Why does Swift not resume an asynchronous function on the same thread it was started? – Ios swift

It helps to approach Swift concurrency with some context: Swift concurrency attempts to provide a higher-level approach to working with concurrent code, and represents a departure from what you may already be used to with threading models, and low-level management of threads, concurrency primitives (locking, semaphores), and so on, so that you don’t have to spend any time thinking about low-level management.

From the Actors section of TSPL, a little further down on the page from your quote:

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…

In Swift Concurrency, a Task represents an isolated bit of work which can be done concurrently, and the concept of isolation here is really important: when code is isolated from the context around it, it can do the work it needs to without having an effect on the outside world, or be affected by it. This means that in the ideal case, a truly isolated task can run on any thread, at any time, and be swapped across threads as needed, without having any measurable effect on the work being done (or the rest of the program).

As @Alexander mentions in comments above, this is a huge benefit, when done right: when work is isolated in this way, any available thread can pick up that work and execute it, giving your process the opportunity to get a lot more work done, instead of waiting for particular threads to be come available.

However: not all code can be so fully isolated that it runs in this manner; at some point, some code needs to interface with the outside world. In some cases, tasks need to interface with one another to get work done together; in others, like UI work, tasks need to coordinate with non-concurrent code to have that effect. Actors are the tool that Swift Concurrency provides to help with this coordination.

Actors help ensure that tasks run in a specific context, serially relative to other tasks which also need to run in that context. To continue the quote from above:

…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.

… 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.

Besides using Actors as isolated havens of state as the rest of that section shows, you can also create Tasks and explicitly annotate their bodies with the Actor within whose context they should run. For example, to use the TemperatureLogger example from TSPL, you could run a task within the context of TemperatureLogger as such:

Task { @TemperatureLogger in
    // This task is now isolated from all other tasks which run against
    // TemperatureLogger. It is guaranteed to run _only_ within the
    // context of TemperatureLogger.
}

The same goes for running against the MainActor:

Task { @MainActor in
    // This code is isolated to the main actor now, and won't run concurrently
    // with any other @MainActor code.
}

This approach works well for tasks which may need to access shared state, and need to be isolated from one another, but: if you test this out, you may notice that multiple tasks running against the same (non-main) actor may still run on multiple threads, or may resume on different threads. What gives?

Tasks and Actors are the high-level tools in Swift concurrency, and they’re the tools that you interface with most as a developer, but let’s get into implementation details:

1. Tasks are actually not the low-level primitive of work in Swift concurrency; Jobs are. A Job represents the code in a Task between await statements, and you never write a Job yourself; the Swift compiler takes Tasks and creates Jobs out of them
2. Jobs are not themselves run by Actors, but by Executors, and again, you never instantiate or use an Executor directly yourself. However, each Actor has an Executor associated with it, that actually runs the jobs submitted to that actor

This is where scheduling actually comes into play. At the moment there are two main executors in Swift concurrency:

1. A cooperative, global executor, which schedules jobs on a cooperative thread pool, and
2. A main executor, which schedules jobs exclusively on the main thread

All non-MainActor actors currently use the global executor for scheduling and executing jobs, and the MainActor uses the main executor for doing the same.

As a user of Swift concurrency, this means that:

1. If you need a piece of code to run exclusively on the main thread, you can schedule it on the MainActor, and it will be guaranteed to run only on that thread
2. If you create a task on any other Actor, it will run on one (or more) of the threads in the global cooperative thread pool
   • And if you run against a specific Actor, the Actor will manage locks and other concurrency primitives for you, so that tasks don’t modify shared state concurrently

With all of this, to get to your questions:

Why doesn’t Swift guarantee resuming on the same thread?

As mentioned in the comments above — because:

1. It shouldn’t be necessary (as tasks should be isolated in a way that the specifics of "which thread are we on?" don’t matter), and
2. Being able to use any one of the available cooperative threads means that you can continue making progress on all of your work much faster

However, the "main thread" is special in many ways, and as such, the @MainActor is bound to using only that thread. When you do need to ensure you’re exclusively on the main thread, you use the main actor.

Are there any rules by which the resuming thread could be determined?

The only rule for non-@MainActor-annotated tasks are: the first available thread in the cooperative thread pool will pick up the work.

Changing this behavior would require writing and using your own Executor, which isn’t quite possible yet (though there are some plans on making this possible).

Are there ways to influence this behaviour, for example make sure it’s resumed on the main thread?

For arbitrary threads, no — you would need to provide your own executor to control that low-level detail.

However, for the main thread, you have several tools:

1. When you create a Task using Task.init(priority:operation:), it defaults to inheriting from the current actor, whatever actor this happens to be. This means that if you’re already running on the main actor, the task will continue using the current actor; but if you aren’t, it will not. To explicitly annotate that you want the task to run on the main actor, you can annotate its operation explicitly:

   Task { @MainActor in
       // ...
   }
   

   This will ensure that regardless of what actor the Task was created on, the contained code will only run on the main actor.

2. From within a Task: regardless of the actor you’re currently on, you can always submit a job directly onto the main actor with MainActor.run(resultType:body:). The body closure is already annotated as @MainActor, and will guarantee execution on the main thread

Note that creating a detached task will never inherit from the current actor, so guaranteed that a detached task will be implicitly scheduled through the global executor instead.

My study of Swift concurrency & subsequent questions above were triggered by finding that a Task started from code running on the main thread (in SwiftUI) was executing it’s block on another thread.

It would help to see specific code here to explain exactly what happened, but two possibilities:

1. You created a non-explicitly @MainActor-annotated Task, and it happened to begin execution on the current thread. However, because you weren’t bound to the main actor, it happened to get suspended and resumed by one of the cooperative threads
2. You created a Task which contained other Tasks within it, which may have run on other actors, or were explicitly detached tasks — and that work continued on another thread

For even more insight into the specifics here, check out Swift concurrency: Behind the scenes from WWDC2021, which @Rob linked in a comment. There’s a lot more to the specifics of what’s going on, and it may be interesting to get an even lower-level view.