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US Place Sampler

This project runs a webapp to allow fast sampling of US addresses within arbitrary (but usually CENSUS-based) geometries.

Usage / development

There are four parts of the stack:

  1. The PostGIS database
  2. A "work box" VM that has all the CLI tools for working with the DB
  3. The Python API
  4. The UI

The full stack can be run with:

docker compose up --build

The app will be served at http://localhost/. You will need to ingest some TIGER and OpenAddresses data to use it. (See below!)

PostGIS

We use Postgres with the PostGIS extension for geospatial analysis.

In addition, we use the TIGER extension for PostGIS to provide geographic context.

You can run a database locally with docker-compose.

Work Box ctl

See the scripts in ./ctl/ for more info.

For development, it's useful to just run the ctl and db VMs in docker.

docker compose up db ctl --build

Ingesting data (only need to do once)

When you are setting up a new PostGIS database, you will need to ingest data from TIGER.

We provide a container in the docker-compose environment to make this easy.

# Get a shell in the controller container:
docker exec -it usps_ctl_1 /bin/bash

# Run TIGER ingestion script.
# Here I'm only pulling Vermont data; you can pass any state here, or `all`.
./init_tiger_data.sh VT

# Run OpenAddresses ingestion script.
# Again, only doing one small (but mighty) state for demoing.
./init_addr_data.sh VT

This will begin downloading and ingesting TIGER data into your database. Ingesting the entire country will take a long time to run (many hours, even days), so make sure you have a snack handy.

API

See the api/README.

UI

See the app/README.

Production

You can add a supplemental docker-compose.prod.yml to expand the cluster for deployment.

Tips:

  1. Use a better nginx config (with SSL)
  2. certbot/cerbot can handle certificates
  3. The postgresql.conf should be tuned for your hardware
  4. The services.db.shm_size might need to be increased for large volumes of data
  5. Use production-ready secrets as needed
  6. Configure the volumes in docker compose to be persistent on a disk (preferablly SSD for Postgres data!)