BENEDIKT TERHECHTE

This is my research notebook. I'm an OSX / iOS indie developer. After 8 years of Objective-C I really enjoy Swift nowadays. Trying to publish all my research on Development, Swift & other technologies here.

Sat, 30 Sep 2017 #

Value Types for Simple Difference Detection

Following sage advice I received from John Sundell half a year ago (I am a slow learner) I will try to write about smaller pieces instead of focusing on longform content. This should make it easier to update appventure more often. Thanks John!.

Today, I'll write about value types: Value types are a very useful addition to Swift. Objective-C did offer C struct types and (obviously) classical value types such as numbers, but Swift goes way beyond that by allowing us to also define more complex structures such as Array, Set, or Dictionary as value types. One of the best properties of value types is that they can easily be compared given that they're values:

let one = [1, 2, 3]
let two = [1, 2, 3]
print(one == two) // returns true

This way of easily comparing arrays is something we can use to implement a simple difference detection algorithm without using more heavy-weight solutions. Imagine you have a simple app that downloads a list of entries from a server and displays them in a table view. Once a minute you download a new list and reload the table view. This is not a particularly nice solution as you're reloading the table view even when there're no changes. If your data is defined as a struct and you implement the Equatable protocol, then you can simply use the equality operator to see if the table view needs to be reloaded:

struct Data: Equatable {
  let username: String
  let userid: Int
  static func ==(lhs: Data, rhs: Data) -> Bool {
    return lhs.username == rhs.username && lhs.userid == rhs.userid
  }
}
let oldData: [Data] = currentData()
let newData: [Data] = retrieveNewData()
guard oldData != newData else {
    return
}
updateData(with: newData)

However, it may be that your data is modelled using struct types, but that they're very complex and change often. So you've never implemented Equatable. Then you have three different options:

  1. Wait for Swift 4.1 which will hopefully merge a PR which will auto-generate Equatable for struct types if all properties of a struct also conform to Equatable.
  2. Use Krzysztof Zabłocki's Sourcery which is a meta programming framework that allows you to auto generate things like Equatable conformance for your types (and much more).
  3. This I will explain in more detail as it is also a pattern that you can use if your data is modelled using class types.

The idea here is to store just the absolutely necessary information in a seperate difference detection cache. Imagine the following data model:

final class Story {
  let story_id: Int
  let views: Int
  let last_updated: TimeInterval
  let description: String
}

In this example, a Story will never change its id and description. In order to create a simple cache, we can now just use the information we absolutely need to determine a change and store them in tuples. Tuples with up to 6 elements will automatically generate Equatable conformance:

let a = (1, 2, 3)
let b = (1, 2, 3)
print(a == b)

With this in mind, we can generate our tuples:

let newInformation: [(Int, Int, TimeInterval)] = 
  stories.map({ ($0.story_id, $0.views, $0.last_updated) })

guard newInformation != oldInformation else { return }

This is a simple solution that leverages value types to give us an easy solution for comparing sets of data. However, if you also need to determine insertions, deletions and moves then you can still do so with value types, but you need a proper diff algorithm such as Dwifft.

Nevertheless, for many simpler use cases it is good to remember that we can easily build a comparison cache of tuples or structs to determine general changes to data.

If you read this far, you should follow me (@terhechte)
on Twitter


    Fri, 15 Jul 2016 #

    Data in Swift 3 parsing a Doom WAD File

    1 From NSData to Data in Swift 3

    Swift 3 encompasses many different small and big changes to the language. One of them is the introduction of value type wrappers for common Foundation reference types such as NSData (Data) or NSDate (Date). These new types differ not only in their memory behaviour and name, their methods also differ from their reference-based counterparts1. From small changes to new method names up to big changes like completely removed functionalities, these new value types require some getting used to. This post will try to highlight some of the bigger changes happened to Data the value-based wrapper for NSData.

    Even better, after going through the basics, we will write a small example application that will read and parse a Doom 2 WAD file.




