Compatibility
- 6.3.0 and master5.35.25.15.04.2
- 6.3.0iOSmacOS(Intel)macOS(ARM)LinuxtvOSwatchOS
- masteriOSmacOS(Intel)macOS(ARM)LinuxtvOSwatchOS
Elegant Reactive Primitives for Clean Swift Architecture #NoRx
SwiftObserver is a lightweight framework for reactive Swift. Its design goals make it easy to learn and a joy to use:
SwiftObserver is only 1800 lines of production code, but it's well beyond a 1000 hours of work, re-imagining and reworking it many times, letting go of fancy features, documenting, unit-testing, and battle-testing it in practice.
Reactive Programming adresses the central challenge of implementing effective architectures: controlling dependency direction, in particular making specific concerns depend on abstract ones. SwiftObserver breaks reactive programming down to its essence, which is the Observer Pattern.
SwiftObserver diverges from convention as it doesn't inherit the metaphors, terms, types, or function- and operator arsenals of common reactive libraries. It's not as fancy as Rx and Combine and not as restrictive as Redux. Instead, it offers a powerful simplicity you might actually love to work with.
With the Swift Package Manager, you add the SwiftObserver package via Xcode (11+).
Or you manually adjust the Package.swift file of your project:
// swift-tools-version:5.1
import PackageDescription
let package = Package(
name: "MyApp",
dependencies: [
.package(url: "https://github.com/flowtoolz/SwiftObserver.git",
.upToNextMajor(from: "6.2.0"))
],
targets: [
.target(name: "MyAppTarget",
dependencies: ["SwiftObserver"])
]
)
Then run $ swift build
or $ swift run
.
With Cocoapods, adjust your Podfile:
target "MyAppTarget" do
pod "SwiftObserver", "~> 6.2"
end
Then run $ pod install
.
Finally, in your Swift files:
import SwiftObserver
No need to learn a bunch of arbitrary metaphors, terms or types.
SwiftObserver is simple: Objects observe other objects.
Or a tad more technically: Observables send messages to their observers.
That's it. Just readable code:
dog.observe(Sky.shared) { color in
// marvel at the sky changing its color
}
Any object can be an Observer
if it has a Receiver
for receiving messages:
class Dog: Observer {
let receiver = Receiver()
}
The receiver keeps the observer's observations alive. The observer just holds on to it strongly.
Observer
/Receiver
must still be alive. There's no awareness after death in memory.Observer
can do multiple simultaneous observations of the same Observable
, for example by calling observe(...)
multiple times.observer.isObserving(observable)
.Any object can be Observable
if it has a Messenger<Message>
for sending messages:
class Sky: Observable {
let messenger = Messenger<Color>() // Message == Color
}
Observable
sends messages via send(_ message: Message)
. The observable's clients, even its observers, are also free to call that function.Observable
delivers messages in exactly the order in which send
is called, which helps when observers, from their message handling closures, somehow trigger further calls of send
.Observable
does not trigger it to send a message. This keeps everything simple, predictable and consistent.Messenger<Message>
. It's a mediator through which other entities communicate.Observable
class that utilizes Messenger<Message>
.Variable<Value>
(a.k.a. Var<Value>
). It holds a value and sends value updates.Observable
.When an Observer
or Observable
dies, SwiftObserver cleans up all related observations automatically, making memory leaks impossible. So there isn't really any memory management to worry about.
However, observers and observables can stop particular- or all their ongoing observations:
dog.stopObserving(Sky.shared) // no more messages from the sky
dog.stopObserving() // no more messages from anywhere
Sky.shared.stopBeingObserved(by: dog) // no more messages to dog
Sky.shared.stopBeingObserved() // no more messages to anywhere
You may start an observation without an explicit observer:
observe(Sky.shared) { color in
// marvel at the sky changing its color
}
Sky.shared.observed { color in // ... same
// ...
