Fuzzy

Fuzzy is a package that provides algorithms that are used to see how similar strings are.

One to two paragraph statement about your product and what it does.

Installation

go get github.com/roadsigns/fuzzy

Algorithms available

Match

Match checks to see if the two strings are a partial match and if so return true, if they aren't then it returns a false. Match is case-sensitive.

import "github.com/roadsigns/fuzzy"

fuzzy.Match("wtrmln", "watermelon")

Levenshtein

Levenshtein allows us to calculate the edit distance between the source and the target. Additional information for this algorithm can be found https://en.wikipedia.org/wiki/Levenshtein_distance

import "github.com/roadsigns/fuzzy"

fuzzy.Levenshtien("kitten", "sitting")

Jaro

The Jaro similarity algorithm is a measure of the similarity between two strings. It is commonly used to calculate the similarity between two strings of text. Additional information for this algorithm can be found https://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance#Jaro_Similarity

import "github.com/roadsigns/fuzzy"

fuzzy.Jaro("gorilla", "guerrilla")

Soundex

The Soundex algorithm is a phonetic algorithm for indexing words by their pronunciation. Additional information for this algorithm can be found https://en.wikipedia.org/wiki/Soundex

import "github.com/roadsigns/fuzzy"

fuzzy.Soundex("Smith")  // S530
fuzzy.Soundex("Smythe") // S530

Sørensen–Dice coefficient

The Sørensen–Dice coefficient algorithm is a similarity coefficient that is used to compare the similarity of two strings. Additional information for this algorithm can be found https://en.wikipedia.org/wiki/S%C3%B8rensen%E2%80%93Dice_coefficient

import "github.com/roadsigns/fuzzy"

fuzzy.SorensenDice("elon musk", "colon musk")

Q-Gram

The Q-Gram algorithm is a similarity algorithm that It does this by dividing each string into substrings of length Q and then comparing the substrings to determine how many of them are the same in both strings. Additional information for this algorithm can be found https://en.wikipedia.org/wiki/N-gram

import "github.com/roadsigns/fuzzy"

fuzzy.QGram("John Jones", "Jon Jones", 3)