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Perform asynchronous operations.

Swift has built-in support for writing asynchronous and parallel code in a structured way. Asynchronous code can be suspended and resumed later, although only one piece of the program executes at a time. Suspending and resuming code in your program lets it continue to make progress on short-term operations like updating its UI while continuing to work on long-running operations like fetching data over the network or parsing files. Parallel code means multiple pieces of code run simultaneously—for example, a computer with a four-core processor can run four pieces of code at the same time, with each core carrying out one of the tasks. A program that uses parallel and asynchronous code carries out multiple operations at a time; it suspends operations that are waiting for an external system, and makes it easier to write this code in a memory-safe way.

The additional scheduling flexibility from parallel or asynchronous code also comes with a cost of increased complexity. Swift lets you express your intent in a way that enables some compile-time checking—for example, you can use actors to safely access mutable state. However, adding concurrency to slow or buggy code isn't a guarantee that it will become fast or correct. In fact, adding concurrency might even make your code harder to debug. However, using Swift's language-level support for concurrency in code that needs to be concurrent means Swift can help you catch problems at compile time.

The rest of this chapter uses the term concurrency to refer to this common combination of asynchronous and parallel code.


If you've written concurrent code before, you might be used to working with threads. The concurrency model in Swift is built on top of threads, but you don't interact with them directly. An asynchronous function in Swift can give up the thread that it's running on, which lets another asynchronous function run on that thread while the first function is blocked. When an asynchronous function resumes, Swift doesn’t make any guarantee about which thread that function will run on.

Although it's possible to write concurrent code without using Swift's language support, that code tends to be harder to read. For example, the following code downloads a list of photo names, downloads the first photo in that list, and shows that photo to the user:

listPhotos(inGallery: "Summer Vacation") { photoNames in
    let sortedNames = photoNames.sorted()
    let name = sortedNames[0]
    downloadPhoto(named: name) { photo in

Even in this simple case, because the code has to be written as a series of completion handlers, you end up writing nested closures. In this style, more complex code with deep nesting can quickly become unwieldy.

Defining and Calling Asynchronous Functions

An asynchronous function or asynchronous method is a special kind of function or method that can be suspended while it's partway through execution. This is in contrast to ordinary, synchronous functions and methods, which either run to completion, throw an error, or never return. An asynchronous function or method still does one of those three things, but it can also pause in the middle when it's waiting for something. Inside the body of an asynchronous function or method, you mark each of these places where execution can be suspended.

To indicate that a function or method is asynchronous, you write the async keyword in its declaration after its parameters, similar to how you use throws to mark a throwing function. If the function or method returns a value, you write async before the return arrow (->). For example, here's how you might fetch the names of photos in a gallery:

func listPhotos(inGallery name: String) async -> [String] {
    let result = // ... some asynchronous networking code ...
    return result

For a function or method that's both asynchronous and throwing, you write async before throws.

When calling an asynchronous method, execution suspends until that method returns. You write await in front of the call to mark the possible suspension point. This is like writing try when calling a throwing function, to mark the possible change to the program's flow if there's an error. Inside an asynchronous method, the flow of execution is suspended only when you call another asynchronous method—suspension is never implicit or preemptive—which means every possible suspension point is marked with await.

For example, the code below fetches the names of all the pictures in a gallery and then shows the first picture:

let photoNames = await listPhotos(inGallery: "Summer Vacation")
let sortedNames = photoNames.sorted()
let name = sortedNames[0]
let photo = await downloadPhoto(named: name)

Because the listPhotos(inGallery:) and downloadPhoto(named:) functions both need to make network requests, they could take a relatively long time to complete. Making them both asynchronous by writing async before the return arrow lets the rest of the app's code keep running while this code waits for the picture to be ready.

To understand the concurrent nature of the example above, here's one possible order of execution:

  1. The code starts running from the first line and runs up to the first await. It calls the listPhotos(inGallery:) function and suspends execution while it waits for that function to return.

  2. While this code's execution is suspended, some other concurrent code in the same program runs. For example, maybe a long-running background task continues updating a list of new photo galleries. That code also runs until the next suspension point, marked by await, or until it completes.

  3. After listPhotos(inGallery:) returns, this code continues execution starting at that point. It assigns the value that was returned to photoNames.

  4. The lines that define sortedNames and name are regular, synchronous code. Because nothing is marked await on these lines, there aren't any possible suspension points.

