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https://github.com/xdrop/fuzzywuzzy
Java fuzzy string matching implementation of the well known Python's fuzzywuzzy algorithm. Fuzzy search for Java
https://github.com/xdrop/fuzzywuzzy
fuzzy-matching fuzzy-search fuzzywuzzy java python-levenshtein string-distance
Last synced: about 6 hours ago
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Java fuzzy string matching implementation of the well known Python's fuzzywuzzy algorithm. Fuzzy search for Java
- Host: GitHub
- URL: https://github.com/xdrop/fuzzywuzzy
- Owner: xdrop
- License: gpl-2.0
- Created: 2016-09-10T20:29:42.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2023-08-03T19:49:28.000Z (over 1 year ago)
- Last Synced: 2024-11-06T16:50:31.116Z (7 days ago)
- Topics: fuzzy-matching, fuzzy-search, fuzzywuzzy, java, python-levenshtein, string-distance
- Language: Java
- Homepage:
- Size: 415 KB
- Stars: 823
- Watchers: 25
- Forks: 118
- Open Issues: 19
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
[](https://search.maven.org/artifact/me.xdrop/fuzzywuzzy)
# JavaWuzzy
## FuzzyWuzzy Java Implementation
Fuzzy string matching for java based on the [FuzzyWuzzy](https://github.com/seatgeek/fuzzywuzzy) Python algorithm. The algorithm uses [Levenshtein distance](https://en.wikipedia.org/wiki/Levenshtein_distance) to calculate similarity between strings.
I've personally needed to use this but all of the other Java implementations out there either had a crazy amount of
dependencies, or simply did not output the correct results as the python one, so I've decided to properly re-implement
this in Java. Enjoy!
* No dependencies!
* Includes implementation of the super-fast [python-Levenshtein](https://github.com/ztane/python-Levenshtein/) in Java!
* Simple to use!
* Lightweight!
* Credits to the great folks at seatgeek for coming up with the algorithm ([More here](http://chairnerd.seatgeek.com/fuzzywuzzy-fuzzy-string-matching-in-python/))
## Installation
In Maven and Gradle examples, remember to replace "`VERSION`" with the
[latest release](https://search.maven.org/artifact/me.xdrop/fuzzywuzzy) of this
library.
### Maven Central
```xml
me.xdrop
fuzzywuzzy
VERSION
```
### Gradle
```gradle
repositories {
mavenCentral()
}
dependencies {
implementation 'me.xdrop:fuzzywuzzy:VERSION'
}
```
### JPMS
If you use Java 9 or newer, and use the Java Platform Module System (JPMS), you will need to add
the following declarations to your `module-info.java` file:
```java
module my.modulename.here {
requires java.base;
requires me.xdrop.fuzzywuzzy;
}
```
### Jar release
Download the latest release [here](https://github.com/xdrop/fuzzywuzzy/releases) and add to your classpath.
## Usage
#### Simple Ratio
```groovy
FuzzySearch.ratio("mysmilarstring","myawfullysimilarstirng")
72
FuzzySearch.ratio("mysmilarstring","mysimilarstring")
97
```
#### Partial Ratio
```groovy
FuzzySearch.partialRatio("similar", "somewhresimlrbetweenthisstring")
71
```
#### Token Sort Ratio
```groovy
FuzzySearch.tokenSortPartialRatio("order words out of"," words out of order")
100
FuzzySearch.tokenSortRatio("order words out of"," words out of order")
100
```
#### Token Set Ratio
```groovy
FuzzySearch.tokenSetRatio("fuzzy was a bear", "fuzzy fuzzy fuzzy bear")
100
FuzzySearch.tokenSetPartialRatio("fuzzy was a bear", "fuzzy fuzzy fuzzy bear")
100
```
#### Weighted Ratio
```groovy
FuzzySearch.weightedRatio("The quick brown fox jimps ofver the small lazy dog", "the quick brown fox jumps over the small lazy dog")
97
```
#### Extract
```groovy
// groovy
FuzzySearch.extractOne("cowboys", ["Atlanta Falcons", "New York Jets", "New York Giants", "Dallas Cowboys"])
(string: Dallas Cowboys, score: 90, index: 3)
```
```groovy
FuzzySearch.extractTop("goolge", ["google", "bing", "facebook", "linkedin", "twitter", "googleplus", "bingnews", "plexoogl"], 3)
[(string: google, score: 83, index: 0), (string: googleplus, score: 63, index:5), (string: plexoogl, score: 43, index: 7)]
```
```groovy
FuzzySearch.extractAll("goolge", ["google", "bing", "facebook", "linkedin", "twitter", "googleplus", "bingnews", "plexoogl"]);
[(string: google, score: 83, index: 0), (string: bing, score: 20, index: 1), (string: facebook, score: 29, index: 2), (string: linkedin, score: 29, index: 3), (string: twitter, score: 15, index: 4), (string: googleplus, score: 63, index: 5), (string: bingnews, score: 29, index: 6), (string: plexoogl, score: 43, index: 7)]
// score cutoff
FuzzySearch.extractAll("goolge", ["google", "bing", "facebook", "linkedin", "twitter", "googleplus", "bingnews", "plexoogl"], 40)
[(string: google, score: 83, index: 0), (string: googleplus, score: 63, index: 5), (string: plexoogl, score: 43, index: 7)]
```
```groovy
FuzzySearch.extractSorted("goolge", ["google", "bing", "facebook", "linkedin", "twitter", "googleplus", "bingnews", "plexoogl"]);
[(string: google, score: 83, index: 0), (string: googleplus, score: 63, index: 5), (string: plexoogl, score: 43, index: 7), (string: facebook, score: 29, index: 2), (string: linkedin, score: 29, index: 3), (string: bingnews, score: 29, index: 6), (string: bing, score: 20, index: 1), (string: twitter, score: 15, index: 4)]
// score cutoff
FuzzySearch.extractSorted("goolge", ["google", "bing", "facebook", "linkedin", "twitter", "googleplus", "bingnews", "plexoogl"], 3);
[(string: google, score: 83, index: 0), (string: googleplus, score: 63, index: 5), (string: plexoogl, score: 43, index: 7)]
```
#### Extract using any object
`extractOne` and related methods can receive `Collection` and produce `BoundExtractedResult`
```java
List foo = ...;
BoundExtractedResult match = FuzzySearch.extractOne("cowboys", foo, x -> x.toString());
Foo matchFoo = match.getReferent();
```
## Credits
- seatgeek
- Adam Cohen
- David Necas (python-Levenshtein)
- Mikko Ohtamaa (python-Levenshtein)
- Antti Haapala (python-Levenshtein)
- Tobias Burdow (burdoto)