# Tasks

`Core.Task` — Type

    Task(func)

Create a `Task` (i.e. coroutine) to execute the given function `func` (which must be callable with no arguments). The task exits when this function returns. The task will run in the "world age" from the parent at construction when `schedule`d.

Warning

By default tasks will have the sticky bit set to true `t.sticky`. This models the historic default for `@async`. Sticky tasks can only be run on the worker thread they are first scheduled on. To obtain the behavior of `Threads.@spawn` set the sticky bit manually to `false`.

Examples

    julia> a() = sum(i for i in 1:1000);

    julia> b = Task(a);

In this example, `b` is a runnable `Task` that hasn't started yet.

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`Base.@task` — Macro

    @task

Wrap an expression in a `Task` without executing it, and return the `Task`. This only creates a task, and does not run it.

Examples

    julia> a1() = sum(i for i in 1:1000);

    julia> b = @task a1();

    julia> istaskstarted(b)
    false

    julia> schedule(b);

    julia> yield();

    julia> istaskdone(b)
    true

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`Base.@async` — Macro

    @async

Wrap an expression in a `Task` and add it to the local machine's scheduler queue.

Values can be interpolated into `@async` via `$`, which copies the value directly into the constructed underlying closure. This allows you to insert the value of a variable, isolating the asynchronous code from changes to the variable's value in the current task.

Warning

It is strongly encouraged to favor `Threads.@spawn` over `@async` always even when no parallelism is required especially in publicly distributed libraries. This is because a use of `@async` disables the migration of the parent task across worker threads in the current implementation of Julia. Thus, seemingly innocent use of `@async` in a library function can have a large impact on the performance of very different parts of user applications.

Julia 1.4

Interpolating values via `$` is available as of Julia 1.4.

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`Base.asyncmap` — Function

    asyncmap(f, c...; ntasks=0, batch_size=nothing)

Uses multiple concurrent tasks to map `f` over a collection (or multiple equal length collections). For multiple collection arguments, `f` is applied elementwise.

`ntasks` specifies the number of tasks to run concurrently. Depending on the length of the collections, if `ntasks` is unspecified, up to 100 tasks will be used for concurrent mapping.

`ntasks` can also be specified as a zero-arg function. In this case, the number of tasks to run in parallel is checked before processing every element and a new task started if the value of `ntasks_func` is greater than the current number of tasks.

If `batch_size` is specified, the collection is processed in batch mode. `f` must then be a function that must accept a `Vector` of argument tuples and must return a vector of results. The input vector will have a length of `batch_size` or less.

The following examples highlight execution in different tasks by returning the `objectid` of the tasks in which the mapping function is executed.

First, with `ntasks` undefined, each element is processed in a different task.

    julia> tskoid() = objectid(current_task());

    julia> asyncmap(x->tskoid(), 1:5)
    5-element Array{UInt64,1}:
     0x6e15e66c75c75853
     0x440f8819a1baa682
     0x9fb3eeadd0c83985
     0xebd3e35fe90d4050
     0x29efc93edce2b961

    julia> length(unique(asyncmap(x->tskoid(), 1:5)))
    5

With `ntasks=2` all elements are processed in 2 tasks.

    julia> asyncmap(x->tskoid(), 1:5; ntasks=2)
    5-element Array{UInt64,1}:
     0x027ab1680df7ae94
     0xa23d2f80cd7cf157
     0x027ab1680df7ae94
     0xa23d2f80cd7cf157
     0x027ab1680df7ae94

    julia> length(unique(asyncmap(x->tskoid(), 1:5; ntasks=2)))
    2

With `batch_size` defined, the mapping function needs to be changed to accept an array of argument tuples and return an array of results. `map` is used in the modified mapping function to achieve this.

    julia> batch_func(input) = map(x->string("args_tuple: ", x, ", element_val: ", x[1], ", task: ", tskoid()), input)
    batch_func (generic function with 1 method)

    julia> asyncmap(batch_func, 1:5; ntasks=2, batch_size=2)
    5-element Array{String,1}:
     "args_tuple: (1,), element_val: 1, task: 9118321258196414413"
     "args_tuple: (2,), element_val: 2, task: 4904288162898683522"
     "args_tuple: (3,), element_val: 3, task: 9118321258196414413"
     "args_tuple: (4,), element_val: 4, task: 4904288162898683522"
     "args_tuple: (5,), element_val: 5, task: 9118321258196414413"

Note

Currently, all tasks in Julia are executed in a single OS thread co-operatively. Consequently, `asyncmap` is beneficial only when the mapping function involves any I/O - disk, network, remote worker invocation, etc.