}
Both examples internally use the global observer FreeObserver.shared
. You may reference FreeObserver.shared
explicitly to stop particular or all such free global observations.
You can also instantiate your own FreeObserver
to do observations even more "freely". Just keep it alive as long as the observation shall last. Such a free observer is like a "Cancellable" or "Token" in other reactive frameworks.
And you can do one-time observations:
observeOnce(Sky.shared) { color in
// notice new color. observation has stopped.
}
Sky.shared.observedOnce { color in // ... same
// ...
}
Both functions return the involved FreeObserver
as a discardable result. Typically we ignore that observer and it will die together with the observation as soon as it has received one message.
Messenger
is the simplest Observable
and the basis of every other Observable
. It doesn't send messages by itself, but anyone can send messages through it and use it for any type of message:
let textMessenger = Messenger<String>()
observer.observe(textMessenger) { textMessage in
// respond to textMessage
}
textMessenger.send("my message")
Messenger
embodies the common messenger / notifier pattern and can be used for that out of the box.
Having a Messenger
is actually what defines Observable
objects:
public protocol Observable: class {
var messenger: Messenger<Message> { get }
associatedtype Message: Any
}
Messenger
is itself Observable
because it points to itself as the required Messenger
:
extension Messenger: Observable {
public var messenger: Messenger<Message> { self }
}
Every other Observable
class is either a subclass of Messenger
or a custom Observable
class that provides a Messenger
. Custom observables often employ some enum
as their message type:
class Model: SuperModel, Observable {
func foo() { send(.willUpdate) }
func bar() { send(.didUpdate) }
deinit { send(.willDie) }
let messenger = Messenger<Event>() // Message == Event
enum Event { case willUpdate, didUpdate, willDie }
}
Var<Value>
is an Observable
that has a property value: Value
.
Whenever its value
changes, Var<Value>
sends a message of type Update<Value>
, informing about the old
and new
value:
let number = Var(42)
observer.observe(number) { update in
let whatsTheBigDifference = update.new - update.old
}
In addition, you can always manually call variable.send()
(without argument) to send an update in which old
and new
both hold the current value
(see Cached Messages
).
Value
must be Equatable
, and based on its value
the whole Var<Value>
is Equatable
. Where Value
is Comparable
, Var<Value>
will also be Comparable
.
You can set value
via initializer, directly and via the <-
operator:
let text = Var<String?>() // text.value == nil
text.value = "a text"
let number = Var(23) // number.value == 23
number <- 42 // number.value == 42
If Value
is some number type Number
that is either an Int
, Float
or Double
:
Every Var<Number>
, Var<Number?>
, Var<Number>?
and Var<Number?>?
has a respective property var int: Int
, var float: Float
or var double: Double
. That property is non-optional and interprets nil
values as zero.
You can apply numeric operators +
, -
, *
and /
to all pairs of Number
, Number?
, Var<Number>
, Var<Number?>
, Var<Number>?
and Var<Number?>?
.
let numVar = Var<Int?>() // numVar.value == nil
print(numVar.int) // 0
numVar.int += 5 // numVar.value == 5
numVar <- Var(1) + 2 // numVar.value == 3
Var<String>
, Var<String?>
, Var<String>?
and Var<String?>?
has a property var string: String
. That property is non-optional and interprets nil
values as ""
.+
to all pairs of String
, String?
, Var<String>
, Var<String?>
, Var<String>?
and Var<String?>?
.string
property, every Var<String>
and Var<String?>
conforms to TextOutputStream
, BidirectionalCollection
, Collection
, Sequence
, CustomDebugStringConvertible
and CustomStringConvertible
.A Var<Value>
is automatically Codable
if its Value
is. So when one of your types has Var
properties, you can make that type Codable
by simply adopting the Codable
protocol:
class Model: Codable {
private(set) var text = Var("String Variable")
}
Note that text
is a var
instead of a let
. It cannot be constant because Swift's implicit decoder must mutate it. However, clients of Model
would be supposed to set only text.value
and not text
itself, so the setter is private.
