README

The PHP package for calculate similarity and Levenshtein distance between strings. Realizes fuzzy search using similar_text() and levenshtein() functions. Easy to use and safe for multibyte encodings (UTF-8).

Requirements

• PHP >= 5.6

Installation

composer require nullform/fuzzio

Usage examples

use \Nullform\Fuzzio\Fuzzio;
use \Nullform\Fuzzio\FuzzioString;

$needle = 'john'; // Reference string
$haystack = ['jon', 'johns', 'jane', 'janie']; // Array of strings

$fuzzio = new Fuzzio($needle, $haystack);

// Get all strings from $haystack with calculated similarity and Levenshtein distance
$all = $fuzzio->get(); // FuzzioString[]

// Get strings with similarity >= 80% and Levenshtein distance <= 1
$filtered = $fuzzio->get(80, 1); // FuzzioString[]

// Get strings with Levenshtein distance <= 1
$filtered = $fuzzio->get(null, 1); // FuzzioString[]

// With max similarity value
$allClosest = $fuzzio->getClosest(); // FuzzioString[]

// One (first) with max similarity value
$closestOne = $fuzzio->getClosestOne(); // FuzzioString

echo $closestOne; // johns
echo $closestOne->getString(); // johns
echo $closestOne->getSimilarity(); // 88.888888888889
echo $closestOne->getLevenshteinDistance(); // 1

echo $fuzzio->getMaxSimilarity(); // 88.888888888889

// Is there an exact match in the collection
$fuzzio->hasExactMatch(); // false

// Add string to haystack
$fuzzio->addToHaystack(['julie']);

// Remove strings from haystack
$fuzzio->removeFromHaystack(['janie', 'julie']);

You can set the similarity threshold and the Levenshtein distance threshold for filtering results:

use \Nullform\Fuzzio\Fuzzio;

$needle = 'john'; // Reference string
$haystack = ['jon', 'johns', 'jane', 'janie']; // Array of strings

$fuzzio = new Fuzzio($needle);

// Set max Levenshtein distance threshold
$fuzzio->setMaxLevenshteinDistanceThreshold(1);

// Set min similarity threshold
$fuzzio->setMinSimilarityThreshold(80);

// Set array of strings to calculate similarity
$fuzzio->setHaystack($haystack);

// Get strings with similarity >= 80% and Levenshtein distance <= 1
$collection = $fuzzio->get();

You can set a normalizer for more predictable calculations:

use \Nullform\Fuzzio\Fuzzio;

$needle = 'John'; // Reference string
$haystack = ['Jon ', 'Johns', 'JANE', 'Janie']; // Array of strings

$normalizer = function ($string) {
    return trim(strtolower($string));
};

$fuzzio = new Fuzzio($needle);

// Normalizer for $needle and $haystack
$fuzzio->setNormalizer($normalizer);
// Set array of strings to calculate similarity
$fuzzio->setHaystack($haystack);

// Or like this
$fuzzio = new Fuzzio($needle, $haystack, $normalizer);

echo $fuzzio->getNeedle(); // John
echo $fuzzio->getNormalizedNeedle(); // john

// One with max similarity
$closest = $fuzzio->getClosestOne();

echo $closest; // Johns
echo $closest->getString(); // Johns
echo $closest->getNormalizedString(); // johns
echo $closest->getSimilarity(); // 88.888888888889
echo $closest->getLevenshteinDistance(); // 1

Methods

Fuzzio

• Fuzzio::__construct(string $needle, string[]|null $haystack = null, callable|null $normalizer = null)
• Fuzzio::getNeedle(): string
• Fuzzio::getNormalizedNeedle(): string
• Fuzzio::setHaystack(string[] $haystack): Fuzzio
• Fuzzio::getHaystack(): string[]
• Fuzzio::getNormalizedHaystack(): string[]
• Fuzzio::addToHaystack(string[] $strings): Fuzzio
• Fuzzio::removeFromHaystack(string[] $strings): Fuzzio
• Fuzzio::hasExactMatch(): bool
• Fuzzio::get(float|null $minSimilarity = null, int|null $maxLevenshteinDistance = null): FuzzioString[]
• Fuzzio::getClosest(): FuzzioString[]
• Fuzzio::getClosestOne(): FuzzioString
• Fuzzio::getMaxLevenshteinDistanceThreshold(): int|null
• Fuzzio::setMaxLevenshteinDistanceThreshold(int $threshold): Fuzzio
• Fuzzio::getMinSimilarityThreshold(): float|null
• Fuzzio::setMinSimilarityThreshold(float $threshold): Fuzzio
• Fuzzio::getMaxSimilarity(): float|null
• Fuzzio::getMinLevenshteinDistance(): int|null
• Fuzzio::setNormalizer(callable|null $normalizer): Fuzzio

FuzzioString

• FuzzioString::getString(): string
• FuzzioString::getNormalizedString(): string
• FuzzioString::getSimilarity(): float
• FuzzioString::getLevenshteinDistance(): int
• FuzzioString::__toString(): string