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`Base.asyncmap!` — Function

    asyncmap!(f, results, c...; ntasks=0, batch_size=nothing)

Like `asyncmap`, but stores output in `results` rather than returning a collection.

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`Base.current_task` — Function

    current_task()

Get the currently running `Task`.

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`Base.istaskdone` — Function

    istaskdone(t::Task) -> Bool

Determine whether a task has exited.

Examples

    julia> a2() = sum(i for i in 1:1000);

    julia> b = Task(a2);

    julia> istaskdone(b)
    false

    julia> schedule(b);

    julia> yield();

    julia> istaskdone(b)
    true

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`Base.istaskstarted` — Function

    istaskstarted(t::Task) -> Bool

Determine whether a task has started executing.

Examples

    julia> a3() = sum(i for i in 1:1000);

    julia> b = Task(a3);

    julia> istaskstarted(b)
    false

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`Base.istaskfailed` — Function

    istaskfailed(t::Task) -> Bool

Determine whether a task has exited because an exception was thrown.

Examples

    julia> a4() = error("task failed");

    julia> b = Task(a4);

    julia> istaskfailed(b)
    false

    julia> schedule(b);

    julia> yield();

    julia> istaskfailed(b)
    true

Julia 1.3

This function requires at least Julia 1.3.

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`Base.task_local_storage` — Method

    task_local_storage(key)

Look up the value of a key in the current task's task-local storage.

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`Base.task_local_storage` — Method

    task_local_storage(key, value)

Assign a value to a key in the current task's task-local storage.

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`Base.task_local_storage` — Method

    task_local_storage(body, key, value)

Call the function `body` with a modified task-local storage, in which `value` is assigned to `key`; the previous value of `key`, or lack thereof, is restored afterwards. Useful for emulating dynamic scoping.

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## Scheduling

`Base.yield` — Function

    yield()

Switch to the scheduler to allow another scheduled task to run. A task that calls this function is still runnable, and will be restarted immediately if there are no other runnable tasks.

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    yield(t::Task, arg = nothing)

A fast, unfair-scheduling version of `schedule(t, arg); yield()` which immediately yields to `t` before calling the scheduler.

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`Base.yieldto` — Function

    yieldto(t::Task, arg = nothing)

Switch to the given task. The first time a task is switched to, the task's function is called with no arguments. On subsequent switches, `arg` is returned from the task's last call to `yieldto`. This is a low-level call that only switches tasks, not considering states or scheduling in any way. Its use is discouraged.

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`Base.sleep` — Function

    sleep(seconds)

Block the current task for a specified number of seconds. The minimum sleep time is 1 millisecond or input of `0.001`.

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`Base.schedule` — Function

    schedule(t::Task, [val]; error=false)

Add a `Task` to the scheduler's queue. This causes the task to run constantly when the system is otherwise idle, unless the task performs a blocking operation such as `wait`.

If a second argument `val` is provided, it will be passed to the task (via the return value of `yieldto`) when it runs again. If `error` is `true`, the value is raised as an exception in the woken task.

Warning

It is incorrect to use `schedule` on an arbitrary `Task` that has already been started. See the API reference for more information.

Examples

    julia> a5() = sum(i for i in 1:1000);

    julia> b = Task(a5);

    julia> istaskstarted(b)
    false

    julia> schedule(b);

    julia> yield();

    julia> istaskstarted(b)
    true

    julia> istaskdone(b)
    true

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## Synchronization

`Base.errormonitor` — Function

    errormonitor(t::Task)

Print an error log to `stderr` if task `t` fails.

Examples

    julia> Base._wait(errormonitor(Threads.@spawn error("task failed")))
    Unhandled Task ERROR: task failed
    Stacktrace:
    [...]

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`Base.@sync` — Macro

    @sync

Wait until all lexically-enclosed uses of `@async`, `@spawn`, `@spawnat` and `@distributed` are complete. All exceptions thrown by enclosed async operations are collected and thrown as a `CompositeException`.

Examples

    julia> Threads.nthreads()
    4

    julia> @sync begin
               Threads.@spawn println("Thread-id $(Threads.threadid()), task 1")
               Threads.@spawn println("Thread-id $(Threads.threadid()), task 2")
           end;
    Thread-id 3, task 1
    Thread-id 1, task 2

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`Base.wait` — Function

    wait(r::Future)

Wait for a value to become available for the specified `Future`.

