Ladybug 2.0.0

Ladybug 2.0.0

TestsTested
LangLanguage SwiftSwift
License MIT
ReleasedLast Release Sep 2017
SwiftSwift Version 4.0
SPMSupports SPM

Maintained by Jeff Hurray.



Ladybug 2.0.0

Ladybug 🐞

Ladybug makes it easy to write a model or data-model layer in Swift 4. Full Codable conformance without the headache.

Quick Links

Codable vs JSONCodable?

Ladybug provides the JSONCodable protocol which is a subprotocol of Codable. Lets compare how we would create an object using Codable vs. using JSONCodable.

Lets model a Tree. I want this object to be Codable so I can decode from JSON and encode to JSON.

Here is some JSON:

{
    "tree_names": {
        "colloquial": ["pine", "big green"],
        "scientific": ["piniferous scientificus"]
    },
    "age": 121,
    "family": 1,
    "planted_at": "7-4-1896",
    "leaves": [
        {
            "size": "large",
            "is_attached": true
        },
        {
            "size": "small",
            "is_attached": false
        }
    ]
}

Using Codable 😱

Tree: Codable Implementation

struct Tree: Codable {
    
    enum Family: Int, Codable {
        case deciduous, coniferous
    }
    
    let name: String
    let family: Family
    let age: Int
    let plantedAt: Date
    let leaves: [Leaf]
    
    enum CodingKeys: String, CodingKey {
        case names = "tree_names"
        case family
        case age
        case plantedAt = "planted_at"
        case leaves
    }
    
    enum NameKeys: String, CodingKey {
        case name = "colloquial"
    }
    
    enum DecodingError: Error {
        case emptyColloquialNames
    }
    
    init(from decoder: Decoder) throws {
        let values = try decoder.container(keyedBy: CodingKeys.self)
        let namesContainer = try values.nestedContainer(keyedBy: NameKeys.self, forKey: .names)
        let names = try namesContainer.decode([String].self, forKey: .name)
        guard let firstColloquialName = names.first else {
            throw DecodingError.emptyColloquialNames
        }
        name = firstColloquialName
        family = try values.decode(Family.self, forKey: .family)
        age = try values.decode(Int.self, forKey: .age)
        plantedAt = try values.decode(Date.self, forKey: .plantedAt)
        leaves = try values.decode([Leaf].self, forKey: .leaves)
    }
    
    func encode(to encoder: Encoder) throws {
        var container = encoder.container(keyedBy: CodingKeys.self)
        var nameContainer = container.nestedContainer(keyedBy: NameKeys.self, forKey: .names)
        let colloquialNames = [name]
        try nameContainer.encode(colloquialNames, forKey: .name)
        try container.encode(family, forKey: .family)
        try container.encode(age, forKey: .age)
        try container.encode(plantedAt, forKey: .plantedAt)
        try container.encode(leaves, forKey: .leaves)
    }
    
    struct Leaf: Codable {
        
        enum Size: String, Codable {
            case small, medium, large
        }
        
        let size: Size
        let isAttached: Bool
        
        enum CodingKeys: String, CodingKey {
            case isAttached = "is_attached"
            case size
        }
        
        init(from decoder: Decoder) throws {
            let values = try decoder.container(keyedBy: CodingKeys.self)
            size = try values.decode(Size.self, forKey: .size)
            isAttached = try values.decode(Bool.self, forKey: .isAttached)
        }
        
        func encode(to encoder: Encoder) throws {
            var container = encoder.container(keyedBy: CodingKeys.self)
            try container.encode(size, forKey: .size)
            try container.encode(isAttached, forKey: .isAttached)
        }
    }
}

Codable is a great step for Swift, but as you can see here, it can get complicated really fast.

