index.community/README.md

fediverse.space 🌐

The map of the fediverse that you always wanted.

Requirements

• For everything:
  • Docker
  • Docker-compose
• For the scraper + API:
  • Python 3
• For laying out the graph:
  • Java
• For the frontend:
  • Yarn

Running it

Backend

• cp example.env .env and modify environment variables as required
• docker-compose build
• docker-compose up -d django
  • if you don't specify django, it'll also start gephi which should only be run as a regular one-off job
  • to run in production, run caddy rather than django

Frontend

• cd frontend && yarn install
• yarn start

Commands

Backend

After running the backend in Docker:

• docker-compose exec web python manage.py scrape scrapes the fediverse
  • It only scrapes instances that have not been scraped in the last 24 hours.
  • By default, it'll only scrape 50 instances in one go. If you want to scrape everything, pass the --all flag.
• docker-compose exec web python manage.py build_edges aggregates this information into edges with weights
• docker-compose run gephi java -Xmx1g -jar build/libs/graphBuilder.jar lays out the graph

To run in production, use docker-compose -f docker-compose.yml -f docker-compose.production.yml instead of just docker-compose.

An example crontab:

# crawl 50 stale instances (plus any newly discovered instances from them)
# the -T flag is important; without it, docker-compose will allocate a tty to the process
15,45 * * * * docker-compose -f docker-compose.yml -f docker-compose.production.yml exec -T django python manage.py scrape
# build the edges based on how much users interact
15 3 * * * docker-compose -f docker-compose.yml -f docker-compose.production.yml exec -T django python manage.py build_edges
# layout the graph
20 3 * * * docker-compose -f docker-compose.yml -f docker-compose.production.yml run gephi java -Xmx1g -jar build/libs/graphBuilder.jar

Frontend

• yarn build to create an optimized build for deployment