Load data from TIGER ADDRFEAT address ranges into Elasticsearch for fast geocoding
using address interpolation and Python 3's asyncio, as well as docker-compose
to make running the setup easier.
The Elasticsearch TIGER loading script reads directly from S3 into memory, but because
it uses boto3, you'll need valid AWS credentials set up through aws-cli or
exposed on your machine as environment variables. The operations we're running
won't have a cost for anyone reading the data, but boto3 requires valid credentials.
Currently, there's an S3 bucket with this information (viewer here),
but you can create one with a similar setup by running the create_tiger_s3.sh
on any machine with aws-cli installed.
To run locally, just run:
docker-compose build
docker-compose up
If you've successfully built and started the containers as shown above, you should be able to start loading TIGER data with:
docker-compose run geocoder es_tiger_loader.py WA
Where WA is the two letter state abbreviation for the state you want to load
TIGER data from.
Alternatively, to restrict the search area more, you can enter the five digit FIPS code for a state and county to load just that county. You can find all county FIPS codes at this Census link. For Cook County, IL:
docker-compose run geocoder es_tiger_loader.py 17031
To start the geocoder itself (which can run into issues if it's started at the same time as the other containers), run:
CSV: docker-compose run geocoder run.py -s WA ./data/input_file.csv
Postgres: docker-compose run geocoder run.py -s WA ./config.json