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    wait(r::RemoteChannel, args...)

Wait for a value to become available on the specified `RemoteChannel`.

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Special note for `Threads.Condition`:

The caller must be holding the `lock` that owns a `Threads.Condition` before calling this method. The calling task will be blocked until some other task wakes it, usually by calling `notify` on the same `Threads.Condition` object. The lock will be atomically released when blocking (even if it was locked recursively), and will be reacquired before returning.

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    wait([x])

Block the current task until some event occurs, depending on the type of the argument:

- `Channel`: Wait for a value to be appended to the channel.
- `Condition`: Wait for `notify` on a condition and return the `val` parameter passed to `notify`. Waiting on a condition additionally allows passing `first=true` which results in the waiter being put first in line to wake up on `notify` instead of the usual first-in-first-out behavior.
- `Process`: Wait for a process or process chain to exit. The `exitcode` field of a process can be used to determine success or failure.
- `Task`: Wait for a `Task` to finish. If the task fails with an exception, a `TaskFailedException` (which wraps the failed task) is thrown.
- `RawFD`: Wait for changes on a file descriptor (see the `FileWatching` package).

If no argument is passed, the task blocks for an undefined period. A task can only be restarted by an explicit call to `schedule` or `yieldto`.

Often `wait` is called within a `while` loop to ensure a waited-for condition is met before proceeding.

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    wait(c::Channel)

Blocks until the `Channel` `isready`.

    julia> c = Channel(1);

    julia> isready(c)
    false

    julia> task = Task(() -> wait(c));

    julia> schedule(task);

    julia> istaskdone(task)  # task is blocked because channel is not ready
    false

    julia> put!(c, 1);

    julia> istaskdone(task)  # task is now unblocked
    true

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`Base.fetch` — Method

    fetch(t::Task)

Wait for a Task to finish, then return its result value. If the task fails with an exception, a `TaskFailedException` (which wraps the failed task) is thrown.

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`Base.fetch` — Method

    fetch(x::Any)

Return `x`.

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`Base.timedwait` — Function

    timedwait(testcb, timeout::Real; pollint::Real=0.1)

Waits until `testcb()` returns `true` or `timeout` seconds have passed, whichever is earlier. The test function is polled every `pollint` seconds. The minimum value for `pollint` is 0.001 seconds, that is, 1 millisecond.

Return `:ok` or `:timed_out`.

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`Base.Condition` — Type

    Condition()

Create an edge-triggered event source that tasks can wait for. Tasks that call `wait` on a `Condition` are suspended and queued. Tasks are woken up when `notify` is later called on the `Condition`. Edge triggering means that only tasks waiting at the time `notify` is called can be woken up. For level-triggered notifications, you must keep extra state to keep track of whether a notification has happened. The `Channel` and `Threads.Event` types do this, and can be used for level-triggered events.

This object is NOT thread-safe. See `Threads.Condition` for a thread-safe version.

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`Base.Threads.Condition` — Type

    Threads.Condition([lock])

A thread-safe version of `Base.Condition`.

To call `wait` or `notify` on a `Threads.Condition`, you must first call `lock` on it. When `wait` is called, the lock is atomically released during blocking, and will be reacquired before `wait` returns. Therefore idiomatic use of a `Threads.Condition` `c` looks like the following:

    lock(c)
    try
        while !thing_we_are_waiting_for
            wait(c)
        end
    finally
        unlock(c)
    end

Julia 1.2

This functionality requires at least Julia 1.2.

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`Base.Event` — Type

    Event([autoreset=false])

Create a level-triggered event source. Tasks that call `wait` on an `Event` are suspended and queued until `notify` is called on the `Event`. After `notify` is called, the `Event` remains in a signaled state and tasks will no longer block when waiting for it, until `reset` is called.

If `autoreset` is true, at most one task will be released from `wait` for each call to `notify`.

This provides an acquire & release memory ordering on notify/wait.

Julia 1.1

This functionality requires at least Julia 1.1.

Julia 1.8

The `autoreset` functionality and memory ordering guarantee requires at least Julia 1.8.

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`Base.notify` — Function

    notify(condition, val=nothing; all=true, error=false)

Wake up tasks waiting for a condition, passing them `val`. If `all` is `true` (the default), all waiting tasks are woken, otherwise only one is. If `error` is `true`, the passed value is raised as an exception in the woken tasks.

Return the count of tasks woken up. Return 0 if no tasks are waiting on `condition`.