Decoding Tree: Codable

let dateFormatter = DateFormatter()
dateFormatter.dateFormat = "MM-dd-yyyy"
let decoder = JSONDecoder()
decoder.dateDecodingStrategy = .formatted(dateFormatter)
let tree = try decoder.decode(Tree_Codable.self, from: jsonData)

Encoding Tree: Codable

let dateFormatter = DateFormatter()
dateFormatter.dateFormat = "MM-dd-yyyy"
let encoder = JSONEncoder()
encoder.dateEncodingStrategy = .formatted(dateFormatter)
let data = try encoder.encode(tree)

🐞 to the Rescue!

By conforming to the JSONCodable protocol, you can skip all the boilerplate that comes with Codable while still getting Codable conformance.

Tree: JSONCodable Implementation

struct Tree: JSONCodable {
    
    enum Family: Int, Codable {
        case deciduous, coniferous
    }
    
    let name: String
    let family: Family
    let age: Int
    let plantedAt: Date
    let leaves: [Leaf]
    
    static let transformersByPropertyKey: [PropertyKey: JSONTransformer] = [
        "name": JSONKeyPath("tree_names", "colloquial", 0),
        "plantedAt": "planted_at" <- format("MM-dd-yyyy"),
        "leaves": [Leaf].transformer,
    ]
    
    struct Leaf: JSONCodable {
        
        enum Size: String, Codable {
            case small, medium, large
        }
        
        let size: Size
        let isAttached: Bool
        
        static let transformersByPropertyKey: [PropertyKey: JSONTransformer] = [
            "isAttached": "is_attached"
        ]
    }
}

As you can see, you only need provide mappings for the JSON keys that don't explicitly map to property names.

Decoding Tree: JSONCodable

let tree = try Tree(data: jsonData)

Encoding Tree: JSONCodable

let data = try tree.toData()

Ladybug will save you time and energy when creating models in Swift by providing Codable conformance without the headache.

Decoding

You can decode any object or array of objects conforming to JSONCodable from a JSON object, or Data.

/// Decode the given object from a JSON object
init(json: Any) throws
/// Decode the given object from `Data`
init(data: Data) throws

Example:

let tree = try Tree(json: treeJSON)
let forest = try Array<Tree>(json: [treeJSON, treeJSON, treeJSON])

Both initializers will throw an exception if decoding fails.

Encoding

You can encode any object or array of objects conforming to JSONCodable to a JSON object or to Data

/// Encode the object into a JSON object
func toJSON() throws -> Any
/// Encode the object into Data
func toData() throws -> Data

Example:

let jsonObject = try tree.toJSON()
let jsonData = try forest.toData()

Both functions will throw an exception if encoding fails.

Mapping JSON Keys to Properties

By conforming to the JSONCodable protocol provided by Ladybug, you can initialize any struct or final class with Data or a JSON object. If your JSON structure diverges form your data model, you can override the static transformersByPropertyKey property to provide custom mapping.

struct Flight: JSONCodable {
    
    enum Airline: String, Codable {
        case delta, united, jetBlue, spirit, other
    }
    
    let airline: Airline
    let number: Int
    
    static let transformersByPropertyKey: [PropertyKey: JSONTransformer] = [
    	"number": JSONKeyPath("flight_number")
    ]
}
...
let flightJSON = [
  "airline": "united",
  "flight_number": 472,
]
...
let directFlight = try Flight(json: flightJSON)
let flightWithLayover = try Array<Flight>(json: [flightJSON, otherFlightJSON])

directFlight and flightWithLayover are fully initialized and can be encoded and decoded. Simple as that.

Note: Any nested enum must conform to Codable and RawRepresentable where the RawValue is Codable.

Note: PropertyKey is a String typealias.

You can associate JSON keys with properties via different objects conforming to JSONTransformer.

Transformers are provided via a readonly static property of the JSONCodable protocol, and are indexed by PropertyKey.

static var transformersByPropertyKey: [PropertyKey: JSONTransformer] { get }

Ok, it gets a little more complicated, but its easy, I swear.

Accessing JSON Values: JSONKeyPath

In the example at the beginning we used JSONKeyPath to map the value associated with the tree_name field to the name property of Tree.

