# Text Metrics

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The library provides efficient implementations of various strings metric
algorithms. It works with strict `Text` values.

The current version of the package implements:

* [Levenshtein distance](https://en.wikipedia.org/wiki/Levenshtein_distance)
* [Normalized Levenshtein distance](https://en.wikipedia.org/wiki/Levenshtein_distance)
* [Damerau-Levenshtein distance](https://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance)
* [Normalized Damerau-Levenshtein distance](https://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance)
* [Hamming distance](https://en.wikipedia.org/wiki/Hamming_distance)
* [Jaro distance](https://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance)
* [Jaro-Winkler distance](https://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance)
* [Overlap coefficient](https://en.wikipedia.org/wiki/Overlap_coefficient)
* [Jaccard similarity coefficient](https://en.wikipedia.org/wiki/Jaccard_index)

## Comparison with the `edit-distance` package

There is [`edit-distance`](https://hackage.haskell.org/package/edit-distance) package whose scope overlaps with the scope of
this package. The differences are:

* `edit-distance` allows to specify costs for every operation when
  calculating Levenshtein distance (insertion, deletion, substitution, and
  transposition). This is rarely needed though in real-world applications,
  IMO.

* `edit-distance` only provides Levenshtein distance, `text-metrics` aims to
  provide implementations of most string metrics algorithms.

* `edit-distance` works on `Strings`, while `text-metrics` works on strict
  `Text` values.

## Implementation

Although we originally used C for speed, currently all functions are pure
Haskell tuned for performance. See [this blog post](https://markkarpov.com/post/migrating-text-metrics.html) for more info.

## License

Copyright © 2016–2017 Mark Karpov

Distributed under BSD 3 clause license.