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`Base.reset` — Method

    reset(::Event)

Reset an Event back into an un-set state. Then any future calls to `wait` will block until `notify` is called again.

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`Base.Semaphore` — Type

    Semaphore(sem_size)

Create a counting semaphore that allows at most `sem_size` acquires to be in use at any time. Each acquire must be matched with a release.

This provides a acquire & release memory ordering on acquire/release calls.

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`Base.acquire` — Function

    acquire(s::Semaphore)

Wait for one of the `sem_size` permits to be available, blocking until one can be acquired.

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    acquire(f, s::Semaphore)

Execute `f` after acquiring from Semaphore `s`, and `release` on completion or error.

For example, a do-block form that ensures only 2 calls of `foo` will be active at the same time:

    s = Base.Semaphore(2)
    @sync for _ in 1:100
        Threads.@spawn begin
            Base.acquire(s) do
                foo()
            end
        end
    end

Julia 1.8

This method requires at least Julia 1.8.

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`Base.release` — Function

    release(s::Semaphore)

Return one permit to the pool, possibly allowing another task to acquire it and resume execution.

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`Base.AbstractLock` — Type

    AbstractLock

Abstract supertype describing types that implement the synchronization primitives: `lock`, `trylock`, `unlock`, and `islocked`.

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`Base.lock` — Function

    lock(lock)

Acquire the `lock` when it becomes available. If the lock is already locked by a different task/thread, wait for it to become available.

Each `lock` must be matched by an `unlock`.

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    lock(f::Function, lock)

Acquire the `lock`, execute `f` with the `lock` held, and release the `lock` when `f` returns. If the lock is already locked by a different task/thread, wait for it to become available.

When this function returns, the `lock` has been released, so the caller should not attempt to `unlock` it.

Julia 1.7

Using a `Channel` as the second argument requires Julia 1.7 or later.

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`Base.unlock` — Function

    unlock(lock)

Releases ownership of the `lock`.

If this is a recursive lock which has been acquired before, decrement an internal counter and return immediately.

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`Base.trylock` — Function

    trylock(lock) -> Success (Boolean)

Acquire the lock if it is available, and return `true` if successful. If the lock is already locked by a different task/thread, return `false`.

Each successful `trylock` must be matched by an `unlock`.

Function `trylock` combined with `islocked` can be used for writing the test-and-test-and-set or exponential backoff algorithms if it is supported by the `typeof(lock)` (read its documentation).

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`Base.islocked` — Function

    islocked(lock) -> Status (Boolean)

Check whether the `lock` is held by any task/thread. This function alone should not be used for synchronization. However, `islocked` combined with `trylock` can be used for writing the test-and-test-and-set or exponential backoff algorithms if it is supported by the `typeof(lock)` (read its documentation).

Extended help

For example, an exponential backoff can be implemented as follows if the `lock` implementation satisfied the properties documented below.

    nspins = 0
    while true
        while islocked(lock)
            GC.safepoint()
            nspins += 1
            nspins > LIMIT && error("timeout")
        end
        trylock(lock) && break
        backoff()
    end

Implementation

A lock implementation is advised to define `islocked` with the following properties and note it in its docstring.

- `islocked(lock)` is data-race-free.
- If `islocked(lock)` returns `false`, an immediate invocation of `trylock(lock)` must succeed (returns `true`) if there is no interference from other tasks.

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`Base.ReentrantLock` — Type

    ReentrantLock()

Creates a re-entrant lock for synchronizing `Task`s. The same task can acquire the lock as many times as required. Each `lock` must be matched with an `unlock`.

Calling 'lock' will also inhibit running of finalizers on that thread until the corresponding 'unlock'. Use of the standard lock pattern illustrated below should naturally be supported, but beware of inverting the try/lock order or missing the try block entirely (e.g. attempting to return with the lock still held):

This provides a acquire/release memory ordering on lock/unlock calls.

    lock(l)
    try
        <atomic work>
    finally
        unlock(l)
    end

If `!islocked(lck::ReentrantLock)` holds, `trylock(lck)` succeeds unless there are other tasks attempting to hold the lock "at the same time."

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## Channels

`Base.AbstractChannel` — Type

    AbstractChannel{T}

Representation of a channel passing objects of type `T`.

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`Base.Channel` — Type

    Channel{T=Any}(size::Int=0)

Constructs a `Channel` with an internal buffer that can hold a maximum of `size` objects of type `T`. `put!` calls on a full channel block until an object is removed with `take!`.

