🍿 Memento

Visualize your Letterboxd profile data with interactive charts and insights!

Try it live! The server sleeps when idle, so the first load takes a moment to wake up.

How It Works

1. Enter your Letterboxd username (or upload your data export)
2. The app scrapes your public profile data (this may take a few minutes)
3. Explore interactive visualizations across multiple categories!

Category	Visualizations
Likes & Ratings	Histogram • Donut chart • Scatter plot • Stat tiles
Diary Activity	Calendar heatmap • Line charts • Weekday bars
Genres & Themes	Bar charts • Radar charts
Decades	Radar chart
Obscurity Metrics	Histogram • Rarest films list
Runtime Analysis	Bar chart
People & Studios	Bar charts • Radar chart
Languages & Countries	Bar charts • Radar charts

Installation & Usage

Option 1: Use the Live Web App

Visit memento-0fke.onrender.com

Scraping by username is rate limited on hosted servers, so uploading your data export is the more reliable route there. Running locally avoids this entirely.

Option 2: Run with Docker

1. Clone the repository:

   git clone https://github.com/danielkwan-dev/memento.git
   cd memento

2. Start everything:

   docker compose up

3. Visit localhost:8080

Option 3: Run Locally

1. Start Postgres:

   docker compose up -d postgres

2. Run the API and the worker:

   go run ./cmd/api
   go run ./cmd/worker

3. Run the frontend!

   cd web && npm install && npm run dev

Data Privacy

• The app only accesses the public Letterboxd data on your profile
• Your ratings and diary entries can be deleted at any time from the dashboard
• Film details are cached and shared between users, so popular films are only fetched once

Tech Stack

Backend:
Go • Postgres • goquery

Frontend & Visualizations:
React • TypeScript • Recharts • Tailwind

Infrastructure:
Docker • GitHub Actions • Render • Neon

The API image also serves the built React app, so the whole web tier is one deploy with no CORS to configure.

Notes

A few things worth knowing if you run this yourself:

• Letterboxd has no public API, so requests go through a client that replays real browser TLS fingerprints
• Rate limits are per-IP and cumulative, so a long scrape can earn a temporary block that clears on its own
• Uploading your export is more reliable than scraping for large accounts, since it skips the paginated profile pages
• Running it locally works best. Letterboxd treats a home connection far more leniently than a datacenter one, so the hosted demo gets rate limited where a local run does not — docker compose up and everything works
• The free hosting tier sleeps when idle, so the first run after a quiet spell waits a few seconds to wake up (the UI shows this as a real 'waking' phase rather than an unexplained pause)
• The database connection must be direct, not pooled: progress streaming uses LISTEN/NOTIFY, and PgBouncer in transaction mode (what most managed poolers run) silently drops it

Running the tests:

go test ./...

docker compose up -d postgres
MEMENTO_TEST_DATABASE_URL=postgres://memento:memento@localhost:5432/memento?sslmode=disable go test ./...