Tasks

# 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.

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.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.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.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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`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` type does this, and so can be used for level-triggered events.

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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.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.

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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`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.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.Channel` — Type.

    Channel{T}(sz::Int)

Constructs a `Channel` with an internal buffer that can hold a maximum of `sz` 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(Inf)`: equivalent to `Channel{Any}(typemax(Int))`
- `Channel(sz)`: equivalent to `Channel{Any}(sz)`

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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.

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`Base.take!` — Method.

    take!(c::Channel)

Remove and return a value from a `Channel`. Blocks until data is available.

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

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`Base.isready` — Method.

    isready(c::Channel)

Determine whether a `Channel` has a value stored to it. Returns immediately, does not block.

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

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`Base.fetch` — Method.

    fetch(c::Channel)

Wait for and get the first available item from the channel. Does not remove the item. `fetch` is unsupported on an unbuffered (0-size) channel.

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`Base.close` — Method.

    close(c::Channel)

Close a channel. An exception 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: foo
    Stacktrace:
    [...]

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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 less 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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