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rethinkdb-boundaries

v1.0.14

Published

Downloads, converts, and indexes US Census TIGER data representing all boundaries in the United States to RethinkDB.

Downloads

42

Readme

rethinkdb-boundaries NPM version Downloads

Downloads, converts, and indexes US Census TIGER data representing all boundaries in the United States to RethinkDB.

By default, this imports the boundaries of every state and incorporated place (~30K boundaries). Takes quite a bit of time depending on your internet speed.

Basically makes it easy to apply a city/state/whatever geo-lens on top of arbitrary data, making queries like these simple:

  • What state and city is this location in?
  • What states and cities does this line pass through?
  • Get all documents that have a line passing through New York, Boston, and Providence
  • Subscribe to all new documents created in Boston, MA
  • Get all documents created within New York City
  • Get all documents created outside of a city

Still a work in progress, more functionality and power being added soon!

Install

npm install rethinkdb-boundaries -g

CLI

$ rethinkdb-boundaries --help
Usage
  $ rethinkdb-boundaries

Options
  --host   Set the RethinkDB host name (default: 'localhost')
  --port   Set the RethinkDB port (default: '29015')
  --db     Set the database name (default: 'test')
  --table  Set the table name (default: 'Boundary')

Examples
  $ rethinkdb-boundaries --db my_app

$ rethinkdb-boundaries --db my_app
Establishing connections:
  -- US Census Bureau @ ftp2.census.gov
  -- RethinkDB @ my_app
Processing 1 boundary file for STATE
  -- Parsed /geo/tiger/TIGER2015/STATE/tl_2015_us_state.zip, inserting 56 boundaries now...
Processing 56 boundary files for PLACE
  -- Parsed /geo/tiger/TIGER2015/PLACE/tl_2015_01_place.zip, inserting 585 boundaries now...
  -- Parsed /geo/tiger/TIGER2015/PLACE/tl_2015_02_place.zip, inserting 355 boundaries now...
  -- Parsed /geo/tiger/TIGER2015/PLACE/tl_2015_04_place.zip, inserting 451 boundaries now...

( and so on... )

TODO:

Want to help out? Here's what I'm thinking about adding:

  • Query sugar
    • Example: Replace r.table('geo').filter({type: 'place', name: 'New York City'}) with geo.place('New York City') in queries
  • Options to import zip codes and more data
  • Store more city meta-information from census data
  • Sample queries for docs!