    2 Basic Differences

    One of the most common usage scenarios for NSData is the loading and writing of data via these calls:

    func writeToURL(_ url: NSURL, atomically atomically: Bool) -> Bool
    func writeToURL(_ url: NSURL, options writeOptionsMask: NSDataWritingOptions) throws
    // ... (implementations for file: String instead of NSURL)
    init?(contentsOfURL url: NSURL)
    init(contentsOfURL url: NSURL, options readOptionsMask: NSDataReadingOptions) throws
    // ... (implementations for file: String instead of NSURL)
    

    For those basic usages, very little changed. The new Data type offers these methods:

    init(contentsOf: URL, options: ReadingOptions)
    func write(to: URL, options: WritingOptions)
    

    Note that Data simplifies the various ways of reading and writing data from the file system into two calls while NSData offers multiple different methods.

    Another difference can be observed when comparing the methods on NSData with those on Data. While NSData offers 30 methods & properties, Data offers 130. This huge difference is easily explained via Swift's formidable Protocol Extensions. Data obtains many of those methods from the following protocols:

    • CustomStringConvertible
    • Equatable
    • Hashable
    • MutableCollection
    • RandomAccessCollection
    • RangeReplaceableCollection
    • ReferenceConvertible

    This adds functionality to Data which did not exist in NSData. Here's a small sample:

    func distance(from: Int, to: Int)
    func dropFirst(Int)
    func dropLast(Int)
    func filter((UInt8) -> Bool)
    func flatMap<ElementOfResult>((UInt8) -> ElementOfResult?)
    func forEach((UInt8) -> Void)
    func index(Int, offsetBy: Int, limitedBy: Int)
    func map<T>((UInt8) -> T)
    func max()
    func min()
    func partition()
    func prefix(Int)
    func reversed()
    func sort()
    func sorted()
    func split(separator: UInt8, maxSplits: Int, omittingEmptySubsequences: Bool)
    func reduce<Result>(Result, (partialResult: Result, UInt8) -> Result)
    

    As you can see, many functional approaches, such as mapping or filtering can now be done on the byte contents of Data types. This, to me, is a huge improvement over NSData. An example of the benefits this brings is how easily you can now subscript and compare data:

    var data = Data(bytes: [0x00, 0x01, 0x02, 0x03])  
    print(data[2]) // 2
    data[2] = 0x09
    print (data == Data(bytes: [0x00, 0x01, 0x09, 0x03])) // true  
    
    2
    true
    
    

    Data also offers several new initializers which specifically handle other common Swift data types:

    init(bytes: Array<UInt8>)
    init<SourceType>(buffer: UnsafeMutableBufferPointer<SourceType>)
    init(repeating: UInt8, count: Int)
    

    3 GetBytes

    Another difference which you will run into if you're using Data to interact with lower level code such as C libraries is the distinct lack of the NSData getBytes method:

    // NSData
    func getBytes(_ buffer: UnsafeMutablePointer<Void>, length length: Int)
    

    There're many different usage scenarious for getBytes. One of the most common is when you need to parse a file and read the bytes into data types / variables. A common example: Say you want to read a binary file which encodes a list of items. The file is encoded as follows:

    Datatype Size Function
    Char 4 Header (ABCD)
    UInt32 4 Start of Data
    UInt32 4 Amount of items

    The file contains a 4 byte string "ABCD" tagging it as the correct file type. The next 4 bytes define the start of the actual data (i.e. where the header ends and the items begin), the final 4 bytes in the header define the amount of items stored in this file.

    Parsing this data with NSData is pretty straight forward:

    let data = ...
    var length: UInt32 = 0
    var start: UInt32 = 0
    data.getBytes(&start, range: NSRange(location: 4, length: 4))
    data.getBytes(&length, range: NSRange(location: 8, length: 4))
    

    This will return the correct result3. If your data does not contain C strings, there's an even easier way of doing this, you can simply define a struct with the correct fields and read the bytes directly into the struct:

    Datatype Size Function
    UInt32 4 Start of Data
    UInt32 4 Amount of items
    let data = ...
    struct Header { 
      let start: UInt32
      let length: UInt32
    }
    var header = Header(start: 0, length: 0)
    data.getBytes(&header, range: NSRange(location: 0, length: 8))
    

    4 Data alternatives to getBytes

    However, if you're using Data this functionality is not available anymore. Instead, Data offers a new method:

    // Access the bytes in the data.
    func withUnsafeBytes<ResultType, ContentType>((UnsafePointer<ContentType>) -> ResultType)
    

    This method allows direct access of the our data's bytes from within a closure. Let's see a simple example:

    let data = Data(bytes: [0x01, 0x02, 0x03])
    data.withUnsafeBytes { (pointer: UnsafePointer<UInt8>) -> Void in
        print(pointer)
        print(pointer.pointee)
    }
    // Prints: 
    // : 0x00007f8dcb77cc50
    // : 1
    

    Ok, now that we have an unsafe UInt8 pointer into our data, how does this help us? First of fall, we obviously need a different data type, and we're sure (we have to be!) that the data is indeed of this particular data type. We know that this data contains a Int32 type, so how do we decode it correctly?

