rapidfuzz 0.1.1
rapidfuzz: ^0.1.1 copied to clipboard
A dart port of the rapidfuzz library, for fuzzy-matching strings, and calculating the edit distance between strings.
rapidfuzz #
A Flutter port of the rapidfuzz library. Note that results may differ from the original implementation due to minor differences in the implementation.
Usage #
Installation #
flutter pub add rapidfuzz
Import #
import 'package:rapidfuzz/rapidfuzz.dart';
Algorithms #
Ratio #
Calculates a Levenshtein simple ratio between the strings This indicates a measure of similarity
ratio("this is a test", "this is a test!") // 96.55172413793103
Partial Ratio #
Inconsistent substrings lead to problems in matching. This ratio uses a heuristic called "best partial" for when two strings are of noticeably different lengths.
partialRatio("this is a test", "this is a test!") // 100.0
Token Sort Ratio #
Find all alphanumeric tokens in the string and sort these tokens and then take ratio of resulting joined strings.
ratio("fuzzy wuzzy was a bear", "wuzzy fuzzy was a bear") // 90.90908813476562
tokenSortRatio("fuzzy wuzzy was a bear", "wuzzy fuzzy was a bear") // 100
Token Set Ratio #
Splits the strings into tokens and computes intersections and remainders between the tokens of the two strings. A comparison string is then built up and is compared using the simple ratio algorithm.
tokenSortRatio("fuzzy was a bear", "fuzzy fuzzy was a bear") // 83.8709716796875
tokenSetRatio("fuzzy was a bear", "fuzzy fuzzy was a bear") // 100
Weighted Ratio #
Calculates a weighted ratio between [s1] and [s2] using the best option from the above fuzzy matching algorithms
weightedRatio("The quick brown fox jimps ofver the small lazy dog", "the quick brown fox jumps over the small lazy dog") // 96.96969696969697
Extraction #
It is often more useful to extract the most similar strings from a list of strings than to calculate the ratio between two strings.
extractOne(
query: 'cowboys',
choices: [
'Atlanta Falcons',
'New York Jets',
'New York Giants',
'Dallas Cowboys'
],
cutoff: 10,
) // (string Dallas Cowboys, score: 90.0, index: 3)
extractTop(
query: 'goolge',
choices: [
'google',
'bing',
'facebook',
'linkedin',
'twitter',
'googleplus',
'bingnews',
'plexoogl'
],
limit: 4,
cutoff: 50,
) // [(string googleplus, score: 90.0, index: 5), (string google, score: 83.33333333333334, index: 0)]
extractAllSorted(
query: 'goolge',
choices: [
'google',
'bing',
'facebook',
'linkedin',
'twitter',
'googleplus',
'bingnews',
'plexoogl'
],
cutoff: 10,
) // [(string googleplus, score: 90.0, index: 5), (string google, score: 83.33333333333334, index: 0), (string plexoogl, score: 42.85714285714286, index: 7), (string bingnews, score: 28.57142857142857, index: 6), (string linkedin, score: 28.57142857142857, index: 3), (string facebook, score: 28.57142857142857, index: 2), (string bing, score: 22.5, index: 1), (string twitter, score: 15.384615384615385, index: 4)]
extractAll(
query: 'goolge',
choices: [
'google',
'bing',
'facebook',
'linkedin',
'twitter',
'googleplus',
'bingnews',
'plexoogl'
],
cutoff: 10,
) // [(string google, score: 83.33333333333334, index: 0), (string bing, score: 22.5, index: 1), (string facebook, score: 28.57142857142857, index: 2), (string linkedin, score: 28.57142857142857, index: 3), (string twitter, score: 15.384615384615385, index: 4), (string googleplus, score: 90.0, index: 5), (string bingnews, score: 28.57142857142857, index: 6), (string plexoogl, score: 42.85714285714286, index: 7)]
Extract using any a list of any type #
All extract
methods can receive List<T>
and return List<ExtractedResult<T>>
class TestContainer {
final String innerVal;
TestContainer(this.innerVal);
}
extractOne<TestContainer>(
query: 'cowboys',
choices: [
'Atlanta Falcons',
'New York Jets',
'New York Giants',
'Dallas Cowboys'
].map((e) => TestContainer(e)).toList(),
cutoff: 10,
getter: (x) => x.innerVal
).toString(); // (string Dallas Cowboys, score: 90.0, index: 3)