this_or_that
| Crates.io | this_or_that |
| lib.rs | this_or_that |
| version | 0.1.1 |
| created_at | 2026-01-24 15:18:08.720181+00 |
| updated_at | 2026-01-24 15:49:05.449402+00 |
| description | Ratings website that uses Chess style rankings. |
| homepage | https://crates.io/crates/this-or-that |
| repository | https://github.com/ali-raheem/this-or-that |
| max_upload_size | |
| id | 2066840 |
| size | 1,490,629 |
Ali Raheem (ali-raheem)
documentation
README
This or That
A generic ELO-based ranking webapp where users vote on head-to-head matchups. Items gain or lose rating points based on votes, creating a chess-style ranking system that's fairer than simple star ratings.
You can see it in action here This or That Rocks.
Features
- Head-to-head voting interface with keyboard shortcuts
- ELO rating system with configurable k-factor
- Top and bottom rankings pages
- Individual item detail pages
- Session-based vote validation (prevents replay attacks)
- Fully configurable for any item type (movies, albums, games, etc.)
Quick Start
Prerequisites
- Rust (1.70+)
- SQLite
Installation
-
Clone the repository
-
Create configuration:
cp Rocket.toml.example Rocket.toml # Edit Rocket.toml with your settings -
Initialize the database:
mkdir -p data sqlite3 data/movies.db < schema.sql -
Populate with items (see example/TMDB.md for movie data)
-
Run the server:
cargo run
Configuration
See Rocket.toml.example for all options. Key settings:
| Option | Description |
|---|---|
name |
Site name displayed in header |
items |
What you're ranking (e.g., "Movie", "Album") |
k |
ELO k-factor: 16 (slow), 32 (standard), 64 (fast) |
image_path_base_url |
Base URL prepended to image paths |
default_ranking_count |
Items shown in rankings |
Keyboard Shortcuts
| Key | Action |
|---|---|
1 or ← |
Vote for left item |
2 or → |
Vote for right item |
Space |
Skip matchup |
Examples
The example/ directory contains scripts for populating the database:
- TMDB - Fetch movies from The Movie Database (documentation)
Use of AI statement
The Rust backend and code of this project is all artisanal hand coded, the front end is heavily edited by AI. Documentation like the README is also largely written based on notes by AI.
License
MIT License