    As we already have a unsafe pointer (of type UInt8) it is easy to move this into an unsafe pointer of our target type. UnsafePointer has a pointee property which returns the type that the pointer is pointing to as the correct type:

    let data = Data(bytes: [0x00, 0x01, 0x00, 0x00])
    let result = data.withUnsafeBytes { (pointer: UnsafePointer<Int32>) -> Int32 in
          return pointer.pointee
    }
    print(result)
    //: 256
    
    256
    
    

    As you can see, we created a byte Data instance, and returned the data as Int32 by defining an UnsafePointer<Int32> in the closure. You can shorten this code if the compiler is able to infer the result type from the context:

    let result: Int32 = data.withUnsafeBytes { $0.pointee }
    

    5 Lifetime of the data

    One important consideration of using withUnsafeBytes (apart from the fact that the whole operation is unsafe) is that the lifetime of the pointer you're accessing is limited to the lifetime of your closure. As the documentation notes:

    Warning The byte pointer argument should not be stored and used outside of the lifetime of the call to the closure.

    6 Generic Solution

    Now that we have a way of accessing raw bytes and casting them to the correct type, we ought to create a generic solution that allows us to perform this operation easily without the syntactical overhead. Also, we still did not account for the fact that we need to perform the operation on a subsequence of our data and not the whole Data instance. A generic solution would look like this:

    extension Data {
        func scanValue<T>(start: Int, length: Int) -> T {
            return self.subdata(in: start..<start+length).withUnsafeBytes { $0.pointee }
        }
    }
    let data = Data(bytes: [0x01, 0x02, 0x01, 0x02])
    let a: Int16 = data.scanValue(start: 0, length: 1)
    print(a)
    // : 1
    
    2
    
    

    Compared to our earlier code, this has a couple of notable differences:

    • We're using subdata to only scan the bytes of a specific slice of our Data.
    • We're using generics to support different possible data types for extraction

    7 To Data

    The opposite case, taking an existing variable and getting a Data buffer to the content, is not relevant for the Doom example below, but easy enough to implement:

    var variable = 256
    let data = Data(buffer: UnsafeBufferPointer(start: &variable, count: 1))
    print(data) // : <00010000 00000000>
    
    <00010000 00000000 00000000 00000000>
    
    

    8 Parsing the Doom WAD file

    I've played a lot of Doom in my youth. I loved the game. I also created a lot of Doom levels and modified the WAD file to incorporate new sprites, textures, and more. So when I thought about a nice (and simple) example of how to parse a binary file, I remembered the layout of the WAD file which is pretty straightforward and easy to implement. So I wrote a simple app that reads a WAD file and lists the names of all the floor textures stored in the WAD4.

    The source code for this application is available on Github.

    The Doom WAD file layout is described in these two documents:

    However, for our simple example, we only need to understand a subset of the format. First, each WAD file begins with a header:

    Datatype Size Function
    Char 4 IWAD or PWAD string
    Int32 4 The number of lumps in the WAD
    Int32 4 Pointer to the location of the directory

    The first 4 bytes are spend to identify the file format. IWAD are official Doom WAD files, PWAD are patches containing additional information patched at runtime into the main WAD file. Our application will only read IWAD files. The next 4 bytes define the number of lumps in the WAD. Lumps are the individual items that the Doom engine operates with: Textures, Sprite-Frames, Text blocks, Models, etc. Each texture is a distinct lump. The final 4 bytes define the location of the directory. We'll explain the directory below, once we start parsing it. First, lets parse the header.

