Elevate is a JSON parsing framework that leverages Swift to make parsing simple, reliable and composable.
Elevate should no longer be used for new feature development. We recommend using the
Codable
protocol provided by Apple in theFoundation
framework in its place. We will continue to support and update Elevate for the foreseeable future.
- Validation of full JSON payload
- Parse complex JSON into strongly typed objects
- Support for optional and required values
- Convenient and flexible protocols to define object parsing
- Large object graphs can be parsed into their component objects
- Error aggregation across entire object graph
- iOS 10.0+ / macOS 10.12+ / tvOS 10.0+ / watchOS 3.0+
- Xcode 10.2+
- Swift 5.0+
- Need help? Open an issue.
- Have a feature request? Open an issue.
- Find a bug? Open an issue.
- Want to contribute? Fork the repo and submit a pull request.
CocoaPods is a dependency manager for Cocoa projects. You can install it with the following command:
[sudo] gem install cocoapods
CocoaPods 1.3+ is required.
To integrate Elevate into your Xcode project using CocoaPods, specify it in your Podfile:
source 'https://github.com/CocoaPods/Specs.git'
platform :ios, '11.0'
use_frameworks!
pod 'Elevate', '~> 3.0'
Carthage is a decentralized dependency manager that builds your dependencies and provides you with binary frameworks.
You can install Carthage with Homebrew using the following command:
brew update
brew install carthage
To integrate Elevate into your Xcode project using Carthage, specify it in your Cartfile:
github "Nike-Inc/Elevate" ~> 3.0
To build Elevate on iOS only, use the following Carthage command:
carthage update --platform iOS
Elevate aims to make JSON parsing and validation simple, yet robust.
This is achieved through a set of protocols and classes that can be utilized to create Decodable
and Decoder
classes.
By using Elevate's parsing infrastructure, you'll be able to easily parse JSON data into strongly typed model objects or simple dictionaries by specifying each property key path and its associated type.
Elevate will validate that the keys exist (if they're not optional) and that they are of the correct type.
Validation errors will be aggregated as the JSON data is parsed.
If an error is encountered, a ParserError
will be thrown.
Elevate also supports encoding model objects back into JSON objects through the light-weight Encodable
protocol.
Convenience extensions have been added to collection types to make it easy to encode nested objects in a single pass.
After you have made your model objects Decodable
or implemented a Decoder
for them, parsing with Elevate is as simple as:
let avatar: Avatar = try Elevate.decodeObject(from: data, atKeyPath: "response.avatar")
Pass an empty string into
atKeyPath
if your object or array is at the root level.
In the previous example Avatar
implements the Decodable
protocol.
By implementing the Decodable
protocol on an object, it can be used by Elevate to parse avatars from JSON data as a top-level object, a sub-object, or even an array of avatar objects.
public protocol Decodable {
init(json: Any) throws
}
The json: Any
will typically be a [String: Any]
instance that was created from the JSONSerialization
APIs.
Use the Elevate Parser.parseEntity
method to define the structure of the JSON data to be validated and perform the parsing.
struct Person {
let identifier: String
let name: String
let nickname: String?
let birthDate: Date
let isMember: Bool?
let addresses: [Address]
}
extension Person: Elevate.Decodable {
fileprivate struct KeyPath {
static let id = "identifier"
static let name = "name"
static let nickname = "nickname"
static let birthDate = "birthDate"
static let isMember = "isMember"
static let addresses = "addresses"
}
init(json: Any) throws {
let dateDecoder = DateDecoder(dateFormatString: "yyyy-MM-dd")
let entity = try Parser.parseEntity(json: json) { schema in
schema.addProperty(keyPath: KeyPath.id, type: .int)
schema.addProperty(keyPath: KeyPath.name, type: .string)
schema.addProperty(keyPath: KeyPath.nickname, type: .string, optional: true)
schema.addProperty(keyPath: KeyPath.birthDate, type: .string, decoder: dateDecoder)
schema.addProperty(keyPath: KeyPath.isMember, type: .bool, optional: true)
schema.addProperty(keyPath: KeyPath.addresses, type: .array, decodableType: Address.self)
}
self.identifier = entity <-! KeyPath.id
self.name = entity <-! KeyPath.name
self.nickname = entity <-? KeyPath.nickname
self.birthDate = entity <-! KeyPath.birthDate
self.isMember = entity <-? KeyPath.isMember
self.addresses = entity <--! KeyPath.addresses
}
}
Implementing the Decodable
protocol in this way allows you to create fully intialized structs that can contain non-optional constants from JSON data.
Some other things worth noting in this example:
- The
Decodable
protocol conformance was implemented as an extension on the struct. This allows the struct to keep its automatic memberwise initializer. - Standard primitive types are supported as well as
URL
,Array
, andDictionary
types. SeeParserPropertyProtocol
definition for the full list. - Elevate facilitates passing a parsed property into a
Decoder
for further manipulation. See thebirthDate
property in the example above. TheDateDecoder
is a standardDecoder
provided by Elevate to make date parsing hassle free. - A
Decoder
orDecodable
type can be provided to a property of type.Array
to parse each item in the array to that type. This also works with the.Dictionary
type to parse a nested JSON object. - The parser guarantees that properties will be of the specified type.