  5. The next await marks the call to the downloadPhoto(named:) function. This code pauses execution again until that function returns, giving other concurrent code an opportunity to run.

  6. After downloadPhoto(named:) returns, its return value is assigned to photo and then passed as an argument when calling show(_:).

The possible suspension points in your code marked with await indicate that the current piece of code might pause execution while waiting for the asynchronous function or method to return. This is also called yielding the thread because, behind the scenes, Swift suspends the execution of your code on the current thread and runs some other code on that thread instead. Because code with await needs to be able to suspend execution, only certain places in your program can call asynchronous functions or methods:

  • Code in the body of an asynchronous function, method, or property.
  • Code in the static main() method of a structure, class, or enumeration that's marked with @main.
  • Code in a detached child task, as shown in Unstructured Concurrency below.

Code in between possible suspension points runs sequentially, without the possibility of interruption from other concurrent code. For example, the code below moves a picture from one gallery to another.

let firstPhoto = await listPhotos(inGallery: "Summer Vacation")[0]
add(firstPhoto, toGallery: "Road Trip")
// At this point, firstPhoto is temporarily in both galleries.
remove(firstPhoto, fromGallery: "Summer Vacation")

There’s no way for other code to run in between the call to add(_:toGallery:) and remove(_:fromGallery:). During that time, the first photo appears in both galleries, temporarily breaking one of the app’s invariants. To make it even clearer that this chunk of code must not have await added to it in the future, you can refactor that code into a synchronous function:

func move(_ photoName: String, from source: String, to destination: String) {
    add(photoName, toGallery: destination)
    remove(photoName, fromGallery: source)
// ...
let firstPhoto = await listPhotos(inGallery: "Summer Vacation")[0]
move(firstPhoto, from: "Summer Vacation", to: "Road Trip")

In the example above, because the move(_:from:to:) function is synchronous, you guarantee that it can never contain possible suspension points. In the future, if you try to add concurrent code to this function, introducing a possible suspension point, you’ll get compile-time error instead of introducing a bug.


The Task.sleep(until:tolerance:clock:) (opens in a new tab) method is useful when writing simple code to learn how concurrency works. This method does nothing, but waits at least the given number of nanoseconds before it returns. Here’s a version of the listPhotos(inGallery:) function that uses sleep(until:tolerance:clock:) to simulate waiting for a network operation:

func listPhotos(inGallery name: String) async throws -> [String] {
    try await Task.sleep(until: .now + .seconds(2), clock: .continuous)
    return ["IMG001", "IMG99", "IMG0404"]

Asynchronous Sequences

The listPhotos(inGallery:) function in the previous section asynchronously returns the whole array at once, after all of the array's elements are ready. Another approach is to wait for one element of the collection at a time using an asynchronous sequence. Here's what iterating over an asynchronous sequence looks like:

import Foundation
let handle = FileHandle.standardInput
for try await line in handle.bytes.lines {

Instead of using an ordinary for-in loop, the example above writes for with await after it. Like when you call an asynchronous function or method, writing await indicates a possible suspension point. A for-await-in loop potentially suspends execution at the beginning of each iteration, when it's waiting for the next element to be available.

In the same way that you can use your own types in a for-in loop by adding conformance to the Sequence (opens in a new tab) protocol, you can use your own types in a for-await-in loop by adding conformance to the AsyncSequence (opens in a new tab) protocol.

Calling Asynchronous Functions in Parallel

Calling an asynchronous function with await runs only one piece of code at a time. While the asynchronous code is running, the caller waits for that code to finish before moving on to run the next line of code. For example, to fetch the first three photos from a gallery, you could await three calls to the downloadPhoto(named:) function as follows:

let firstPhoto = await downloadPhoto(named: photoNames[0])
let secondPhoto = await downloadPhoto(named: photoNames[1])
let thirdPhoto = await downloadPhoto(named: photoNames[2])
let photos = [firstPhoto, secondPhoto, thirdPhoto]

This approach has an important drawback: Although the download is asynchronous and lets other work happen while it progresses, only one call to downloadPhoto(named:) runs at a time. Each photo downloads completely before the next one starts downloading. However, there's no need for these operations to wait—each photo can download independently, or even at the same time.