    8.1 Parsing the Header

    Reading a WAD file is straight forward:

    let data = try Data(contentsOf: wadFileURL, options: .alwaysMapped)
    

    Once we have the data, we need to parse the header. We're making heavy use of the scanValue Data extension we defined earlier.

    public func validateWadFile() throws {
        // Several Wad File definitions
        let wadMaxSize = 12, wadLumpsStart = 4, wadDirectoryStart = 8, wadDefSize = 4
        // A WAD file always starts with a 12-byte header.
        guard data.count >= wadMaxSize else { throw WadReaderError.invalidWadFile(reason: "File is too small") }
    
        // It contains three values:
    
        // The ASCII characters "IWAD" or "PWAD". Defines whether the WAD is an IWAD or a PWAD.
        let validStart = "IWAD".data(using: String.Encoding.ascii)!
        guard data.subdata(in: 0..<wadDefSize) == validStart else
        { throw WadReaderError.invalidWadFile(reason: "Not an IWAD") }
    
        // An integer specifying the number of lumps in the WAD.
        let lumpsInteger: Int32 = data.scanValue(start: wadLumpsStart, length: wadDefSize)
    
        // An integer holding a pointer to the location of the directory.
        let directoryInteger: Int32 = data.scanValue(start: wadDirectoryStart, length: wadDefSize)
    
        guard lumpsInteger > 0 && directoryInteger > Int32(wadMaxSize)
            else {
                throw WadReaderError.invalidWadFile(reason: "Empty Wad File")
        }
    }
    

    You can find additional types (such as the WadReaderError enum) in the source on GitHub. The next step is to parse the directory, so that we get the addresses and sizes of the individual lumps.

    8.2 Parsing the Directory

    The directory associates names of lumps with the data that belong to them. It consists of a number of entries, each with a length of 16 bytes. The length of the directory is determined by the number given in the WAD header.

    Each of the 16 bytes entries follows the same format:

    Datatype Size Function
    Int32 4 The start of the lumps data in the file
    Int32 4 The size of the lump in bytes
    Char 8 An ASCII string defining the lump's name

    The name char is a bit more complicated. The documentation says:

    An ASCII string defining the lump's name. Only the characters A-Z (uppercase), 0-9, and [ ] - _ should be used in lump names (an exception has to be made for some of the Arch-Vile sprites, which use "\"). When a string is less than 8 bytes long, it should be null-padded to the tight byte.

    Note the last sentence. In C, a String is terminated with the null character (\0). This signifies to the system that the memory for the string ends here. Doom saves space by having an optional null character. When the string is less than 8 bytes long, it will contain a null character, when it is of the max length (8 bytes) the 8th byte will be the final character, not the null character.

      0 1 2 3 4 5 6 7  
    Short I M P \0 \0 \0 \0 \0 #
    Long F L O O R 4 _ 5 #

    See above for an example. The Short name has a null character after the last letter in position 3, the long name does not have a null character, instead the last letter is the 5 from the name FLOOR4_5. The # signifies the beginning of the next item / piece of memory.

    Before we venture into supporting this, lets first take care of the easier part, reading the start and size.

    Before we start, we should define a data structure that can store the information from the directory:

    public struct Lump {
        public let filepos: Int32
        public let size: Int32
        public let name: String
    }
    

    Afterwards, we take the slice of data that constitutes our directory from the complete data instance.

    // Define the default size of a directory entry
    let wadDirectoryEntrySize = 16
    // Extract the directory slice from the main Data
    let directory = data.subdata(in: Int(directoryLocation)..<(Int(directoryLocation) + Int(numberOfLumps) * wadDirectoryEntrySize))
    

    Next, we can iterate over the Data in 16byte steps. This works great with Swift's stride function:

    for currentIndex in stride(from: 0, to: directory.count, by: wadDirectoryEntrySize) {
        let currentDirectoryEntry = directory.subdata(in: currentIndex..<currentIndex+wadDirectoryEntrySize)
    
        // An integer holding a pointer to the start of the lump's data in the file.
        let lumpStart: Int32 = currentDirectoryEntry.scanValue(start: 0, length: 4)
    
        // An integer representing the size of the lump in bytes.
        let lumpSize: Int32 = currentDirectoryEntry.scanValue(start: 4, length: 4)
        ...
    }
    

    This was the easier part the next part is a bit more difficult.

