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flowtoolz/SwiftObserver 6.3.0
Elegant Reactive Primitives for Clean Swift Architecture #NoRx
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πŸ•“ 2 weeks ago
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.package(url: "https://github.com/flowtoolz/SwiftObserver.git", from: "6.3.0")



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SwiftObserver is a lightweight framework for reactive Swift. Its design goals make it easy to learn and a joy to use:

  1. Meaningful Code πŸ’‘
    SwiftObserver promotes meaningful metaphors, names and syntax, producing highly readable code.
  2. Non-intrusive Design ✊🏻
    SwiftObserver doesn't limit or modulate your design. It just makes it easy to do the right thing.
  3. Simplicity πŸ•Ή
    SwiftObserver employs few radically simple concepts and applies them consistently without exceptions.
  4. Flexibility πŸ€ΈπŸ»β€β™€οΈ
    SwiftObserver's types are simple but universal and composable, making them applicable in many situations.
  5. Safety β›‘
    SwiftObserver does the memory management for you. Oh yeah, memory leaks are impossible.

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.

Why the Hell Another Reactive Swift Framework?

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.


Get Involved

Get Started


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:5.4
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.

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: Observable objects 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.

Notes on Observers

  • For a message receiving closure to be called, the Observer/Receiver must still be alive. There's no awareness after death in memory.
  • An Observer can do multiple simultaneous observations of the same ObservableObject, for example by calling observe(...) multiple times.
  • You can check wether an observer is observing an "observable" via observer.isObserving(observable).

Observable Objects

Any object can be an ObservableObject if it has a Messenger<Message> for sending messages:

class Sky: ObservableObject {
    let messenger = Messenger<Color>()  // Message == Color

Notes on Observable Objects

  • An ObservableObject sends messages via send(_ message: Message). The object's clients, even its observers, are also free to call that function.
  • An ObservableObject 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.
  • Just starting to observe an ObservableObject does not trigger it to send a message. This keeps everything simple, predictable and consistent.

Ways to Create an Observable Object

  1. Create a Messenger<Message>. It's a mediator through which other entities communicate.
  2. Create an object of a custom ObservableObject class that utilizes Messenger<Message>.
  3. Create a Variable<Value> (a.k.a. Var<Value>). It holds a value and sends value updates.
  4. Create a transform object. It wraps and transforms another ObservableObject.

Memory Management

When an Observer or ObservableObject dies, SwiftObserver cleans up all related observations automatically, making memory leaks impossible. So there isn't really any memory management to worry about.

However, observing- and observed objects 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

Free Observers

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 ObservableObject and the basis of every other ObservableObject. 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.

Understand Observable Objects

Having a Messenger is actually what defines ObservableObject:

public protocol ObservableObject: class {
    var messenger: Messenger<Message> { get }
    associatedtype Message: Any

Messenger is itself ObservableObject because it points to itself as the required Messenger:

extension Messenger: ObservableObject {
    public var messenger: Messenger<Message> { self }

Every other ObservableObject class is either a subclass of Messenger or a custom ObservableObject class that provides a Messenger. Custom observables often employ some enum as their message type:

class Model: SuperModel, ObservableObject {
    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 ObservableObject that has a property value: Value.

Observe Variables

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).

Use Variable Values

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

Number Values

If Value is some number type Number that is either an Int, Float or Double:

  1. 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.

  2. 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

String Values

  1. Every 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 "".
  2. You can apply concatenation operator + to all pairs of String, String?, Var<String>, Var<String?>, Var<String>? and Var<String?>?.
  3. Representing its string property, every Var<String> and Var<String?> conforms to TextOutputStream, BidirectionalCollection, Collection, Sequence, CustomDebugStringConvertible and CustomStringConvertible.

Encode and Decode Variables

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

Make Transforms Observable

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 ObservableObject 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 ObservableObject 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 ObservableObjects, you must hold them strongly somewhere. Holding transform chains as dedicated observable objects suits entities like view models that represent transformations of other data.

Use Prebuilt Transforms

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 ObservableObject 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

Unwrap with Default

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

Chain Transforms

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/Future implementations are now obsolete due to Swift's native async/await. Promise was added to SwiftObserver before async/await existed. I intent to replace any use of Promise by async/await in my own apps and then remove Promise from SwiftObserver. I had added it for these reasons: Combine's Future 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.

Receive a Promised Value

Receive It Once

func getID() -> Promise<Int> {   // getID() promises an Int
    Promise { promise in         // convenience initializer
        getIDAsync { id in       // handler retains the promise until it's fulfilled

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 ObservableObject. 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.

Receive It Again

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

Compose Promises

Sequential Composition

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.

Concurrent Composition

promise {                    
}.and {                     // chain another promise concurrently
}.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.

Value Mapping

promise {                    
}.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.

Promise a Failable Result

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 {
}.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.


Message Authors

Every message has an author associated with it. This feature is only noticable in code if we use it.

An observable object can send an author together with a message via object.send(message, from: author). If noone specifies an author as in object.send(message), the observable object itself becomes the author.

Mutate Variables

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

Receive Authors

The observer can receive the author, by adding it as an argument to the message handling closure:

observer.observe(observableObject) { 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.

Share Observable Objects

Identifying message authors can become essential whenever multiple observers observe the same object while their actions can cause it so send messages.

Mutable data is a common type of such shared observable objects. 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>()

Filter by Author

There are three transforms related to message authors. As with other transforms, we can apply them directly in observations or create them as standalone observable objects.

Filter Author

We filter authors just like messages:

let messenger = Messenger<String>()             // sends String

let friendMessages = messenger.filterAuthor {   // sends String if message is from friend


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

Not From

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

Cached Messages

An ObservableCache is an ObservableObject 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.

Four Kinds of Caches

  1. Any Var is an ObservableCache. Its latestMessage is an Update in which old and new both hold the current value.

  2. Calling cache() on an ObservableObject 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.

  3. 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.

  4. Custom observable objects 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.

State-Based Messages

An ObservableObject 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

Weak Observable Objects

When you want to put an ObservableObject into some data structure or as the origin into a transform object but hold it there as a weak reference, transform it via observableObject.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>>](https://raw.github.com/flowtoolz/SwiftObserver/master/)

Of course, weak() wouldn't make sense as an adhoc transform, so it can only create a distinct observable object.


Further Reading

Open Tasks

  • Decompose, rework and extend unit test suite
  • Write API documentation comments
  • Update, rework and extend documentation of features, philosophy and patterns
  • Document adapters for interoperation with Combine and SwiftUI
  • Add syntax sugar for observing/processing on queues, if added API complexity is worth it
  • Leverage property wrappers where they offer any sort of benefit
  • Engage feedback and contribution


Stars: 14
Last commit: 2 weeks ago
jonrohan Something's broken? Yell at me @ptrpavlik. Praise and feedback (and money) is also welcome.


Release Notes

Promise Mappers
1 year ago

New functions on Promise<Value> that return a mapped new Promise<MappedValue>:

  • map(...)
  • unwrap(default)
  • new()

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