This is a pure Ruby implementation of a BK-Tree (https://signal-to-noise.xyz/post/bk-tree/) which can be used for any sort of quick comparison for hamming distances. Usually this is for something like spell check or auto suggestions, but it can also be utilized for image similarity search as well.
It runs completely in memory, which makes it very quick (even at 500,000 words), this takes up a little space, taking about 4MB for 400,000 words. Building the graph taking about 35 seconds for 400k elements and about 1-2 seconds to search depending on the length of the search query (longer query is longer time).
Eventually it'd be faster to rewrite this in C and toss a Ruby wrapper over it, but for now this will work quite well for what we want it to.
Add this line to your application's Gemfile:
gem 'zelkova'And then execute:
$ bundle install
Or install it yourself as:
$ gem install zelkova
TODO: Write usage instructions here
After checking out the repo, run bin/setup to install dependencies. Then, run rake test to run the tests. You can also run bin/console for an interactive prompt that will allow you to experiment.
To install this gem onto your local machine, run bundle exec rake install. To release a new version, update the version number in version.rb, and then run bundle exec rake release, which will create a git tag for the version, push git commits and tags, and push the .gem file to rubygems.org.
Bug reports and pull requests are welcome on GitHub at https://github.com/[USERNAME]/zelkova. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the code of conduct.
The gem is available as open source under the terms of the MIT License.
Everyone interacting in the Zelkova project's codebases, issue trackers, chat rooms and mailing lists is expected to follow the code of conduct.