JavaWuzzy

https://github.com/xdrop/fuzzywuzzy
Admin
JavaWuzzy is a Java implementation of the FuzzyWuzzy algorithm that provides fuzzy string matching...
Tokens:16,492
Snippets:105
Trust Score:7.2
License:GPL-2.0
Update:6 days ago
Show doc for...
Tokens:
Raw
### ExtractTop usage

Source: https://github.com/xdrop/fuzzywuzzy/blob/master/README.md

Extract the top N matches using FuzzySearch.extractTop. The example returns the top 3 matches for 'goolge'.

```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)]
```

--------------------------------

### Token Set Ratio usage

Source: https://github.com/xdrop/fuzzywuzzy/blob/master/README.md

Calculate token set full and partial ratios using FuzzySearch.tokenSetRatio and FuzzySearch.tokenSetPartialRatio. Both examples return 100.

```groovy
FuzzySearch.tokenSetRatio("fuzzy was a bear", "fuzzy fuzzy fuzzy bear")
100
FuzzySearch.tokenSetPartialRatio("fuzzy was a bear", "fuzzy fuzzy fuzzy bear")
100
```

--------------------------------

### Partial Ratio usage

Source: https://github.com/xdrop/fuzzywuzzy/blob/master/README.md

Calculate the partial ratio between two strings using FuzzySearch.partialRatio. The example shows a score of 71.

```groovy
FuzzySearch.partialRatio("similar", "somewhresimlrbetweenthisstring")
71
```

--------------------------------

### ExtractAll usage

Source: https://github.com/xdrop/fuzzywuzzy/blob/master/README.md

Extract all matches using FuzzySearch.extractAll. The first example shows all matches, the second shows a score cutoff of 40.

```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)]
```

--------------------------------

### Weighted Ratio usage

Source: https://github.com/xdrop/fuzzywuzzy/blob/master/README.md

Calculate the weighted ratio using FuzzySearch.weightedRatio. The example shows a score of 97.

```groovy
FuzzySearch.weightedRatio("The quick brown fox jimps ofver the small lazy dog", "the quick brown fox jumps over the small lazy dog")
97
```

--------------------------------

### Token Sort Ratio usage

Source: https://github.com/xdrop/fuzzywuzzy/blob/master/README.md

Calculate token sort partial and full ratios using FuzzySearch.tokenSortPartialRatio and FuzzySearch.tokenSortRatio. Both examples return 100.

```groovy
FuzzySearch.tokenSortPartialRatio("order words out of","  words out of order")
100
FuzzySearch.tokenSortRatio("order words out of","  words out of order")
100
```

--------------------------------

### ExtractOne usage

Source: https://github.com/xdrop/fuzzywuzzy/blob/master/README.md

Extract the best matching string from a list using FuzzySearch.extractOne. The example returns Dallas Cowboys with a score of 90.

```groovy
// groovy

FuzzySearch.extractOne("cowboys", ["Atlanta Falcons", "New York Jets", "New York Giants", "Dallas Cowboys"])
(string: Dallas Cowboys, score: 90, index: 3)
```

--------------------------------

### Simple Ratio usage

Source: https://github.com/xdrop/fuzzywuzzy/blob/master/README.md

Calculate the simple ratio between two strings using FuzzySearch.ratio. The examples show scores of 72 and 97 for different string pairs.

```groovy
FuzzySearch.ratio("mysmilarstring","myawfullysimilarstirng")
72

FuzzySearch.ratio("mysmilarstring","mysimilarstring")
97
```

--------------------------------

### ExtractSorted usage

Source: https://github.com/xdrop/fuzzywuzzy/blob/master/README.md

Extract matches sorted by score using FuzzySearch.extractSorted. The first example shows all matches sorted, the second shows a score cutoff of 3.

```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)]
```

--------------------------------

### Gradle dependency for fuzzywuzzy

Source: https://github.com/xdrop/fuzzywuzzy/blob/master/README.md

Add the fuzzywuzzy library to your Gradle project. Replace VERSION with the latest release version.

```gradle
repositories {
    mavenCentral()
}

dependencies {
    implementation 'me.xdrop:fuzzywuzzy:VERSION'
}
```

--------------------------------

### Maven dependency for fuzzywuzzy

Source: https://github.com/xdrop/fuzzywuzzy/blob/master/README.md

Add the fuzzywuzzy library to your Maven project. Replace VERSION with the latest release version.

```xml
<dependency>
    <groupId>me.xdrop</groupId>
    <artifactId>fuzzywuzzy</artifactId>
    <version>VERSION</version>
</dependency>
```

--------------------------------

### Extract using any object

Source: https://github.com/xdrop/fuzzywuzzy/blob/master/README.md

Use extractOne with a collection of custom objects and a function to convert them to strings. The result is a BoundExtractedResult that can be used to retrieve the original object.

```java
List<Foo> foo = ...;
BoundExtractedResult<Foo> match = FuzzySearch.extractOne("cowboys", foo, x -> x.toString());
Foo matchFoo = match.getReferent();
```

--------------------------------

### JPMS module declaration for fuzzywuzzy

Source: https://github.com/xdrop/fuzzywuzzy/blob/master/README.md

Required for Java 9+ projects using the Java Platform Module System. Add these declarations to your module-info.java file.

```java
module my.modulename.here {
    requires java.base;
    requires me.xdrop.fuzzywuzzy;
}
```
Tokens:
Raw