To call an asynchronous function and let it run in parallel with code around it, write async in front of let when you define a constant, and then write await each time you use the constant.

async let firstPhoto = downloadPhoto(named: photoNames[0])
async let secondPhoto = downloadPhoto(named: photoNames[1])
async let thirdPhoto = downloadPhoto(named: photoNames[2])
let photos = await [firstPhoto, secondPhoto, thirdPhoto]

In this example, all three calls to downloadPhoto(named:) start without waiting for the previous one to complete. If there are enough system resources available, they can run at the same time. None of these function calls are marked with await because the code doesn't suspend to wait for the function's result. Instead, execution continues until the line where photos is defined—at that point, the program needs the results from these asynchronous calls, so you write await to pause execution until all three photos finish downloading.

Here's how you can think about the differences between these two approaches:

  • Call asynchronous functions with await when the code on the following lines depends on that function's result. This creates work that is carried out sequentially.
  • Call asynchronous functions with async-let when you don't need the result until later in your code. This creates work that can be carried out in parallel.
  • Both await and async-let allow other code to run while they're suspended.
  • In both cases, you mark the possible suspension point with await to indicate that execution will pause, if needed, until an asynchronous function has returned.

You can also mix both of these approaches in the same code.

Tasks and Task Groups

A task is a unit of work that can be run asynchronously as part of your program. All asynchronous code runs as part of some task. The async-let syntax described in the previous section creates a child task for you. You can also create a task group and add child tasks to that group, which gives you more control over priority and cancellation, and lets you create a dynamic number of tasks.

Tasks are arranged in a hierarchy. Each task in a task group has the same parent task, and each task can have child tasks. Because of the explicit relationship between tasks and task groups, this approach is called structured concurrency. Although you take on some of the responsibility for correctness, the explicit parent-child relationships between tasks lets Swift handle some behaviors like propagating cancellation for you, and lets Swift detect some errors at compile time.

await withTaskGroup(of: Data.self) { taskGroup in
    let photoNames = await listPhotos(inGallery: "Summer Vacation")
    for name in photoNames {
        taskGroup.addTask { await downloadPhoto(named: name) }

For more information about task groups, see TaskGroup (opens in a new tab).

Unstructured Concurrency

In addition to the structured approaches to concurrency described in the previous sections, Swift also supports unstructured concurrency. Unlike tasks that are part of a task group, an unstructured task doesn't have a parent task. You have complete flexibility to manage unstructured tasks in whatever way your program needs, but you're also completely responsible for their correctness. To create an unstructured task that runs on the current actor, call the Task.init(priority:operation:) (opens in a new tab) initializer. To create an unstructured task that's not part of the current actor, known more specifically as a detached task, call the Task.detached(priority:operation:) (opens in a new tab) class method. Both of these operations return a task handle that lets you interact with the task—for example, to wait for its result or to cancel it.

let newPhoto = // ... some photo data ...
let handle = Task {
    return await add(newPhoto, toGalleryNamed: "Spring Adventures")
let result = await handle.value

For more information about managing detached tasks, see Task (opens in a new tab).

Task Cancellation

Swift concurrency uses a cooperative cancellation model. Each task checks whether it has been canceled at the appropriate points in its execution, and responds to cancellation in whatever way is appropriate. Depending on the work you're doing, that usually means one of the following:

  • Throwing an error like CancellationError
  • Returning nil or an empty collection
  • Returning the partially completed work

To check for cancellation, either call Task.checkCancellation() (opens in a new tab), which throws CancellationError if the task has been canceled, or check the value of Task.isCancelled (opens in a new tab) and handle the cancellation in your own code. For example, a task that's downloading photos from a gallery might need to delete partial downloads and close network connections.

To propagate cancellation manually, call Task.cancel() (opens in a new tab).


You can use tasks to break up your program into isolated, concurrent pieces. Tasks are isolated from each other, which is what makes it safe for them to run at the same time, but sometimes you need to share some information between tasks. Actors let you safely share information between concurrent code.

Like classes, actors are reference types, so the comparison of value types and reference types in Classes Are Reference Types applies to actors as well as classes. Unlike classes, actors allow only one task to access their mutable state at a time, which makes it safe for code in multiple tasks to interact with the same instance of an actor. For example, here's an actor that records temperatures:

actor TemperatureLogger {
    let label: String
    var measurements: [Int]
    private(set) var max: Int
    init(label: String, measurement: Int) {
        self.label = label
        self.measurements = [measurement]
        self.max = measurement

You introduce an actor with the actor keyword, followed by its definition in a pair of braces. The TemperatureLogger actor has properties that other code outside the actor can access, and restricts the max property so only code inside the actor can update the maximum value.

