cb372/dusty-study

Anagram helper. Rust, Yew, WASM, deployed to Netlify.

Dusty Study - an anagram solver

Initial setup

To install everything you need and confirm that the app builds, run:

./build.sh

This is the script that Netlify runs to build the app.

Running the app locally

To serve the app using Trunk, run:

./serve.sh

Every time you make a change, Trunk will recompile and live-reload the page.

Deploying to Netlify

Just push main to GitHub.

Repo overview

Frontend

The frontend app is implemented with Yew. The relevant files are:

• ./Cargo.toml
• ./index.html
• ./src/

The Yew app is built using Trunk. The output files are written to the dist/ directory.

Backend

The backend is a single Netlify function implemented in Rust.

It accepts a query string as input, looks up a list of matching anagrams in its database, and returns them in its response.

The relevant files are:

• netlify/functions/solve/

Dataset

The dataset/ directory contains a Bash script and a Rust script for building the database of anagrams.

The scripts take a kaikki.org dictionary file as input and transform them into an anagram dataset. The result is written as a JSON file inside the backend's src directory.

To build the dataset:

1. Run ./download-dictionary.sh inside the dataset directory. This will download the dictionary file. It is not stored in git because it is > 1 GB.

2. Run ./extract-words.sh to do some preprocessing.

3. Run cargo run --release to generate the anagram dataset.