Ifrit

https://github.com/ukushu/Ifrit.git
[email protected]:ukushu/Ifrit.git

What is Ifrit?

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

This repository is based on archived repository Fuze-Swift by KRisk ( https://github.com/krisk/fuse-swift)

Difference: Ifrit VS Fuze-Swift?

+ Fuze-Swift support Pods and Packages :)
- Ifrit supports only Packages :(

- Fuze-Swift is dead :(
+ Ifrit is live :)

- Fuze-Swift have multithreading issues - crashes is possible :(
+ Ifrit is a Fuze-Swift with fixed multithreading issues - no crashes :)

- Fuze-Swift written for xcode 11 and have a lot of warnings at now :(
+ Ifrit code is updated to swift's latest standards and there are no build warnings :)

- Fuze-Swift supports async functins with callbacks, but does not support async/await
+ Ifrit supports both async functions types :)

- Fuze-Swift async functins returned incorrect results (wrong indexes) :((((
+ Ifrit's async functins returns correct indexes :)

+ Ifrit have refactored code end extended tests coverage :)

Usage

Searching in a String

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

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

Search in [String]

Synchronous version

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

let results = fuse.searchSync("Te silm", in: books)

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

ASYNChronous version search in [String] ( async/await )

let results = await fuse.search("Te silm", in: books)

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

ASYNChronous version 2 ( callback )

fuse.search("Te silm", in: books, completion: { results in
    results.forEach { item in
        print("index: " + item.index)
        print("score: " + item.score)
        print("ranges: " + item.ranges)
    }
})

Search in [Fuseable] objects

Synchronous version

struct Book: Fuseable {
    let title: String
    let author: String
    
    var properties: [FuseProp] {
        return [
            FuseProp(title, weight: 0.3),
            FuseProp(author, weight: 0.7)
        ]
    }
    //Or this like:
    //var properties: [FuseProp] {
    //    return [title, author].map{ FuseProp($0) }
    //}
    //
}

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.searchSync("man", in: books)

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

// Output:
//
// index: 1
// score: 0.015000000000000003
// results: [(value: "P.D. Mans", score: 0.015000000000000003, ranges: [CountableClosedRange(5...7)])]
// ---------------
// index: 0
// score: 0.027999999999999997
// results: [(value: "Old Man\'s War fiction", score: 0.027999999999999997, ranges: [CountableClosedRange(4...6)])]

ASYNChronous version: search in [Fuseable] objects ( async/await )

let results = await fuse.search("Man", in: books)

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

ASYNChronous version: search in [Fuseable] objects ( callback )

fuse.search("Man", in: books, completion: { results in
    results.forEach { item in
        print("index: " + item.index)
        print("score: " + item.score)
        print("results: " + item.results)
        print("---------------")
    }
})

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

!!!!!!!!!!! Ifrit repository have no example project. !!!!!!!!!!!

As example project you can use project from original Fuse-Swift repository To run the example project:

• clone the Fuse-Swift( https://github.com/krisk/fuse-swift.git ) repo
• and run pod install from the Example directory first.

Installation

1. XCode -> Menu Line -> Add Package Dependencies -> https://github.com/ukushu/Ifrit.git

2. import Ifrit to your source files.