    8.3 Parsing C Strings

    Remember, for each lump's name, we need to stop reading bytes into our Swift string once we reach a null terminator or once we reach 8 bytes. The very first thing to do is create a data slice with the relevant data:

    let nameData = currentDirectoryEntry.subdata(in: 8..<16)
    

    Swift offers great support for C String interoperability. This means that to create a string we just need to hand the data to a String initializer:

    let lumpName = String(data: nameData, encoding: String.Encoding.ascii)
    

    This works, though the result is not correct. This method ignores the null terminator, so that all names, even the short ones, are converted to 8byte strings. As an example, the lump for the IMP character name becomes IMP00000. This happens because Doom fills the remaining 5 bytes with null characters and String(data:encoding:) does not interpret them but creates a string of the full 8 bytes of the nameData.

    If we want to support null characters, Swift offers something else, a cString initializer which is defined for reading valid cStrings with null terminators:

    // Produces a string containing the bytes in a given C array, 
    // interpreted according to a given encoding.
    init?(cString: UnsafePointer<CChar>, encoding enc: String.Encoding)
    

    Note that it doesn't require a data instance as its parameter but an unsafePointer to CChars instead. We already know how to do that, so lets write the code:

    let lumpName2 = nameData.withUnsafeBytes({ (pointer: UnsafePointer<UInt8>) -> String? in
        return String(cString: UnsafePointer<CChar>(pointer), encoding: String.Encoding.ascii)
    })
    

    This, again, doesn't work. In all cases where Doom's names are less than 8 characters, this code works flawlessly, but once we reach a 8 byte name without a null terminator, it will continue reading (into the next 16byte segment) until it finds the next valid null terminator. This results in long strings with random memory at the end.

    Since this logic is custom to Doom, we also need to implement custom code. As Data supports Swift's collection & sequence operations, we can just solve this in terms of reduce:

    let lumpName3Bytes = try nameData.reduce([UInt8](), { (a: [UInt8], b: UInt8) throws -> [UInt8] in
        guard b > 0 else { return a }
        guard a.count <= 8 else { return a }
        return a + [b]
    })
    guard let lumpName3 = String(bytes: lumpName3Bytes, encoding: String.Encoding.ascii)
        else {
            throw WadReaderError.invalidLup(reason: "Could not decode lump name for bytes \(lumpName3Bytes)")
    }
    

    This code just reduces over the UInt8 bytes of our data and checks whether we have an early null terminator. This code works, though it is not necessarily fast as the data has to be moved through several abstractions.

    It would be better if we could solve this similarly to how the Doom engine does it. Doom just moves the pointer of the char* and checks for each char whether it is a null terminator in order to break early. As Doom is written in low level C code, it can just iterate over the raw pointer addresses.

    How would we implement this logic in Swift? We can actually do something quite similar in Swift by, again, utilizing withUnsafeBytes. Lets see:

    let finalLumpName = nameData.withUnsafeBytes({ (pointer: UnsafePointer<CChar>) -> String? in
        var localPointer = pointer
        for _ in 0..<8 {
            guard localPointer.pointee != CChar(0) else { break }
            localPointer = localPointer.successor()
        }
        let position = pointer.distance(to: localPointer)
        return String(data: nameData.subdata(in: 0..<position),
                      encoding: String.Encoding.ascii)
    })
    guard let lumpName4 = finalLumpName else {
        throw WadReaderError.invalidLup(reason: "Could not decode lump name for bytes \(lumpName3Bytes)")
    }
    

    Similar to our earlier uses of withUnsafeBytes we're receiving a pointer to the raw memory. pointer is a let constant, but we need to modify the variable, which is why we create a local mutable version in the first line 5.

    Afterwards, we're performing the main work. We loop from 0 to 8 and for each loop iteration we test whether the char that the pointer is pointing to (the pointee) is equal to the null terminator (CChar(0)). If it is equal to the null terminator, this means that we found the null terminator early, and we break. If it is not equal to the null terminator, we overwrite localPointer with its successor, i.e. the next position in memory after the current pointer. That way, we're iterating byte by byte over the contents of our memory.

    Once we're done, we calculate the distance between our original pointer and our localPointer. If we just advanced three times before finding a null terminator, the distance between the two pointers would be 3. This distance, finally, allows us to create a new String instance with the subdata of actual C String.

    This allows us to create a new Lump struct with the required data:

    lumps.append(Lump(filepos: lumpStart, size: lumpSize, name: lumpName4))                
    

    When you look into the source, you will see ominous references to F_START and F_END. Doom marks the beginning and end of special lump regions with empty lumps with magic names. F_START / F_END enclose all the floor texture lumps. We will ignore this additional step in this tutorial.