JSONKeyPath is used to access values in JSON. It is initialized with a variadic list of json subscripts (Int or String).

In the example below:

  • JSONKeyPath("foo") maps to {"hello": "world"}
  • Similarly, "foo" maps to {"hello": "world"}
  • JSONKeyPath("foo", "hello") maps to "world"
  • JSONKeyPath("bar", 0) maps to "lorem"
{
  "foo": {
     "hello": "world"
  },
  "bar": [ 
  	 "lorem",
  	 "ipsum"
  ]  
}

Note: These key paths are used optionally in objects conforming to JSONTransformer when the property being mapped to does not match the json structure. If the property name is the same as the key path, you dont need to include the key path.

Note: JSONKeyPath can also be expressed as a string literal.

JSONKeyPath("some_key") == "some_key"

Note: You can also use Objective-C keypath notation.

JSONKeyPath("foo", "hello") == JSONKeyPath("foo.hello") == "foo.hello"

This does not work for Int subscripts

JSONKeyPath("bar", 1) != JSONKeyPath("bar.1")

Nested Objects

Lets add a nested class, Passenger. Flights have passengers. Nice.

You can denote a nested object via the static transformer property of any object or array of objects conforming to JSONCodable.

You can combine transformers using the <- operator. In this case, for the airMarshal property, both the key path and the nested object need explicit transforms.

{
  "airline": "united",
  "flight_number": 472,
  "air_marshal" {
     "name": "50 Cent",
  },
  "passengers": [
  	  {
  	  "name": "Jennifer Lawrence",
  	  },
  	  {
  	  "name": "Chris Pratt"
  	  },
  	  ... 
  ]
}
struct Flight: JSONCodable {
	...
    let passengers: [Passenger]
    let airMarshal: Passenger
    ...
    static let transformersByPropertyKey: [PropertyKey: JSONTransformer] = [
    	...
    	"passengers": [Passenger].transformer,
    	"airMarshal": "air_marshal" <- Passenger.transformer
    ]
    
    struct Passenger: JSONCodable {
        let name: String
    }
}

Note: When using the <- operator, always put the JSONKeyPath transformer first.

Dates

Finally, lets add dates to the mix. Ladybug provides multiple date transformers:

  • secondsSince1970: Decode the date as a UNIX timestamp from a JSON number.
  • millisecondsSince1970: Decode the date as UNIX millisecond timestamp from a JSON number.
  • iso8601: Decode the date as an ISO-8601-formatted string (in RFC 3339 format).
  • format(_ format: String): Decode the date with a custom date format string.
  • custom(_ adapter: @escaping (Any?) -> Date?): Return a Date from the JSON value.
{
"july4th": "7/4/1776",
"y2k": 946684800,
}
struct SomeDates: JSONCodable {
    let july4th: Date
    let Y2K: Date
    let createdAt: Date
    
    static let transformersByPropertyKey: [PropertyKey: JSONTransformer] = [
        "july4th": format("MM/dd/yyyy"),
        "Y2K": "y2k" <- secondsSince1970,
        "createdAt": custom { _ in return Date() }
    ]
}

Note: If using custom to map to a non-optional Date, returning nil will result in an exception being thrown during decoding.

Additional Mapping: Map<T: Codable>

If you need to provide a simple mapping from a JSON value to a property, use MapTransformer. A great example is using this to convert a string to an integer.

{
"count": "100"
}
...
struct BottlesOfBeerOnTheWall: JSONCodable {
    let count: Int
    
    static let transformersByPropertyKey: [PropertyKey: JSONTransformer] = [
    	"count": Map<Int> { return Int($0 as! String) }
    ]
}

Default Values / Migrations: Default

If you wish to supply a default value for a property, you can use Default. You supply the default value, and can also control whether or not to override the property if the property key exists in the JSON payload.

init(value: Any, override: Bool = false)

The default transformer is useful when API's change, and can help migration from cached JSON data to JSONCodable objects with new properties.

