match-mate

match-mate

A Ruby gem for matching demographics data.

Installation

---

Prerequisites

Python / FuzzyWuzzy

match-mate uses FuzzyWuzzy, a Python library that uses Levenshtein Distance to calculate the differences between sequences. It has some features not currently found in any Ruby gems, particularily the ability to ignore word order and duplicated words. Thus, it currently requires Python version 2.7 or higher, as well as

To install FuzzyWuzzy:

On Ubuntu/Debian

sudo apt install python python-pip
pip install fuzzywuzzy[speedup]

On CentOS/RHEL

sudo yum install python python-pip
pip install fuzzywuzzy[speedup]

On MacOS

Python comes pre-installed on MacOS.

pip install fuzzywuzzy[speedup]

libpostal

match-mate uses ruby_postal, a gem that provides Ruby bindings to libpostal for fast street address parsing and normalization.

Before you install, make sure you have the following prerequisites:

On Ubuntu/Debian

sudo apt-get install curl autoconf automake libtool pkg-config

On CentOS/RHEL

sudo yum install curl autoconf automake libtool pkgconfig

On MacOS

brew install curl autoconf automake libtool pkg-config

Then to install the C library:

git clone https://github.com/openvenues/libpostal
cd libpostal
./bootstrap.sh
./configure --datadir=[...some dir with a few GB of space...]
make -j4
sudo make install

# On Linux it's probably a good idea to run
sudo ldconfig

Install the Gem

To install using Bundler:

gem 'match-mate', github: 'combinaut/match-mate'

Configuration

---

Create an initializer and configure your Python path and match weights

MatchMate.configure do |config|
  config.python_path = '/usr/local/bin/python'
  config.address_weights =  {
    road: {
      weight: 30,
      threshold: 80
    },
    unit: {
      weight: 2,
      threshold: 80
    },
    postcode: {
      weight: 30,
      threshold: 100
    },
    city: {
      weight: 8,
      threshold: 80
    },
    house_number: {
      weight: 30,
      threshold: 100
    }
  }
end

Usage

Address Matcher

Compare two addresses and get similarity score:

address = MatchMate::Address.new "742 Evergreen Terrace Springfield IL 62704"
other_address = MatchMate::Address.new "742 Evergreen Springfield IL 62704"
matcher = MatchMate::AddressMatcher.new(address, other_address)
matcher.score
# => 100