fuzzywuzzy 0.1.6
fuzzywuzzy: ^0.1.6 copied to clipboard
An implementation of the popular fuzzywuzzy package in Dart, to suit all your fuzzy string matching/searching needs!
FuzzyWuzzy #
This is a Dart port of the popular FuzzyWuzzy python package. This algorithm uses Levenshtein distance to calculate similarity between strings.
I personally needed to use this for my own search algorithms, and there weren't any packages as good as my experience with FuzzyWuzzy was, so here we are. Enjoy!
- Just one dependency (collection).
- Pure Dart implementation of the superfast python-Levenshtein.
- Simple to use.
- Lightweight.
- Massive props to the folks over at seatgeek for coming up with the algorithm.
Get started #
Add dependency #
dependencies:
fuzzywuzzy: 0.1.6 # latest version
Usage #
First, import the package
import 'package:fuzzywuzzy/fuzzywuzzy.dart'
Simple ratio #
ratio("mysmilarstring", "myawfullysimilarstirng") // 72
ratio("mysmilarstring", "mysimilarstring") // 97
Partial ratio #
partialRatio("similar", "somewhresimlrbetweenthisstring") // 71
Token sort ratio #
tokenSortPartialRatio("order words out of", "words out of order") // 100
tokenSortRatio("order words out of"," words out of order") // 100
Token set ratio #
tokenSetRatio("fuzzy was a bear", "fuzzy fuzzy fuzzy bear") // 100
tokenSetPartialRatio("fuzzy was a bear", "fuzzy fuzzy fuzzy bear") // 100
Weighted ratio #
weightedRatio("The quick brown fox jimps ofver the small lazy dog", "the quick brown fox jumps over the small lazy dog") // 97
Extract #
extractOne(
query: 'cowboys',
choices: [
'Atlanta Falcons',
'New York Jets',
'New York Giants',
'Dallas Cowboys'
],
cutoff: 10,
) // (string Dallas Cowboys, score: 90, index: 3)
extractTop(
query: 'goolge',
choices: [
'google',
'bing',
'facebook',
'linkedin',
'twitter',
'googleplus',
'bingnews',
'plexoogl'
],
limit: 4,
cutoff: 50,
) // [(string google, score: 83, index: 0), (string googleplus, score: 75, index: 5)]
extractAllSorted(
query: 'goolge',
choices: [
'google',
'bing',
'facebook',
'linkedin',
'twitter',
'googleplus',
'bingnews',
'plexoogl'
],
cutoff: 10,
) // [(string google, score: 83, index: 0), (string googleplus, score: 75, index: 5), (string plexoogl, score: 43, index: 7), (string bingnews, score: 29, index: 6), (string linkedin, score: 29, index: 3), (string facebook, score: 29, index: 2), (string bing, score: 23, index: 1), (string twitter, score: 15, index: 4)]
extractAll(
query: 'goolge',
choices: [
'google',
'bing',
'facebook',
'linkedin',
'twitter',
'googleplus',
'bingnews',
'plexoogl'
],
cutoff: 10,
) // [(string google, score: 83, index: 0), (string bing, score: 23, index: 1), (string facebook, score: 29, index: 2), (string linkedin, score: 29, index: 3), (string twitter, score: 15, index: 4), (string googleplus, score: 75, index: 5), (string bingnews, score: 29, index: 6), (string plexoogl, score: 43, 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, index: 3)