File: README.md
The Composable Architecture
The Composable Architecture (TCA, for short) is a library for building applications in a consistent
and understandable way, with composition, testing, and ergonomics in mind. It can be used in
SwiftUI, UIKit, and more, and on any Apple platform (iOS, macOS, iPadOS, visionOS, tvOS, and watchOS).
- What is the Composable Architecture?
- Learn more
- Examples
- Basic usage
- Documentation
- FAQ
- Community
- Installation
- Translations
What is the Composable Architecture?
This library provides a few core tools that can be used to build applications of varying purpose and
complexity. It provides compelling stories that you can follow to solve many problems you encounter
day-to-day when building applications, such as:
State management
How to manage the state of your application using simple value types, and share state across
many screens so that mutations in one screen can be immediately observed in another screen.Composition
How to break down large features into smaller components that can be extracted to their own,
isolated modules and be easily glued back together to form the feature.Side effects
How to let certain parts of the application talk to the outside world in the most testable
and understandable way possible.Testing
How to not only test a feature built in the architecture, but also write integration tests
for features that have been composed of many parts, and write end-to-end tests to understand how
side effects influence your application. This allows you to make strong guarantees that your
business logic is running in the way you expect.Ergonomics
How to accomplish all of the above in a simple API with as few concepts and moving parts as
possible.
Learn More
The Composable Architecture was designed over the course of many episodes on
Point-Free, a video series exploring advanced programming topics in the Swift language,
hosted by Brandon Williams and Stephen Celis.
You can watch all of the episodes here, as well as a dedicated, multipart
tour of the architecture from scratch.
Examples
This repo comes with lots of examples to demonstrate how to solve common and complex problems with
the Composable Architecture. Check out this directory to see them all, including:
- Case Studies
- Getting started
- Effects
- Navigation
- Higher-order reducers
- Reusable components
- Location manager
- Motion manager
- Search
- Speech Recognition
- SyncUps app
- Tic-Tac-Toe
- Todos
- Voice memos
Looking for something more substantial? Check out the source code for isowords, an
iOS word search game built in SwiftUI and the Composable Architecture.
Basic Usage
[!Note]
For a step-by-step interactive tutorial, be sure to check out Meet the Composable
Architecture.
To build a feature using the Composable Architecture you define some types and values that model
your domain:
- State: A type that describes the data your feature needs to perform its logic and render its
UI. - Action: A type that represents all of the actions that can happen in your feature, such as
user actions, notifications, event sources and more. - Reducer: A function that describes how to evolve the current state of the app to the next
state given an action. The reducer is also responsible for returning any effects that should be
run, such as API requests, which can be done by returning anEffectvalue. - Store: The runtime that actually drives your feature. You send all user actions to the store
so that the store can run the reducer and effects, and you can observe state changes in the store
so that you can update UI.
The benefits of doing this are that you will instantly unlock testability of your feature, and you
will be able to break large, complex features into smaller domains that can be glued together.
As a basic example, consider a UI that shows a number along with "+" and "β" buttons that increment
and decrement the number. To make things interesting, suppose there is also a button that when
tapped makes an API request to fetch a random fact about that number and displays it in the view.
To implement this feature we create a new type that will house the domain and behavior of the
feature, and it will be annotated with the @Reducer macro:
import ComposableArchitecture
@Reducer
struct Feature {
}In here we need to define a type for the feature's state, which consists of an integer for the
current count, as well as an optional string that represents the fact being presented:
@Reducer
struct Feature {
@ObservableState
struct State: Equatable {
var count = 0
var numberFact: String?
}
}[!Note]
We've applied the@ObservableStatemacro toStatein order to take advantage of the
observation tools in the library.