    A screenshot from the final application:




    Not really impressive, I know. One of the next installments on this blog might concentrate on how to display those textures.

    9 Bridging to NSData

    I find the new Data easier to work with than NSData. Nevertheless, if you need NSData or if you need to use the getBytes method, there's an easy way to convert Data to NSData. The Swift documentation writes:

    This type provides “copy-on-write” behavior, and is also bridged to the Objective-C NSData class. You can wrap an instance of a custom subclass of NSData in struct Data by converting it using myData as Data.

    // Create a new Data Struct
    let aDataStruct = Data()
    // Get the underlying reference type NSData
    let aDataReference = aDataStruct as NSData
    

    Whenever you feel that what you're trying to do seems to be really hard with the Data type, it is easy to go back to NSData to use the well known tried and trusted methods. However, in general you should strive to use the new Data type whenever possible (except if you need reference semantics):

    Footnotes:

    1
    Some, such as Date aren't even wrappers but completely new implementations
    2
    Doom1, Doom2, Hexen, Heretic, or Ultimate Doom. Though I've only tested it with Doom1 Shareware
    3
    Note we did not make sure that this is indeed an ABCD file by testing for the first 4 bytes, but that would be easy to add
    4
    I kinda wanted to also display the textures but lacked the time to implement that.
    5
    Swift 3 dropped support for the useful var annotation in closure or function bodies

    If you read this far, you should follow me (@terhechte)
    on Twitter


      Thu, 28 Apr 2016 #

      SwiftWatch

      And now for something slightly different. I'm not sure how others perceive this, but I find it very difficult to keep on track of all the exciting developments in the Swift community. There're so many fascinating GitHub projects, valuable conference talks, educational blog posts, insightful Twitter discussions and fantastic newsletters that it is hard to keep yourself updated on recent developments. To make matters worse, the scope of Swift is also expanding from iOS/watchOS/tvOS/macOS development to Linux server development and now even Android development.

      There're several great Swift & iOS newsletters that remedy this situation in part, but they only appear once a week and usually showcase a limited, curated selection of what happened during the week. There's also the reddit Swift community, but the myriad of subreddits (like iOS, Mac, programming, etc), again, requires the visiting of multiple different locations in order to get an overview 1.

      After feeling constantly overwhelmed and underinformed, I decided to try to do something about this. I'm an avid reader of Hacker News, and, to me, it feels as if what's missing is a place like Hacker News 2 but solely for everything Swift. A place to share interesting Swift tidbits and (maybe) discuss them.

      So without further ado, let me introduce SwiftWatch:





      SwiftWatch tries to be this place. I'd not call it a community or a social network. Rather, it is a place to share interesting Swift news. You have to register with a Twitter or Github account, in order to (ever so slightly) decrease the likelihood of spam. Commenting is possible, but I don't envision this site to be a source of great discussions. Instead, I'd be more than happy if people start using it to post interesting Swift developments.

      If you have any feedback regarding Swiftwatch, feel free to contact me on Twitter.

      As you can see, @renelindhorst 3 and I have already been feeding the page with a couple of links which we deemed interesting enough to post them.

      The site is based on Monocle, an open source link sharing platform. I'd have rather developed something in Swift but that'd have consumed too much time. If SwiftWatch survives (i.e. if it gains decent traction) then I'd seriously consider rewriting the guts in Swift3 + one of those nice Web Frameworks (like Perfect).

      Thanks for reading!

      PS: In case you're wondering "SwiftWatch" is named after the peculiar habbit of birdwatching, "a form of wildlife observation in which the observation of birds is a recreational activity". I found this a particularly good fit as the core objective of this site is quite similar.

      Footnotes:

      1
      Alternatively, one can sign up on reddit and meticulously manage one's subreddit subscriptions, but not everybody does that
      2
      or LamerNews or Designer News or Product Hunt
      3
      Thanks Rene!