`Channel(0)` constructs an unbuffered channel. `put!` blocks until a matching `take!` is called. And vice-versa.

Other constructors:

- `Channel()`: default constructor, equivalent to `Channel{Any}(0)`
- `Channel(Inf)`: equivalent to `Channel{Any}(typemax(Int))`
- `Channel(sz)`: equivalent to `Channel{Any}(sz)`

Julia 1.3

The default constructor `Channel()` and default `size=0` were added in Julia 1.3.

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`Base.Channel` — Method

    Channel{T=Any}(func::Function, size=0; taskref=nothing, spawn=false, threadpool=nothing)

Create a new task from `func`, bind it to a new channel of type `T` and size `size`, and schedule the task, all in a single call. The channel is automatically closed when the task terminates.

`func` must accept the bound channel as its only argument.

If you need a reference to the created task, pass a `Ref{Task}` object via the keyword argument `taskref`.

If `spawn=true`, the `Task` created for `func` may be scheduled on another thread in parallel, equivalent to creating a task via `Threads.@spawn`.

If `spawn=true` and the `threadpool` argument is not set, it defaults to `:default`.

If the `threadpool` argument is set (to `:default` or `:interactive`), this implies that `spawn=true` and the new Task is spawned to the specified threadpool.

Return a `Channel`.

Examples

    julia> chnl = Channel() do ch
               foreach(i -> put!(ch, i), 1:4)
           end;

    julia> typeof(chnl)
    Channel{Any}

    julia> for i in chnl
               @show i
           end;
    i = 1
    i = 2
    i = 3
    i = 4

Referencing the created task:

    julia> taskref = Ref{Task}();

    julia> chnl = Channel(taskref=taskref) do ch
               println(take!(ch))
           end;

    julia> istaskdone(taskref[])
    false

    julia> put!(chnl, "Hello");
    Hello

    julia> istaskdone(taskref[])
    true

Julia 1.3

The `spawn=` parameter was added in Julia 1.3. This constructor was added in Julia 1.3. In earlier versions of Julia, Channel used keyword arguments to set `size` and `T`, but those constructors are deprecated.

Julia 1.9

The `threadpool=` argument was added in Julia 1.9.

    julia> chnl = Channel{Char}(1, spawn=true) do ch
               for c in "hello world"
                   put!(ch, c)
               end
           end
    Channel{Char}(1) (2 items available)

    julia> String(collect(chnl))
    "hello world"

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`Base.put!` — Method

    put!(c::Channel, v)

Append an item `v` to the channel `c`. Blocks if the channel is full.

For unbuffered channels, blocks until a `take!` is performed by a different task.

Julia 1.1

`v` now gets converted to the channel's type with `convert` as `put!` is called.

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`Base.take!` — Method

    take!(c::Channel)

Removes and returns a value from a `Channel` in order. Blocks until data is available. For unbuffered channels, blocks until a `put!` is performed by a different task.

Examples

Buffered channel:

    julia> c = Channel(1);

    julia> put!(c, 1);

    julia> take!(c)
    1

Unbuffered channel:

    julia> c = Channel(0);

    julia> task = Task(() -> put!(c, 1));

    julia> schedule(task);

    julia> take!(c)
    1

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`Base.isready` — Method

    isready(c::Channel)

Determines whether a `Channel` has a value stored in it. Returns immediately, does not block.

For unbuffered channels returns `true` if there are tasks waiting on a `put!`.

Examples

Buffered channel:

    julia> c = Channel(1);

    julia> isready(c)
    false

    julia> put!(c, 1);

    julia> isready(c)
    true

Unbuffered channel:

    julia> c = Channel();

    julia> isready(c)  # no tasks waiting to put!
    false

    julia> task = Task(() -> put!(c, 1));

    julia> schedule(task);  # schedule a put! task

    julia> isready(c)
    true

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`Base.fetch` — Method

    fetch(c::Channel)

Waits for and returns (without removing) the first available item from the `Channel`. Note: `fetch` is unsupported on an unbuffered (0-size) `Channel`.

Examples

Buffered channel:

    julia> c = Channel(3) do ch
               foreach(i -> put!(ch, i), 1:3)
           end;

    julia> fetch(c)
    1

    julia> collect(c)  # item is not removed
    3-element Vector{Any}:
     1
     2
     3

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`Base.close` — Method

    close(c::Channel[, excp::Exception])

Close a channel. An exception (optionally given by `excp`), is thrown by:

- `put!` on a closed channel.
- `take!` and `fetch` on an empty, closed channel.