We also need to define a type for the feature's actions. There are the obvious actions, such as
tapping the decrement button, increment button, or fact button. But there are also some slightly
non-obvious ones, such as the action that occurs when we receive a response from the fact API
request:
@Reducer
struct Feature {
@ObservableState
struct State: Equatable { /* ... */ }
enum Action {
case decrementButtonTapped
case incrementButtonTapped
case numberFactButtonTapped
case numberFactResponse(String)
}
}And then we implement the body property, which is responsible for composing the actual logic and
behavior for the feature. In it we can use the Reduce reducer to describe how to change the
current state to the next state, and what effects need to be executed. Some actions don't need to
execute effects, and they can return .none to represent that:
@Reducer
struct Feature {
@ObservableState
struct State: Equatable { /* ... */ }
enum Action { /* ... */ }
var body: some Reducer<State, Action> {
Reduce { state, action in
switch action {
case .decrementButtonTapped:
state.count -= 1
return .none
case .incrementButtonTapped:
state.count += 1
return .none
case .numberFactButtonTapped:
return .run { [count = state.count] send in
let (data, _) = try await URLSession.shared.data(
from: URL(string: "http://number-trivia.com/\(count)/trivia")!
)
await send(
.numberFactResponse(String(decoding: data, as: UTF8.self))
)
}
case let .numberFactResponse(fact):
state.numberFact = fact
return .none
}
}
}
}And then finally we define the view that displays the feature. It holds onto a StoreOf<Feature>
so that it can observe all changes to the state and re-render, and we can send all user actions to
the store so that state changes:
struct FeatureView: View {
let store: StoreOf<Feature>
var body: some View {
Form {
Section {
Text("\(store.count)")
Button("Decrement") { store.send(.decrementButtonTapped) }
Button("Increment") { store.send(.incrementButtonTapped) }
}
Section {
Button("Number fact") { store.send(.numberFactButtonTapped) }
}
if let fact = store.numberFact {
Text(fact)
}
}
}
}It is also straightforward to have a UIKit controller driven off of this store. You can observe
state changes in the store in viewDidLoad, and then populate the UI components with data from
the store. The code is a bit longer than the SwiftUI version, so we have collapsed it here:
Click to expand!
class FeatureViewController: UIViewController {
let store: StoreOf<Feature>
init(store: StoreOf<Feature>) {
self.store = store
super.init(nibName: nil, bundle: nil)
}
required init?(coder: NSCoder) {
fatalError("init(coder:) has not been implemented")
}
override func viewDidLoad() {
super.viewDidLoad()
let countLabel = UILabel()
let decrementButton = UIButton()
let incrementButton = UIButton()
let factLabel = UILabel()
// Omitted: Add subviews and set up constraints...
observe { [weak self] in
guard let self
else { return }
countLabel.text = "\(self.store.count)"
factLabel.text = self.store.numberFact
}
}
@objc private func incrementButtonTapped() {
self.store.send(.incrementButtonTapped)
}
@objc private func decrementButtonTapped() {
self.store.send(.decrementButtonTapped)
}
@objc private func factButtonTapped() {
self.store.send(.numberFactButtonTapped)
}
}Once we are ready to display this view, for example in the app's entry point, we can construct a
store. This can be done by specifying the initial state to start the application in, as well as
the reducer that will power the application:
import ComposableArchitecture
@main
struct MyApp: App {
var body: some Scene {
WindowGroup {
FeatureView(
store: Store(initialState: Feature.State()) {
Feature()
}
)
}
}
}And that is enough to get something on the screen to play around with. It's definitely a few more
steps than if you were to do this in a vanilla SwiftUI way, but there are a few benefits. It gives
us a consistent manner to apply state mutations, instead of scattering logic in some observable
objects and in various action closures of UI components. It also gives us a concise way of
expressing side effects. And we can immediately test this logic, including the effects, without
doing much additional work.
Testing
[!Note]
For more in-depth information on testing, see the dedicated testing article.
To test use a TestStore, which can be created with the same information as the Store, but it
does extra work to allow you to assert how your feature evolves as actions are sent:
@Test
func basics() async {
let store = TestStore(initialState: Feature.State()) {
Feature()
}
}Once the test store is created we can use it to make an assertion of an entire user flow of steps.
