Awesome

Fuse

What is Fuse?

Fuse is a super lightweight library which provides a simple way to do fuzzy searching.

Usage

Example 1

let fuse = Fuse()
let result = fuse.search("od mn war", in: "Old Man's War")

print(result?.score)  // 0.44444444444444442
print(result?.ranges) // [CountableClosedRange(0...0), CountableClosedRange(2...6), CountableClosedRange(9...12)]

Example 2

Search for a text pattern in an array of srings.

let books = ["The Silmarillion", "The Lock Artist", "The Lost Symbol"]
let fuse = Fuse()

// Improve performance by creating the pattern once
let pattern = fuse.createPattern(from: "Te silm")

// Search for the pattern in every book
books.forEach {
    let result = fuse.search(pattern, in: $0)
    print(result?.score)
    print(result?.ranges)
}

Example 3

class Book: Fuseable {
    dynamic var name: String
    dynamic var author: String

    var properties: [FuseProperty] {
        return [
            FuseProperty(name: "title", weight: 0.3),
            FuseProperty(name: "author", weight: 0.7),
        ]
    }
}

let books: [Book] = [
    Book(author: "John X", title: "Old Man's War fiction"),
    Book(author: "P.D. Mans", title: "Right Ho Jeeves")
]

let fuse = Fuse()
let results = fuse.search("man", in: books)

results.forEach { item in
    print("index: " + item.index)
    print("score: " + item.score)
    print("results: " + item.results)
    print("---------------")
}

// Output:
//
// index: 1
// score: 0.015
// results: [(key: "author", score: 0.015000000000000003, ranges: [CountableClosedRange(5...7)])]
// ---------------
// index: 0
// score: 0.028
// results: [(key: "title", score: 0.027999999999999997, ranges: [CountableClosedRange(4...6)])]

Example 4

let fuse = Fuse()
fuse.search("Man", in: books, completion: { results in
    print(results)
})

Options

Fuse takes the following options:

• location: Approximately where in the text is the pattern expected to be found. Defaults to 0
• distance: Determines how close the match must be to the fuzzy location (specified above). An exact letter match which is distance characters away from the fuzzy location would score as a complete mismatch. A distance of 0 requires the match be at the exact location specified, a distance of 1000 would require a perfect match to be within 800 characters of the fuzzy location to be found using a 0.8 threshold. Defaults to 100
• threshold: At what point does the match algorithm give up. A threshold of 0.0 requires a perfect match (of both letters and location), a threshold of 1.0 would match anything. Defaults to 0.6
• maxPatternLength: The maximum valid pattern length. The longer the pattern, the more intensive the search operation will be. If the pattern exceeds the maxPatternLength, the search operation will return nil. Why is this important? Read this. Defaults to 32
• isCaseSensitive: Indicates whether comparisons should be case sensitive. Defaults to false

Example Project

To run the example project, clone the repo, and run pod install from the Example directory first.

Requirements

Installation

Fuse is available through CocoaPods. To install it, simply add the following line to your Podfile:

pod "Fuse"

License

Fuse is available under the MIT license. See the LICENSE file for more info.