Caverphone2 Algorithm in Python 3+

This repository is purely for reference and is illustrative in it is purpose. This is one of the many ways of implementing this algorithm.

This project illustrates an implementation of the Coverphone2 Algorithm in Python. The Caverphone2 Algorithm is a phonetic algorithm that can match words or names in a "commonly recogniable form". The Caversham Project at the University of Otago is the source of the original algorithm and optimised for accents present in the southern part of the city of Dunedin, New Zealand.

Examples would be Tedder and Tudor, or ready and radio, as they "sound alike" when spelled differenly.

IMPORTANT

This algorithm was authored to be readable as to the steps to achieve consistant and expected Caverphone2 codes given the specification provided. This code can be refactored to be more compact and performant if needed.

Prerequisites

Before you continue, ensure you have met the following requirements:

• Python 3 installed
• PyTest installed (to run the unit tests if need be)

Running / Testing

• Run pytest from the command line

Notes

• This implementaton uses standard Python string maninulation vs REGEX as to apply the basics needed to create codes. While REGEX would be easier to write, a vanilla string manipulation implementation illustrates some of the intracacies of the algorithm, and may perform better
• This repository is heavily commented to provide context as to what and why, if in VS Code feel free to collapse all comments if they are obtrusive
  • On Mac -> Press ⌘ + K then ⌘ + /
  • On Windows & Linux -> Press Ctrl + K then Ctrl + /
• The Caverphone2 validation words are from various sites across the web, there will be more added and augmentation of the algorithm when edge cases are found.

Try / Ask

• authoring this implementation or parts of it using REGEX, observe the performance at scale (try 10,000 iterations or more)
• try horse, hoarse and why horace doesn't match? Which phonteic algorithm will match all three against eachother