Each step of the way we need to prove that state changed how we expect. For example, we can
simulate the user flow of tapping on the increment and decrement buttons:
// Test that tapping on the increment/decrement buttons changes the count
await store.send(.incrementButtonTapped) {
$0.count = 1
}
await store.send(.decrementButtonTapped) {
$0.count = 0
}Further, if a step causes an effect to be executed, which feeds data back into the store, we must
assert on that. For example, if we simulate the user tapping on the fact button we expect to
receive a fact response back with the fact, which then causes the numberFact state to be
populated:
await store.send(.numberFactButtonTapped)
await store.receive(\.numberFactResponse) {
$0.numberFact = ???
}However, how do we know what fact is going to be sent back to us?
Currently our reducer is using an effect that reaches out into the real world to hit an API server,
and that means we have no way to control its behavior. We are at the whims of our internet
connectivity and the availability of the API server in order to write this test.
It would be better for this dependency to be passed to the reducer so that we can use a live
dependency when running the application on a device, but use a mocked dependency for tests. We can
do this by adding a property to the Feature reducer:
@Reducer
struct Feature {
let numberFact: (Int) async throws -> String
// ...
}Then we can use it in the reduce implementation:
case .numberFactButtonTapped:
return .run { [count = state.count] send in
let fact = try await self.numberFact(count)
await send(.numberFactResponse(fact))
}And in the entry point of the application we can provide a version of the dependency that actually
interacts with the real world API server:
@main
struct MyApp: App {
var body: some Scene {
WindowGroup {
FeatureView(
store: Store(initialState: Feature.State()) {
Feature(
numberFact: { number in
let (data, _) = try await URLSession.shared.data(
from: URL(string: "http://number-trivia.com/\(number)")!
)
return String(decoding: data, as: UTF8.self)
}
)
}
)
}
}
}But in tests we can use a mock dependency that immediately returns a deterministic, predictable
fact:
@Test
func basics() async {
let store = TestStore(initialState: Feature.State()) {
Feature(numberFact: { "\($0) is a good number Brent" })
}
}With that little bit of upfront work we can finish the test by simulating the user tapping on the
fact button, and then receiving the response from the dependency to present the fact:
await store.send(.numberFactButtonTapped)
await store.receive(\.numberFactResponse) {
$0.numberFact = "0 is a good number Brent"
}We can also improve the ergonomics of using the numberFact dependency in our application. Over
time the application may evolve into many features, and some of those features may also want access
to numberFact, and explicitly passing it through all layers can get annoying. There is a process
you can follow to βregisterβ dependencies with the library, making them instantly available to any
layer in the application.
[!Note]
For more in-depth information on dependency management, see the dedicated
dependencies article.
We can start by wrapping the number fact functionality in a new type:
struct NumberFactClient {
var fetch: (Int) async throws -> String
}And then registering that type with the dependency management system by conforming the client to
the DependencyKey protocol, which requires you to specify the live value to use when running the
application in simulators or devices:
extension NumberFactClient: DependencyKey {
static let liveValue = Self(
fetch: { number in
let (data, _) = try await URLSession.shared
.data(from: URL(string: "http://number-trivia.com/\(number)")!
)
return String(decoding: data, as: UTF8.self)
}
)
}
extension DependencyValues {
var numberFact: NumberFactClient {
get { self[NumberFactClient.self] }
set { self[NumberFactClient.self] = newValue }
}
}With that little bit of upfront work done you can instantly start making use of the dependency in
any feature by using the @Dependency property wrapper:
@Reducer
struct Feature {
- let numberFact: (Int) async throws -> String
+ @Dependency(\.numberFact) var numberFact
β¦
- try await self.numberFact(count)
+ try await self.numberFact.fetch(count)
}This code works exactly as it did before, but you no longer have to explicitly pass the dependency
when constructing the feature's reducer. When running the app in previews, the simulator or on a
device, the live dependency will be provided to the reducer, and in tests the test dependency will
be provided.