      If you read this far, you should follow me (@terhechte)
      on Twitter


        Sat, 23 Apr 2016 #

        Raw value initializers for enums with associated types

        Enums are a beautiful way of structuring information in Swift. Sometimes you find yourself initializing enums from raw values, maybe because the values were intermittendly stored somewhere else, say in the NSUserDefaults:

        enum Device: String {
          case phone, tablet, watch
        }
        let aDevice = Device(rawValue: "phone")
        print(aDevice)
        
        Prints Optional(main.Device.phone)
        
        

        1 The Problem

        As soon as you're using associated values in your enums, this doesn't work anymore:

        enum Example {
           case Factory(workers: Int)
           case House(street: String)
        }
        

        Swift can't create an instance of Example because the two cases, Factory and House have different associated types (the workers integer and the street string. Each invocation of Example requires different parameters, so this can't be generalized.

        However, that's not the case when your associated types all match up:

        enum Device {
            case phone(name: String, screenSize: CGSize)
            case watch(name: String, screenSize: CGSize)
            case tablet(name: String, screenSize: CGSize)
        }
        

        In thise case, all the associated types are the same. There're a myriad of other ways to model this, but I found the device enum to be a concise example for what I'm about to explain. Even though every Device invocation is the same now, you still can't just call it with some sort of raw value and expect the correct type. Instead, what you have to do is perform a match in order to create the correct instance:

        import Foundation
        
        enum Device {
            case phone(name: String, screenSize: CGSize)
            case watch(name: String, screenSize: CGSize)
            case tablet(name: String, screenSize: CGSize)
            
            static func fromDefaults(rawValue: String, name: String, screenSize: CGSize) -> Device? {
                switch rawValue {
                case "phone": return Device.phone(name: name, screenSize: screenSize)
                case "watch": return Device.watch(name: name, screenSize: screenSize)
                case "tablet": return Device.tablet(name: name, screenSize: screenSize)
                default: return nil
                }
            }
        }
        let b = Device.fromDefaults("phone", name: "iPhone SE", screenSize: CGSize(width: 640, height: 1136))
        print(b)
        
        prints Optional(main.Device.phone("iPhone SE", (640.0, 1136.0)))
        
        

        This looks ok, but it is already a bit of repetitive code. Once you develop more than just three enum cases / two associated types, this will quickly get out of hand.

        enum Vehicle {
          case .car(wheels: Int, capacity: Int, weight: Int, length: Int, height: Int, width: Int, color: Int, name: Int, producer: Int, creation: NSDate, amountOfProducedUnits: Int)
          case .ship(wheels: Int, capacity: Int, weight: Int, length: Int, height: Int, width: Int, color: Int, name: Int, producer: Int, creation: NSDate, amountOfProducedUnits: Int)
          case .yacht(wheels: Int, capacity: Int, weight: Int, length: Int, height: Int, width: Int, color: Int, name: Int, producer: Int, creation: NSDate, amountOfProducedUnits: Int)
          case .truck(wheels: Int, capacity: Int, weight: Int, length: Int, height: Int, width: Int, color: Int, name: Int, producer: Int, creation: NSDate, amountOfProducedUnits: Int)
          case .motorbike(wheels: Int, capacity: Int, weight: Int, length: Int, height: Int, width: Int, color: Int, name: Int, producer: Int, creation: NSDate, amountOfProducedUnits: Int)
          case .helicopter(wheels: Int, capacity: Int, weight: Int, length: Int, height: Int, width: Int, color: Int, name: Int, producer: Int, creation: NSDate, amountOfProducedUnits: Int)
          case .train(wheels: Int, capacity: Int, weight: Int, length: Int, height: Int, width: Int, color: Int, name: Int, producer: Int, creation: NSDate, amountOfProducedUnits: Int)
          ...
        }
        

        I think you get my point.

        2 The Solution

        So.. how do we solve this? Interestingly, there's a quirky similarity between the initializer of an associated type and a closure. Take this code:

        enum Example {
          case test(x: Int)
        }
        let exampleClosure = Example.test
        

        What is the type of exampleClosure here? The type is (Int) -> Example. That's right, calling an associated value enum case without any parameters will yield a closure that, when called with the correct types, will return an instance of said type.

