`):

Direct Letterboxd film URLs to scrape, e.g. https://letterboxd.com/film/parasite-2019/.

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

Stop after this many film records are scraped.

## `resultsPerSearch` (type: `integer`):

How many films to take from each search term's results.

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

Residential proxy is recommended — Letterboxd blocks datacenter IPs.

## Actor input object example

```json
{
  "searchTerms": [
    "parasite",
    "the substance"
  ],
  "maxItems": 100,
  "resultsPerSearch": 10,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}
```

# Actor output Schema

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

All scraped film records in the default dataset.

# 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 = {
    "searchTerms": [
        "parasite",
        "dune"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("masked_hacker/letterboxd-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 = { "searchTerms": [
        "parasite",
        "dune",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("masked_hacker/letterboxd-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 '{
  "searchTerms": [
    "parasite",
    "dune"
  ]
}' |
apify call masked_hacker/letterboxd-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,masked_hacker/letterboxd-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/Lrf43wtO3blLs5RQ0/builds/YfoyZakmbBfz8F9dU/openapi.json