This means the entry point to the application no longer needs to construct dependencies:
@main
struct MyApp: App {
var body: some Scene {
WindowGroup {
FeatureView(
store: Store(initialState: Feature.State()) {
Feature()
}
)
}
}
}And the test store can be constructed without specifying any dependencies, but you can still
override any dependency you need to for the purpose of the test:
let store = TestStore(initialState: Feature.State()) {
Feature()
} withDependencies: {
$0.numberFact.fetch = { "\($0) is a good number Brent" }
}
// ...That is the basics of building and testing a feature in the Composable Architecture. There are
a lot more things to be explored, such as composition, modularity, adaptability, and complex
effects. The Examples directory has a bunch of projects to explore to see more
advanced usages.
Documentation
The documentation for releases and main are available here:
There are a number of articles in the documentation that you may find helpful as you become more
comfortable with the library:
FAQ
We have a dedicated article for all of the most frequently asked questions and
comments people have concerning the library.
Community
If you want to discuss the Composable Architecture or have a question about how to use it to solve
a particular problem, there are a number of places you can discuss with fellow
Point-Free enthusiasts:
- For long-form discussions, we recommend the discussions tab of this repo.
- For casual chat, we recommend the Point-Free Community slack.
Installation
You can add ComposableArchitecture to an Xcode project by adding it as a package dependency.
- From the File menu, select Add Package Dependencies...
- Enter "https://github.com/pointfreeco/swift-composable-architecture" into the package
repository URL text field - Depending on how your project is structured:
- If you have a single application target that needs access to the library, then add
ComposableArchitecture directly to your application. - If you want to use this library from multiple Xcode targets, or mix Xcode targets and SPM
targets, you must create a shared framework that depends on ComposableArchitecture and
then depend on that framework in all of your targets. For an example of this, check out the
Tic-Tac-Toe demo application, which splits lots of features into
modules and consumes the static library in this fashion using the tic-tac-toe Swift
package.
- If you have a single application target that needs access to the library, then add
Companion libraries
The Composable Architecture is built with extensibility in mind, and there are a number of
community-supported libraries available to enhance your applications:
- Composable Architecture Extras:
A companion library to the Composable Architecture. - TCAComposer: A macro framework for generating
boiler-plate code in the Composable Architecture. - TCACoordinators: The coordinator pattern
in the Composable Architecture.
If you'd like to contribute a library, please open a
PR with a link
to it!
Translations
The following translations of this README have been contributed by members of the community:
- Arabic
- French
- Hindi
- Indonesian
- Italian
- Japanese
- Korean
- Persian
- Polish
- Portuguese
- Russian
- Simplified Chinese
- Spanish
- Turkish
- Ukrainian
If you'd like to contribute a translation, please open a
PR with a link
to a Gist!
Credits and thanks
The following people gave feedback on the library at its early stages and helped make the library
what it is today:
Paul Colton, Kaan Dedeoglu, Matt Diephouse, Josef DoleΕΎal, Eimantas, Matthew Johnson, George
Kaimakas, Nikita Leonov, Christopher Liscio, Jeffrey Macko, Alejandro Martinez, Shai Mishali, Willis
Plummer, Simon-Pierre Roy, Justin Price, Sven A. Schmidt, Kyle Sherman, Petr Ε Γma, Jasdev Singh,
Maxim Smirnov, Ryan Stone, Daniel Hollis Tavares, and all of the Point-Free
subscribers π.
Special thanks to Chris Liscio who helped us work through many strange
SwiftUI quirks and helped refine the final API.
And thanks to Shai Mishali and the
CombineCommunity project, from which we took
their implementation of Publishers.Create, which we use in Effect to help bridge delegate and
callback-based APIs, making it much easier to interface with 3rd party frameworks.
Other libraries
The Composable Architecture was built on a foundation of ideas started by other libraries, in
particular Elm and Redux.
There are also many architecture libraries in the Swift and iOS community. Each one of these has
their own set of priorities and trade-offs that differ from the Composable Architecture.
And more
License
This library is released under the MIT license. See LICENSE for details.
File: Examples/CaseStudies/README.md
Composable Architecture Case Studies
This project includes a number of digestible examples of how to solve common problems using the Composable Architecture.
File: Examples/Search/README.md
Search
This application demonstrates how to build a moderately complex search feature in the Composable Architecture:
- Typing into the search field executes an API request to search for locations.