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`Base.bind` — Method

    bind(chnl::Channel, task::Task)

Associate the lifetime of `chnl` with a task. `Channel` `chnl` is automatically closed when the task terminates. Any uncaught exception in the task is propagated to all waiters on `chnl`.

The `chnl` object can be explicitly closed independent of task termination. Terminating tasks have no effect on already closed `Channel` objects.

When a channel is bound to multiple tasks, the first task to terminate will close the channel. When multiple channels are bound to the same task, termination of the task will close all of the bound channels.

Examples

    julia> c = Channel(0);

    julia> task = @async foreach(i->put!(c, i), 1:4);

    julia> bind(c,task);

    julia> for i in c
               @show i
           end;
    i = 1
    i = 2
    i = 3
    i = 4

    julia> isopen(c)
    false

    julia> c = Channel(0);

    julia> task = @async (put!(c, 1); error("foo"));

    julia> bind(c, task);

    julia> take!(c)
    1

    julia> put!(c, 1);
    ERROR: TaskFailedException
    Stacktrace:
    [...]
        nested task error: foo
    [...]

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## Low-level synchronization using `schedule` and `wait`

The easiest correct use of `schedule` is on a `Task` that is not started (scheduled) yet. However, it is possible to use `schedule` and `wait` as a very low-level building block for constructing synchronization interfaces. A crucial pre-condition of calling `schedule(task)` is that the caller must "own" the `task`; i.e., it must know that the call to `wait` in the given `task` is happening at the locations known to the code calling `schedule(task)`. One strategy for ensuring such pre-condition is to use atomics, as demonstrated in the following example:

    @enum OWEState begin
        OWE_EMPTY
        OWE_WAITING
        OWE_NOTIFYING
    end

    mutable struct OneWayEvent
        @atomic state::OWEState
        task::Task
        OneWayEvent() = new(OWE_EMPTY)
    end

    function Base.notify(ev::OneWayEvent)
        state = @atomic ev.state
        while state !== OWE_NOTIFYING
            # Spin until we successfully update the state to OWE_NOTIFYING:
            state, ok = @atomicreplace(ev.state, state => OWE_NOTIFYING)
            if ok
                if state == OWE_WAITING
                    # OWE_WAITING -> OWE_NOTIFYING transition means that the waiter task is
                    # already waiting or about to call `wait`. The notifier task must wake up
                    # the waiter task.
                    schedule(ev.task)
                else
                    @assert state == OWE_EMPTY
                    # Since we are assuming that there is only one notifier task (for
                    # simplicity), we know that the other possible case here is OWE_EMPTY.
                    # We do not need to do anything because we know that the waiter task has
                    # not called `wait(ev::OneWayEvent)` yet.
                end
                break
            end
        end
        return
    end

    function Base.wait(ev::OneWayEvent)
        ev.task = current_task()
        state, ok = @atomicreplace(ev.state, OWE_EMPTY => OWE_WAITING)
        if ok
            # OWE_EMPTY -> OWE_WAITING transition means that the notifier task is guaranteed to
            # invoke OWE_WAITING -> OWE_NOTIFYING transition.  The waiter task must call
            # `wait()` immediately.  In particular, it MUST NOT invoke any function that may
            # yield to the scheduler at this point in code.
            wait()
        else
            @assert state == OWE_NOTIFYING
            # Otherwise, the `state` must have already been moved to OWE_NOTIFYING by the
            # notifier task.
        end
        return
    end

    ev = OneWayEvent()
    @sync begin
        @async begin
            wait(ev)
            println("done")
        end
        println("notifying...")
        notify(ev)
    end

    # output
    notifying...
    done

`OneWayEvent` lets one task to `wait` for another task's `notify`. It is a limited communication interface since `wait` can only be used once from a single task (note the non-atomic assignment of `ev.task`)

In this example, `notify(ev::OneWayEvent)` is allowed to call `schedule(ev.task)` if and only if it modifies the state from `OWE_WAITING` to `OWE_NOTIFYING`. This lets us know that the task executing `wait(ev::OneWayEvent)` is now in the `ok` branch and that there cannot be other tasks that tries to `schedule(ev.task)` since their `@atomicreplace(ev.state, state => OWE_NOTIFYING)` will fail.

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This document was generated with Documenter.jl version 0.27.23 on Tuesday 14 November 2023. Using Julia version 1.9.4.