Transforms make common steps of message processing more succinct and readable. They allow to map, filter and unwrap messages in many ways. You may freely chain these transforms together and also define new ones with them.
This example transforms messages of type Update<String?>
into ones of type Int
:
let title = Var<String?>()
observer.observe(title).new().unwrap("Untitled").map({ $0.count }) { titleLength in
// do something with the new title length
}
You may transform a particular observation directly on the fly, like in the above example. Such ad hoc transforms give the observer lots of flexibility.
Or you may instantiate a new Observable
that has the transform chain baked into it. The above example could then look like this:
let title = Var<String?>()
let titleLength = title.new().unwrap("Untitled").map { $0.count }
observer.observe(titleLength) { titleLength in
// do something with the new title length
}
Every transform object exposes its underlying Observable
as origin
. You may even replace origin
:
let titleLength = Var("Dummy Title").new().map { $0.count }
let title = Var("Real Title")
titleLength.origin.origin = title
Such stand-alone transforms can offer the same preprocessing to multiple observers. But since these transforms are distinct Observable
objects, you must hold them strongly somewhere. Holding transform chains as dedicated observable objects suits entities like view models that represent transformations of other data.
Whether you apply transforms ad hoc or as stand-alone objects, they work the same way. The following list illustrates prebuilt transforms as observable objects.
First, there is your regular familiar map
function. It transforms messages and often also their type:
let messenger = Messenger<String>() // sends String
let stringToInt = messenger.map { Int($0) } // sends Int?
When an Observable
like a Var<Value>
sends messages of type Update<Value>
, we often only care about the new
value, so we map the update with new()
:
let errorCode = Var<Int>() // sends Update<Int>
let newErrorCode = errorCode.new() // sends Int
When you want to receive only certain messages, use filter
:
let messenger = Messenger<String>() // sends String
let shortMessages = messenger.filter { $0.count < 10 } // sends String if length < 10
Use select
to receive only one specific message. select
works with all Equatable
message types. select
maps the message type onto Void
, so a receiving closure after a selection takes no message argument:
let messenger = Messenger<String>() // sends String
let myNotifier = messenger.select("my notification") // sends Void (no messages)
observer.observe(myNotifier) { // no argument
// someone sent "my notification"
}
Sometimes, we make message types optional, for example when there is no meaningful initial value for a Var
. But we often don't want to deal with optionals down the line. So we can use unwrap()
, suppressing nil
messages entirely:
let errorCodes = Messenger<Int?>() // sends Int?
let errorAlert = errorCodes.unwrap() // sends Int if the message is not nil
You may also unwrap optional messages by replacing nil
values with a default:
let points = Messenger<Int?>() // sends Int?
let pointsToShow = points.unwrap(0) // sends Int with 0 for nil
You may chain transforms together:
let numbers = Messenger<Int>()
observer.observe(numbers).map {
"\($0)" // Int -> String
}.filter {
$0.count > 1 // suppress single digit integers
}.map {
Int.init($0) // String -> Int?
}.unwrap { // Int? -> Int
print($0) // receive and process resulting Int
}
Of course, ad hoc transforms like the above end on the actual message handling closure. Now, when the last transform in the chain also takes a closure argument for its processing, like map
and filter
do, we use receive
to stick with the nice syntax of trailing closures:
dog.observe(Sky.shared).map {
$0 == .blue
}.receive {
print("Will we go outside? \($0 ? "Yes" : "No")!")
}
Promise<Value>
helps managing asynchronous returns and makes that intention explicit.