- Tapping a location runs another API request to fetch the weather for that location, and when a response is received the data is displayed inline in that row.
In addition to those basic features, the following extra things are implemented:
- Search API requests are debounced so that one is run only after the user stops typing for 300ms.
- If you tap a location while a weather API request is already in-flight it will cancel that request and start a new one.
- Dependencies and side effects are fully controlled. The reducer that runs this application needs a weather API client to run effects.
- A full test suite is implemented. Not only is core functionality tested, but also failure flows and subtle edge cases (e.g. clearing the search query cancels any in-flight search requests).
File: Examples/SpeechRecognition/README.md
Speech Recognition
This application demonstrates how to work with a complex dependency in the Composable Architecture. It uses the SFSpeechRecognizer API from the Speech framework to listen to audio on the device and live-transcribe it to the UI.
The SFSpeechRecognizer class is a complex dependency, and if we used it freely in our application we wouldn't be able to test any of that code. So, instead, we wrap the API in a SpeechClient type that exposes asynchronous endpoints for accessing the underlying SFSpeechRecognizer class. Then we can use it in the reducer in an understandable way, and we can write tests for the reducer.
File: Examples/SyncUps/README.md
SyncUps
This project demonstrates how to build a complex, real world application that deals with many forms
of navigation (e.g., sheets, drill-downs, alerts), many side effects (timers, speech recognizer,
data persistence), and do so in a way that is testable and modular.
The inspiration for this application comes from Apple's Scrumdinger tutorial:
This module guides you through the development of Scrumdinger, an iOS app that helps users manage
their daily scrums. To help keep scrums short and focused, Scrumdinger uses visual and audio cues
to indicate when and how long each attendee should speak. The app also displays a progress screen
that shows the time remaining in the meeting and creates a transcript that users can refer to
later.
The Scrumdinger app is one of Apple's most interesting code samples as it deals with many real
world problems that one faces in application development. It shows off many types of navigation,
it deals with complex effects such as timers and speech recognition, and it persists application
data to disk.
However, it is not necessarily built in the most ideal way. It uses mostly fire-and-forget style
navigation, which means you can't easily deep link into any screen of the app, which is handy for
push notifications and opening URLs. It also uses uncontrolled dependencies, including file system
access, timers and a speech recognizer, which makes it nearly impossible to write automated tests
and even hinders the ability to preview the app in Xcode previews.
But, the simplicity of Apple's Scrumdinger codebase is not a defect. In fact, it's a feature!
Apple's sample code is viewed by hundreds of thousands of developers across the world, and so its
goal is to be as approachable as possible in order to teach the basics of SwiftUI. But, that doesn't mean there isn't room for improvement.
Composable SyncUps
Our SyncUps application is a rebuild of Apple's Scrumdinger application, but with a focus on
modern, best practices for SwiftUI development. We faithfully recreate the Scrumdinger, but with
some key additions:
- Identifiers are made type safe using our Tagged library. This prevents us from
writing nonsensical code, such as comparing aSyncUp.IDto aAttendee.ID. - Instead of using bare arrays in feature logic we use an "identified" array from our
IdentifiedCollections library. This allows you to read and modify
elements of the collection via their ID rather than positional index, which can be error-prone
and lead to bugs or crashes. - All navigation is driven off of state, including sheets, drill-downs and alerts. This makes
it possible to deep link into any screen of the app by just constructing a piece of state and
handing it off to SwiftUI. - Further, each view represents its navigation destinations as a single enum, which gives us
compile time proof that two destinations cannot be active at the same time. This cannot be
accomplished with default SwiftUI tools, but can be done easily with the tools that the
Composable Architecture provides. - All side effects are controlled. This includes access to the file system for persistence, access
to time-based asynchrony for timers, access to speech recognition APIs, and even the creation
of dates and UUIDs. This allows us to run our application in specific execution contexts, which
is very useful in tests and Xcode previews. We accomplish this using our
Dependencies library. - The project includes a full test suite. Since all of navigation is driven off of state, and
because we controlled all dependencies, we can write very comprehensive and nuanced tests. For
example, we can write a unit test that proves that when a sync-up meeting's timer runs out the
screen pops off the stack and a new transcript is added to the sync-up. Such a test would be
very difficult, if not impossible, without controlling dependencies.
