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StringDistances.jl
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The package is registered in the [`General`](https://github.com/JuliaRegistries/General) registry and so can be installed at the REPL with `] add StringDistances`.
## Evaluate
The function `evaluate` returns the distance between two strings. Its syntax is:
To compute the distance between two strings (or between two iterators), you can use one of these two syntaxes:
```julia
evaluate(dist, s1, s2)
dist()(s1, s2)
```
where `s1` and `s2` can be any iterator with a `length` method (e.g. `AbstractString`, `GraphemeIterator`, `AbstractVector`...), and `dist` is one of the following distances:
where `dist` is one of the following distances::
- Edit Distances
- [Jaro Distance](https://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance) `Jaro()`
@ -33,28 +34,20 @@ where `s1` and `s2` can be any iterator with a `length` method (e.g. `AbstractSt
- [TokenSet](http://chairnerd.seatgeek.com/fuzzywuzzy-fuzzy-string-matching-in-python/) adjusts for differences in word orders and word numbers by comparing the intersection of two strings with each string.
- [TokenMax](http://chairnerd.seatgeek.com/fuzzywuzzy-fuzzy-string-matching-in-python/) combines scores using the base distance, the `Partial`, `TokenSort` and `TokenSet` modifiers, with penalty terms depending on string lengths.
Some examples:
A good distance to match strings composed of multiple words (like addresses) is `TokenMax(Levenshtein())` (see [fuzzywuzzy](http://chairnerd.seatgeek.com/fuzzywuzzy-fuzzy-string-matching-in-python/)
```julia
evaluate(Jaro(), "martha", "marhta")
evaluate(Winkler(Jaro()), "martha", "marhta")
evaluate(QGram(2), "martha", "marhta")
evaluate(Winkler(QGram(2)), "martha", "marhta")
evaluate(Levenshtein(), "martha", "marhta")
evaluate(Partial(Levenshtein()), "martha", "marhta")
evaluate(Jaro(), "martha", "marhta")
evaluate(TokenSet(Jaro()), "martha", "marhta")
evaluate(TokenMax(RatcliffObershelp()), "martha", "marhta")
```
evaluate(QGram(2), "martha", "marhta")
evaluate(Winkler(Jaro()), "martha", "marhta")
Alternatively, each distance can be used as a callable to call the evaluate function of each metric or modified metric, for example:
```julia
Jaro()("martha", "marhta")
Winkler(Jaro())("martha", "marhta")
Levenshtein()("martha", "marhta")
QGram(2)("martha", "marhta")
Winkler(Jaro())("martha", "marhta")
```
A good distance to match strings composed of multiple words (like addresses) is `TokenMax(Levenshtein())` (see [fuzzywuzzy](http://chairnerd.seatgeek.com/fuzzywuzzy-fuzzy-string-matching-in-python/)).
## Compare
The function `compare` is defined as 1 minus the normalized distance between two strings. It always returns a number between 0 and 1: a value of 0 means completely different and a value of 1 means completely similar.
```julia