Side Note:
Promise
is part of SwiftObserver because Combine'sFuture
is unfortunately an impractical and incomplete solution for one-shot asynchronous calls and to depend on PromiseKit or Vapor/NIO's Async might be overkill (and too server-specific) in many contexts. Also, integrating promises in SwiftObserver offers the advantages of consistency, simplicity and readability. However, at some point all promise/future implementations will be obsolete due to Swift's async/await.
func getID() -> Promise<Int> { // getID() promises an Int
Promise { promise in // convenience initializer
getIDAsync { id in // handler retains the promise until it's fulfilled
promise.fulfill(id)
}
}
}
getID().whenFulfilled { id in // get id (if fulfilled) or observe promise
// do somethin with the ID
}
A Promise
is either fulfilled or not. When it is fulfilled it stays that way. When a function returns a Promise
, that promise might already be fulfilled and not change anymore. Also, mappings are the only transforms that make sense on promises. So, to guard against mistakes, Promise
is not directly Observable
. Instead we call whenFulfilled
on it, which does an internal one-shot observation of the promise if the promise isn't yet fulfilled.
Typically, promises are shortlived objects that we don't hold on to. That works fine since an asynchronous function like getID()
that returns a promise keeps that promise alive in order to fulfill it. So we get the promised value asynchronously without even holding the promise anywhere, and the promise as well as its internal observations get cleaned up automatically when the promise is fulfilled and dies.
Sometimes, we wanna do multiple things with an asynchronous result (long) after receiving it:
let idPromise = getID() // Promise<Int>
idPromise.whenFulfilled { id in
// do somethin with id
}
idPromise.whenFulfilled { id in
// do somethin else with id
}
promise { // establish context and increase readability
getInt() // return a Promise<Int>
}.then { // chain another promise sequentially
getString(takeInt: $0) // take Int sent by 'promise', return a Promise<String>
}.whenFulfilled { // observation dies when promise 'then' is fulfilled
print($0) // print String sent by promise 'then'
}
promise
is for readability. It allows for nice consistent closure syntax and makes it clear that we're working with promises. It takes a closure that returns a Promise
and simply returns that Promise
.
We call then
on a first Promise
and pass it a closure that returns a second Promise
. That closure takes the value of the first promise, allowing the second promise to depend on the value of the first. then
returns a new Promise
that provides the value of the second promise.
promise {
getInt()
}.and { // chain another promise concurrently
getString()
}.whenFulfilled {
print($0.0) // print Int sent by 'promise'
print($0.1) // print String sent by promise 'getString()'
}
We call and
on a Promise
and pass it a closure that returns another Promise
. This immediatly observes both promises and returns a new Promise
that provides the combined values of both.
promise {
getInt()
}.whenFulfilled { // returns 'promise' so the chain can continue
print($0) // print Int sent by 'promise'
}.map { // chain a mapping promise sequentially
"\($0)" // map Int sent by promise 'whenFulfilled' to String
}.whenFulfilled {
print($0) // print String sent by promise 'map'
}
Transform functions that neither filter messages nor exclusively create standalone transforms return a new Promise
when called on a Promise
. These functions are map(...)
, unwrap(default)
and new()
. The advantage here is, as with any function that returns a promise, that we don't need to keep that promise alive in order to receive the promised value.
A function that can fail cannot promise a pure value. It can only promise a Result
, which contains a value on success and an error on failure:
func getID() -> ResultPromise<Int> { // typealias for Promise<Result<Int, Error>>
Promise { promise in
getIDAsync { result in
promise.fulfill(result) // fulfill with Result, Result.Value or Error
}
}
}
getID().whenSucceeded { id in // corresponds to whenFulfilled
// do somethin with id
} failed: { error in // whenSucceeded requires handling failure
// do somethin with error
}
When composing result promises, we often only care about either success or failure:
promise {
getID()
}.whenFailed { // whenFailed / whenSucceeded don't need to end the chain
log(error: $0)
}.onSuccess { // corresponds to then
getName(forID: $0)
}.mapSuccess { // corresponds to map
try Data(name: $0) // mapSuccess, onSuccess and whenSucceeded can throw
} // finally returns a ResultPromise<Data>
Every closure that handles the success case can throw an Error
.