Using JSONCodable as a Generic Constraint

Because Array does not explicitly conform to JSONCodable, JSONCodable does not support list types when used as a generic constraint. If you need this support, you can use the List<T: JSONCodable> wrapper type.

struct Tweet: JSONCodable { ... }
class ContentProvider<T: JSONCodable> { ... }

let tweetDetailProvider = ContentProvider<Tweet>()
let timelineProvider = ContentProvider<List<Tweet>>()

Handling Failure

Exceptions

Ladybug is failure driven, and all JSONCodable initializers and encoding mechanisms throw exceptions if they fail. There is a JSONCodableError type that Ladybug will throw if there is a typecasting error, and Ladybug will also throw exceptions from JSONSerialization, JSONDecoder, and JSONEncoder.

Optionals

If a value is optional in your JSON payload, it should be optional in your data model. Ladybug will only throw an exception if a key is missing and the property it is being mapped to is non-optional. Play it safe kids, use optionals.

Safety for Map and Custom Dates

There are 2 transformers that can return nil values: Map<T: Codable> and custom(_ adapter: @escaping (Any?) -> Date?).

If you are decoding from an already encoded JSONCodable object, returning nil is fine.

If you are decoding from a URLResponse, returning nil can lead to an exception being thrown.

Class Conformance to JSONCodable

There are 2 small caveat to keep in mind when you are conforming a class to JSONCodable:

  1. Because classes in swift dont come with baked in default initializers like structs do, you have to make sure properties are initialized. You can do this by supplying default values, or a default initializer that initializes these values.

You can see examples in ClassConformanceTests.swift.

  1. Subclassing an object conforming to Codable will not work, so it won't work for JSONCodable either.

Because of these caveats, I would suggest using structs for your data models.

Thoughts About 🐞

It would be pretty great if AnyKeyPath could generate a string for its associated property

If Swift 4 key paths exposed a string value, we could use PartialKeyPath<Self> as our PropertyKey typealias instead of String. This would be a much safer alternative.

 typealias PropertyKey = PartialKeyPath<Self>
...
static var transformersByPropertyKey: [PropertyKey: JSONTransformer] = [
	\Tree.name: JSONKeyPath("tree_name") 
]

There was no disussion of this in SE-0161.

It would also be great if Mirror could be created for types instead of instances

This would allow us to implicitly map nested objects conforming to JSONCodable.

Whats wrong with Codable?

As mentioned before, Codable is a great step towards simplifying JSON parsing in swift, but the O(n) boilerplate that has become a mainstay in swift JSON parsing still exists when using Codable (e.g. For every property your object has, you need to write 1 or more lines of code to map the json to said property). In Apple's documentation on Encoding and Decoding Custom Types, you can see that as soon as JSON keys diverge from property keys, you have to write a ton of boilerplate code to get Codable conformance. Ladybug sidesteps this, and does a lot of this for you under the hood.

Be careful with MapTransformer

Its easy to go a little to far with MapTransformer. In the example below, the map transformer is being used to calculate a sum instead of mapping a JSON value to a Codable type. To me, this promotes bad data modeling. I'm a firm believer that data models should closely mirror JSON responses. When used in the wrong way, map transformers can give too data models too much responsibility.

{
"values": [1, 1, 2, 3, 5, 8, 13]
}
... 
struct FibonacciSequence: JSONCodable {
	let values: [Int]
	let sum: Int
	
	static let transformersByPropertyKey: [PropertyKey: JSONTransformer] = [
		"sum": MapTransformer<Int>(keyPath: "values") { value in
			let values = value as! [Int]
			return values.reduce(0) { $0 + $1 }
		}
	]
}

Credits

Shoutout to the good folks at Mantle for giving me some inspiration on this project. I'm pretty happy a similar framework is finally possible for Swift without mixing in Obj-C runtime.

Contact Info && Contributing

Feel free to email me at [email protected] or hit me up on the twitterverse. I'd love to hear your thoughts on this, or see examples where this has been used.

MIT License