        This means that, the following is valid, working Swift:

        enum Fruit {
          case apple(amount: Int)
          case orange(amount: Int)
        }
        let appleMaker = Fruit.apple
        let firstApple = appleMaker(amount: 10)
        let secondApple = appleMaker(amount: 12)
        print(firstApple, secondApple)
        
        apple(10) apple(12)
        
        

        So, how would that help us simplify the gross code duplication problem above? Have a look:

        import Foundation
        
        enum Device {
            case phone(name: String, screenSize: CGSize)
            case watch(name: String, screenSize: CGSize)
            case tablet(name: String, screenSize: CGSize)
            
            private static var initializers: [String: (name: String, screenSize: CGSize) -> Device] = {
                return ["phone": Device.phone, "watch": Device.watch, "tablet": Device.tablet]
            }()
            
            static func fromDefaults(rawValue: String, name: String, screenSize: CGSize) -> Device? {
                return Device.initializers[rawValue]?(name: name, screenSize: screenSize)
            }
        }
        
        let iPhone = Device.fromDefaults("phone", name: "iPhone SE", screenSize: CGSize(width: 640, height: 1134))
        print(iPhone)
        
        Optional(main.Device.phone("iPhone SE", (640.0, 1134.0)))
        
        

        So, let's try to figure out what happened here. We have a new property initializers on our Device. It's a Dictionary of type [String: (name: String, screenSize: CGSize) -> Device]. I.e. something that maps from a String key to a closure with the same type as our Device cases. The dictionary contains the initializers of each of our distinct cases, simply by using the same trick as above, just handing in the closure: phone:Device.phone

        The fromDefaults function, then, only has to know the key of the device we'd like to create, and it can call the appropriate closure. This leads to a much shorter implementation, especially for bigger enums (like our Vehicle example above). As you can see, creating a Device instance is then as simple as:

        Device.initializers["phone"]?(name: "iPhone 5", screenSize: CGSize(width: 640, height: 1134)))
        

        Just as with raw values, in case there is no enum case phone we'd just get an empty optional back.

        This solution isn't perfect of course. You still have to have the initializers dictionary, however it will be much less repetitve than having to match over all cases manually.

        Finally, I suppose it goes without saying that the code above ignores an important best practice to be concise and to be able to concentrate on the task at hand; Nevertheless: having stringified code like Device.initializers["phone"] is not the best way to write this. Instead, those keys should be properly defined somewhere else.

        If you read this far, you should follow me (@terhechte)
        on Twitter


          Thu, 14 Apr 2016 #

          Force optionals in multi-unwrapped "guard let" or "if let"

          I really love unwrapping optionals in a multi- guard or let statement with additional where clauses added. See my previous post on this here. However, sometimes I run into a situation where I have one function call (or a array subscript) in between my others that does not return an optional:

          // Imagine this function does something complicated
          func someArray() -> [Int]? {
              return [1, 2, 3, 4, 5, 6]
          }
          
          func example() {
              guard let array = someArray(),
          	numberThree = array[2]
          	where numberThree == 3
          	else { return }
              print(numberThree)
          }
          
          

          This doesn't work. The compiler will explain to you that it expects an optional:

          "Initializer for conditional binding must have Optional type, not 'Int'"

          So, what you oftentimes end up with, instead, is something like this:

          func example() {
              guard let array = someArray() else { return }
              let numberThree = array[2]
              guard numberThree == 3 else { return }
              print(numberThree)
          }
          

          Not only is this awful to look at, you also have to write the failure block twice. That's ok for a simple example as this one { return }, but when you have to perform a bit more work in there you'll have to repeat code blocks; and that's bad 1.

          So what's the solution here? Well, since the guard or let requires an optional, we can just as well create one and unpack it again:

          func example() {
              guard let array = someArray(),
          	numberThree = Optional.Some(array[2])
          	where numberThree == 3
          	else { return }
              print(numberThree)
          }
          

          As you may remember, Swift's optionals are internally more or less enums with a .Some and a .None case. So what we're doing here is creating a new .Some case only to unwrap it again in the very same line: The array[2] expression will be wrapped with Optional.Some and then unwrapped again into numberThree.

          There is a wee bit of overhead here, but on the other hand it does allow us to keep the guard or let unwrappings much cleaner.

          This obviously doesn't just work with array subscripts like array[3] but also with any non-optional function, i.e.:

          guard let aString = optionalString(),
              elements = Optional.Some(aString.characters.split("/")),
              last = elements.last,
              count = Optional.Some(last.characters.count),
              where count == 5 else { fatalError("Wrong Path") }
          print("We have \(count) items in \(last)")
          

          Footnotes:

          1
          Or you start refactoring this into seperate closures or functions, but that's an awful lot of work for just one guard statement

          If you read this far, you should follow me (@terhechte)
          on Twitter