Every message has an author associated with it. This feature is only noticable in code if we use it.
An observable can send an author together with a message via observable.send(message, from: author)
. If noone specifies an author as in observable.send(message)
, the observable itself becomes the author.
Variables have a special value setter that allows to identify change authors:
let number = Var(0)
number.set(42, as: controller) // controller becomes author of the update message
The observer can receive the author, by adding it as an argument to the message handling closure:
observer.observe(observable) { message, author in
// process message from author
}
Through the author, observers can determine a message's origin. In the plain messenger pattern, the origin would simply be the message sender.
Identifying message authors can become essential whenever multiple observers observe the same observable while their actions can cause it so send messages.
Mutable data is a common type of such shared observables. For example, when multiple entities observe and modify a storage abstraction or caching hierarchy, they often want to avoid reacting to their own actions. Such overreaction might lead to redundant work or inifnite response cycles. So they identify as change authors when modifying the data and ignore messages from self
when observing it:
class Collaborator: Observer {
func observeText() {
observe(sharedText).notFrom(self) { update, author in // see author filters below
// someone else edited the text
}
}
func editText() {
sharedText.set("my new text", as: self) // identify as change author
}
let receiver = Receiver()
}
let sharedText = Var<String>()
There are three transforms related to message authors. As with other transforms, we can apply them directly in observations or create them as standalone observables.
We filter authors just like messages:
let messenger = Messenger<String>() // sends String
let friendMessages = messenger.filterAuthor { // sends String if message is from friend
friends.contains($0)
}
If only one specific author is of interest, filter authors with from
. It captures the selected author weakly:
let messenger = Messenger<String>() // sends String
let joesMessages = messenger.from(joe) // sends String if message is from joe
If all but one specific author are of interest, use notFrom
. It also captures the excluded author weakly:
let messenger = Messenger<String>() // sends String
let humanMessages = messenger.notFrom(hal9000) // sends String, but not from an evil AI
An ObservableCache
is an Observable
that has a property latestMessage: Message
which typically returns the last sent message or one that indicates that nothing has changed. ObservableCache
has a function send()
that takes no argument and sends latestMessage
.
Any Var
is an ObservableCache
. Its latestMessage
is an Update
in which old
and new
both hold the current value
.
Calling cache()
on an Observable
creates a transform that is an ObservableCache
. That cache's Message
will be optional but never an optional optional, even when the origin's Message
is already optional.
Of course, cache()
wouldn't make sense as an adhoc transform of an observation, so it can only create a distinct observable object.
Any transform whose origin is an ObservableCache
is itself implicitly an ObservableCache
if it never suppresses (filters) messages. These compatible transforms are: map
, new
and unwrap(default)
.
Note that the latestMessage
of a transform that is an implicit ObservableCache
returns the transformed latestMessage
of its underlying ObservableCache
origin. Calling send(transformedMessage)
on that transform itself will not "update" its latestMessage
.
Custom observables can easily conform to ObservableCache
. Even if their message type isn't based on some state, latestMessage
can still return a meaningful default value - or even nil
where Message
is optional.
An Observable
like Var
, that derives its messages from its state, can generate a "latest message" on demand and therefore act as an ObservableCache
:
class Model: Messenger<String>, ObservableCache { // informs about the latest state
var latestMessage: String { state } // ... either on demand
var state = "initial state" {
didSet {
if state != oldValue {
send(state) // ... or when the state changes
}
}
}
}
When you want to put an Observable
into some data structure or as the origin into a transform object but hold it there as a weak
reference, transform it via observable.weak()
:
let number = Var(12)
let weakNumber = number.weak()
observer.observe(weakNumber) { update in
// process update of type Update<Int>
}
var weakNumbers = [Weak<Var<Int>>]()
weakNumbers.append(weakNumber)
Of course, weak()
wouldn't make sense as an adhoc transform, so it can only create a distinct observable object.