Therefore, it is safe to use the custom operators to automatically extract the
Any
value from theentity
dictionary and cast it to the return type.
Elevate contains four property extraction operators to make it easy to extract values out of the entity
dictionary and cast the Any
value to the appropriate type.
<-!
- Extracts the value from theentity
dictionary for the specified key. This operator should only be used on non-optional properties.<-?
- Extracts the optional value from theentity
dictionary for the specified key. This operator should only be used on optional properties.<--!
- Extracts the array from theentity
dictionary for the specified key as the specified array type. This operator should only be used on non-optional array properties.<--?
- Extracts the array from theentity
dictionary for the specified key as the specified optional array type.
Extending a model object to conform to the Encodable
protocol is less involved than making it Decodable
.
Since your object is already strongly typed, it only needs to be converted into a JSON friendly Any
object.
Building on the previous Person
type, let's make it conform to the Encodable
protocol.
extension Person: Elevate.Encodable {
var json: Any {
var json: [String: Any] = [
KeyPath.id: identifier,
KeyPath.name: name,
KeyPath.birthDate: birthDate,
KeyPath.addresses: addresses.json
]
if let nickname = nickname { json[KeyPath.nickname] = nickname }
if let isMember = isMember { json[KeyPath.isMember] = isMember }
return json
}
}
As you can see in the example, converting the Person
into a JSON dictionary is straightforward.
It's also easy to convert the array of Address
objects into JSON by calling the json
property on the array.
This works because Address
also conforms to Encodable
.
The collection type extensions on Array
, Set
and Dictionary
make it easy to convert a complex objects with multiple layers of Encodable
objects into a JSON objects.
In most cases implementing a Decodable
model object is all that is needed to parse JSON using Elevate.
There are some instances though where you will need more flexibility in the way that the JSON is parsed.
This is where the Decoder
protocol comes in.
public protocol Decoder {
func decode(_ object: Any) throws -> Any
}
A Decoder
is generally implemented as a separate object that returns instances of the desired model object.
This is useful when you have multiple JSON mappings for a single model object, or if you are aggregating data across multiple JSON payloads.
For example, if there are two separate services that return JSON for Avatar
objects that have a slightly different property structure, a Decoder
could be created for each mapping to handle them individually.
The input type and output types are intentionally vague to allow for flexibility. A
Decoder
can return any type you want -- a strongly typed model object, a dictionary, etc. It can even dynamically return different types at runtime if needed.
class AvatarDecoder: Elevate.Decoder {
func decode(_ object: Any) throws -> Any {
let urlKeyPath = "url"
let widthKeyPath = "width"
let heightKeyPath = "height"
let entity = try Parser.parseEntity(json: object) { schema in
schema.addProperty(keyPath: urlKeyPath, type: .url)
schema.addProperty(keyPath: widthKeyPath, type: .int)
schema.addProperty(keyPath: heightKeyPath, type: .int)
}
return Avatar(
URL: entity <-! urlKeyPath,
width: entity <-! widthKeyPath,
height: entity <-! heightKeyPath
)
}
}
class AlternateAvatarDecoder: Elevate.Decoder {
func decode(_ object: Any) throws -> Any {
let locationKeyPath = "location"
let wKeyPath = "w"
let hKeyPath = "h"
let entity = try Parser.parseEntity(json: object) { schema in
schema.addProperty(keyPath: locationKeyPath, type: .url)
schema.addProperty(keyPath: wKeyPath, type: .int)
schema.addProperty(keyPath: hKeyPath, type: .int)
}
return Avatar(
URL: entity <-! locationKeyPath,
width: entity <-! wKeyPath,
height: entity <-! hKeyPath
)
}
}
Then to use the two different Decoder
objects with the Parser
:
let avatar1: Avatar = try Elevate.decodeObject(
from: data1,
atKeyPath: "response.avatar",
with: AvatarDecoder()
)
let avatar2: Avatar = try Elevate.decodeObject(
from: data2,
atKeyPath: "alternative.response.avatar",
with: AlternateAvatarDecoder()
)
Each Decoder
is designed to handle a different JSON structure for creating an Avatar
.
Each uses the key paths specific to the JSON data it's dealing with, then maps those back to the properties on the Avatar
object.
This is a very simple example to demonstration purposes.
There are MANY more complex examples that could be handled in a similar manner via the Decoder
protocol.
A second use for the Decoder
protocol is to allow for the value of a property to be further manipulated.
The most common example is a date string.
Here is how the DateDecoder
implements the Decoder
protocol:
public func decode(_ object: Any) throws -> Any {
if let string = object as? String {
return try dateFromString(string, withFormatter:self.dateFormatter)
} else {
let description = "DateParser object to parse was not a String."
throw ParserError.Validation(failureReason: description)
}
}
And here is how it's used to parse a JSON date string:
let dateDecoder = DateDecoder(dateFormatString: "yyyy-MM-dd 'at' HH:mm")
let entity = try Parser.parseEntity(data: data) { schema in
schema.addProperty(keyPath: "dateString", type: .string, decoder: dateDecoder)
}
You are free to create any decoders that you like and use them with your properties during parsing.
Some other uses would be to create a StringToBoolDecoder
or StringToFloatDecoder
that parses a Bool
or Float
from a JSON string value.
The DateDecoder
and StringToIntDecoder
are already included in Elevate for your convenience.