File: Examples/TicTacToe/README.md
Tic-Tac-Toe
This example demonstrates how to build a full, moderately complex application in the Composable Architecture. It is based off the Tic-Tac-Toe examples used to demonstrate RIBs from Uber (see here) and Workflows from Square (see here).
It shows many real-world use cases and best practices that we encounter when building applications:
Login flow and two-factor screens.
Multistep navigation flows, from login to new game screen to game screen.
Comprehensive test suite for every feature, including integration tests of many features working in unison, and end-to-end testing of side effects.
Fully controlled side effects. Every feature is provided with all the dependencies it needs to do its work, which makes testing very easy.
Highly modularized: every feature is isolated into its own module with minimal dependencies between them, allowing us to compile and run features in isolation without building the entire application.
SwiftUI and UIKit applications are implemented, and both share the same core logic. This shows it's possible to create UIKit applications with the Composable Architecture just as easily as it is to create SwiftUI applications.
The core logic of the application is put into modules named like
*Core, and they are kept separate from modules containing UI, which is what allows us to share code across multiple platforms (SwiftUI and UIKit), but could also allow us to share code across iOS, macOS, watchOS and tvOS apps.Navigation is completely driven off of state. To see this, try opening the SwiftUI game, do a few things in the game, then close the modal and open the UIKit version to see that state is fully restored to where you left off.
File: Examples/Todos/README.md
Todos
This simple todo application built with the Composable Architecture includes a few bells and whistles:
- Filtering and rearranging todo items.
- Automatically sort completed todos to the bottom of the list.
- Debouncing the sort action to allow multiple todo items to be toggled before being sorted.
- A comprehensive test suite.
File: Examples/VoiceMemos/README.md
Voice Memos
This application demonstrates how to work with multiple dependencies and manage a complex state machine driven off of timers in the Composable Architecture. Some functionality includes:
- Requesting the userβs permission to record audio.
- Prompting the user if insufficient permission is provided.
- Audio recording and playback.
- Handling errors that may occur during recording or playback.
- Stubbing dependencies to work with SwiftUI previews.
File: Examples/README.md
Examples
This directory holds many case studies and applications to demonstrate solving various problems with the Composable Architecture. Open the ComposableArchitecture.xcworkspace at the root of the repo to see all example projects in one single workspace, or you can open each example application individually.
Case Studies
Demonstrates how to solve some common application problems in an isolated environment, in both SwiftUI and UIKit. Things like bindings, navigation, effects, and reusable components.Search
Demonstrates how to build a search feature, with debouncing of typing events, and comes with a full test suite to perform end-to-end testing from user actions to running side effects.Speech Recognition
This application uses Apple's Speech framework to demonstrate how to wrap complex dependencies in theEffecttype of the Composable Architecture. Doing a little bit of upfront work allows you to interact with the dependencies in a controlled, understandable way, and you can write tests on how the dependency interacts with your application logic.SyncUps
This application is a faithful reconstruction of one of Apple's more interesting sample projects, called Scrumdinger. It deals with many forms of navigation (alerts, sheets, drill-downs) and many forms of side effects (data persistence, timers and speech recognizers).Tic-Tac-Toe
Builds a moderately complex application in both SwiftUI and UIKit that is fully controlled by the Composable Architecture. The core application logic is put into its own modules, with no UI, and then both of the SwiftUI and UIKit applications are run off of that single source of logic. This demonstrates how one can hyper-modularize an application, which for a big enough application can greatly help compile times and developer productivity. This demo was inspired by the equivalent demos in RIBs (see here) and Workflow (see here).Todos
A simple todo application with a few bells and whistles, and a comprehensive test suite.Voice Memos
A more complex demo that demonstrates how to work with many complex dependencies at once, and how to manage a complex state machine driven off of timers.