You create an instance of an actor using the same initializer syntax as structures and classes. When you access a property or method of an actor, you use await to mark the potential suspension point—for example:

Task {
    let logger = TemperatureLogger(label: "Outdoors", measurement: 25)
    print(await logger.max)
// Prints "25"

In this example, accessing logger.max is a possible suspension point. Because the actor allows only one task at a time to access its mutable state, if code from another task is already interacting with the logger, this code suspends while it waits to access the property.

In contrast, code that's part of the actor doesn't write await when accessing the actor's properties. For example, here's a method that updates a TemperatureLogger with a new temperature:

extension TemperatureLogger {
    func update(with measurement: Int) {
        if measurement > max {
            max = measurement

The update(with:) method is already running on the actor, so it doesn't mark its access to properties like max with await. This method also shows one of the reasons why actors allow only one task at a time to interact with their mutable state: Some updates to an actor's state temporarily break invariants. The TemperatureLogger actor keeps track of a list of temperatures and a maximum temperature, and it updates the maximum temperature when you record a new measurement. In the middle of an update, after appending the new measurement but before updating max, the temperature logger is in a temporary inconsistent state. Preventing multiple tasks from interacting with the same instance simultaneously prevents problems like the following sequence of events:

  1. Your code calls the update(with:) method. It updates the measurements array first.

  2. Before your code can update max, code elsewhere reads the maximum value and the array of temperatures.

  3. Your code finishes its update by changing max.

In this case, the code running elsewhere would read incorrect information because its access to the actor was interleaved in the middle of the call to update(with:) while the data was temporarily invalid. You can prevent this problem when using Swift actors because they only allow one operation on their state at a time, and because that code can be interrupted only in places where await marks a suspension point. Because update(with:) doesn't contain any suspension points, no other code can access the data in the middle of an update.

If you try to access those properties from outside the actor, like you would with an instance of a class, you'll get a compile-time error; for example:

sprint(logger.max) // Error

Accessing logger.max without writing await fails because the properties of an actor are part of that actor's isolated local state. Swift guarantees that only code inside an actor can access the actor's local state. This guarantee is known as actor isolation.

Sendable Types

Tasks and actors let you divide a program into pieces that can safely run concurrently. Inside of a task or an instance of an actor, the part of a program that contains mutable state, like variables and properties, is called a concurrency domain. Some kinds of data can’t be shared between concurrency domains, because that data contains mutable state, but it doesn’t protect against overlapping access.

A type that can be shared from one concurrency domain to another is known as a sendable type. For example, it can be passed as an argument when calling an actor method or be returned as the result of a task. The examples earlier in this chapter didn’t discuss sendability because those examples use simple value types that are always safe to share for the data being passed between concurrency domains. In contrast, some types aren’t safe to pass across concurrency domains. For example, a class that contains mutable properties and doesn’t serialize access to those properties can produce unpredictable and incorrect results when you pass instances of that class between different tasks.

You mark a type as being sendable by declaring conformance to the Sendable protocol. That protocol doesn’t have any code requirements, but it does have semantic requirements that Swift enforces. In general, there are three ways for a type to be sendable:

  • The type is a value type, and its mutable state is made up of other sendable data — for example, a structure with stored properties that are sendable or an enumeration with associated values that are sendable.

  • The type doesn’t have any mutable state, and its immutable state is made up of other sendable data — for example, a structure or class that has only read-only properties.

  • The type has code that ensures the safety of its mutable state, like a class that’s marked @MainActor or a class that serializes access to its properties on a particular thread or queue.

For a detailed list of the semantic requirements, see the Sendable (opens in a new tab) protocol reference.

Some types are always sendable, like structures that have only sendable properties and enumerations that have only sendable associated values. For example:

struct TemperatureReading: Sendable {
    var measurement: Int
extension TemperatureLogger {
    func addReading(from reading: TemperatureReading) {
let logger = TemperatureLogger(label: "Tea kettle", measurement: 85)
let reading = TemperatureReading(measurement: 45)
await logger.addReading(from: reading)

Because TemperatureReading is a structure that has only sendable properties, and the structure isn’t marked public or @usableFromInline, it’s implicitly sendable. Here’s a version of the structure where conformance to the Sendable protocol is implied:

struct TemperatureReading {
    var measurement: Int