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Finds degree of similarity between two strings, based on Dice's Coefficient, which is mostly better than Levenshtein distance.

string-similarity #

Finds degree of similarity between two strings, based on Dice's Coefficient, which is mostly better than Levenshtein distance.

📄 Table of Contents #

🎮 Usage #

In your code:

import  'package:string_similarity/string_similarity.dart';

var similarity = 'french'.similarityTo('quebec'); // or StringSimilarity.compareTwoStrings('french', 'quebec');

var matches = 'healed'.bestMatch(['edward', 'sealed', 'theatre']); // or StringSimilarity.findBestMatch('healed', ['edward', 'sealed', 'theatre']);

📚 API #

'string'.similarityTo(other) #

Returns a fraction between 0 and 1, which indicates the degree of similarity between the two strings. 0 indicates completely different strings, 1 indicates identical strings. The comparison is case and diacritic sensitive.

Arguments

  • other (String): The second string

Order does not make a difference.

Returns

(double): A fraction from 0 to 1, both inclusive. Higher number indicates more similarity.

Examples

'healed'.similarityTo('sealed'); // → 0.8

'france'.similarityTo('FrancE'); // → 0.6

'Olive-green table for sale, in extremely good condition.'.similarityTo('For sale: table in very good  condition, olive green in colour.'); // → 0.6060606060606061

or you can use the StringSimilarity.compareTwoStrings static method

StringSimilarity.compareTwoStrings('healed', 'sealed'); // → 0.8

'string'.bestMatch(targetStrings) #

Compares mainString against each string in targetStrings.

Arguments

  • targetStrings (List<String>): Each string in this array will be matched against the main string.

Returns

(BestMatch): An object with a ratings property, which gives a similarity rating for each target string, a bestMatch property, which specifies which target string was most similar to the main string, and a bestMatchIndex property, which specifies the index of the bestMatch in the targetStrings array.

Examples

'Olive-green table for sale, in extremely good condition.'.bestMatch([
  'For sale: green Subaru Impreza, 210,000 miles',
  'For sale: table in very good condition, olive green in colour.',
  'Wanted: mountain bike with at least 21 gears.',
]);
// →
{ ratings:
   [ { target: 'For sale: green Subaru Impreza, 210,000 miles',
       rating: 0.2558139534883721 },
     { target: 'For sale: table in very good condition, olive green in colour.',
       rating: 0.6060606060606061 },
     { target: 'Wanted: mountain bike with at least 21 gears.',
       rating: 0.1411764705882353 } ],
  bestMatch:
   { target: 'For sale: table in very good condition, olive green in colour.',
     rating: 0.6060606060606061 },
  bestMatchIndex: 1
}

or you can use the StringSimilarity.findBestMatch static method

StringSimilarity.findBestMatch('Olive-green table for sale, in extremely good condition.', [
  'For sale: green Subaru Impreza, 210,000 miles',
  'For sale: table in very good condition, olive green in colour.',
  'Wanted: mountain bike with at least 21 gears.',
]);

🔮 Credit #

based on 'string-similarity' Javascript project : https://github.com/aceakash/string-similarity

thanks @shinayser

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Publisher

verified publisherjeremylandon.com

Finds degree of similarity between two strings, based on Dice's Coefficient, which is mostly better than Levenshtein distance.

Repository (GitHub)
View/report issues

License

MIT (LICENSE)

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