# `Task`
[🔗](https://github.com/elixir-lang/elixir/blob/v1.20.0-rc.3/lib/elixir/lib/task.ex#L5)

Conveniences for spawning and awaiting tasks.

Tasks are processes meant to execute one particular
action throughout their lifetime, often with little or no
communication with other processes. The most common use case
for tasks is to convert sequential code into concurrent code
by computing a value asynchronously:

    task = Task.async(fn -> do_some_work() end)
    res = do_some_other_work()
    res + Task.await(task)

Tasks spawned with `async` can be awaited on by their caller
process (and only their caller) as shown in the example above.
They are implemented by spawning a process that sends a message
to the caller once the given computation is performed.

Compared to plain processes, started with `spawn/1`, tasks
include monitoring metadata and logging in case of errors.

Besides `async/1` and `await/2`, tasks can also be
started as part of a supervision tree and dynamically spawned
on remote nodes. We will explore these scenarios next.

## async and await

One of the common uses of tasks is to convert sequential code
into concurrent code with `Task.async/1` while keeping its semantics.
When invoked, a new process will be created, linked and monitored
by the caller. Once the task action finishes, a message will be sent
to the caller with the result.

`Task.await/2` is used to read the message sent by the task.

There are two important things to consider when using `async`:

  1. If you are using async tasks, you **must await** a reply
     as they are *always* sent. If you are not expecting a reply,
     consider using `Task.start_link/1` as detailed below.

  2. Async tasks link the caller and the spawned process. This
     means that, if the caller crashes, the task will crash
     too and vice-versa. This is on purpose: if the process
     meant to receive the result no longer exists, there is
     no purpose in completing the computation. If this is not
     desired, you will want to use supervised tasks, described
     in a subsequent section.

## Tasks are processes

Tasks are processes and so data will need to be completely copied
to them. Take the following code as an example:

    large_data = fetch_large_data()
    task = Task.async(fn -> do_some_work(large_data) end)
    res = do_some_other_work()
    res + Task.await(task)

The code above copies over all of `large_data`, which can be
resource intensive depending on the size of the data.
There are two ways to address this.

First, if you need to access only part of `large_data`,
consider extracting it before the task:

    large_data = fetch_large_data()
    subset_data = large_data.some_field
    task = Task.async(fn -> do_some_work(subset_data) end)

Alternatively, if you can move the data loading altogether
to the task, it may be even better:

    task = Task.async(fn ->
      large_data = fetch_large_data()
      do_some_work(large_data)
    end)

## Dynamically supervised tasks

The `Task.Supervisor` module allows developers to dynamically
create multiple supervised tasks.

A short example is:

    {:ok, pid} = Task.Supervisor.start_link()

    task =
      Task.Supervisor.async(pid, fn ->
        # Do something
      end)

    Task.await(task)

However, in the majority of cases, you want to add the task supervisor
to your supervision tree:

    Supervisor.start_link([
      {Task.Supervisor, name: MyApp.TaskSupervisor}
    ], strategy: :one_for_one)

And now you can use async/await by passing the name of
the supervisor instead of the PID:

    Task.Supervisor.async(MyApp.TaskSupervisor, fn ->
      # Do something
    end)
    |> Task.await()

We encourage developers to rely on supervised tasks as much as possible.
Supervised tasks improve the visibility of how many tasks are running
at a given moment and enable a variety of patterns that give you
explicit control on how to handle the results, errors, and timeouts.
Here is a summary:

  * Using `Task.Supervisor.start_child/2` allows you to start a fire-and-forget
    task when you don't care about its results or if it completes successfully or not.

  * Using `Task.Supervisor.async/2` + `Task.await/2` allows you to execute
    tasks concurrently and retrieve its result. If the task fails,
    the caller will also fail.

  * Using `Task.Supervisor.async_nolink/2` + `Task.yield/2` + `Task.shutdown/2`
    allows you to execute tasks concurrently and retrieve their results
    or the reason they failed within a given time frame. If the task fails,
    the caller won't fail. You will receive the error reason either on
    `yield` or `shutdown`.

Furthermore, the supervisor guarantees all tasks terminate within a
configurable shutdown period when your application shuts down. See the
`Task.Supervisor` module for details on the supported operations.

### Distributed tasks

With `Task.Supervisor`, it is easy to dynamically start tasks across nodes:

    # First on the remote node named :remote@local
    Task.Supervisor.start_link(name: MyApp.DistSupervisor)

    # Then on the local client node
    supervisor = {MyApp.DistSupervisor, :remote@local}
    Task.Supervisor.async(supervisor, MyMod, :my_fun, [arg1, arg2, arg3])

Note that, as above, when working with distributed tasks, one should use the
`Task.Supervisor.async/5` function that expects explicit module, function,
and arguments, instead of `Task.Supervisor.async/3` that works with anonymous
functions. That's because anonymous functions expect the same module version
to exist on all involved nodes. Check the `Agent` module documentation for
more information on distributed processes as the limitations described there
apply to the whole ecosystem.

## Statically supervised tasks

The `Task` module implements the `child_spec/1` function, which
allows it to be started directly under a regular `Supervisor` -
instead of a `Task.Supervisor` - by passing a tuple with a function
to run:

    Supervisor.start_link([
      {Task, fn -> :some_work end}
    ], strategy: :one_for_one)

This is often useful when you need to execute code concurrently while
setting up your supervision tree. For example: to warm up caches,
log the initialization status, and such.

If you don't want to put the Task code directly under the `Supervisor`,
you can wrap the `Task` in its own module, similar to how you would
do with a `GenServer` or an `Agent`:

    defmodule MyTask do
      use Task

      def start_link(arg) do
        Task.start_link(__MODULE__, :run, [arg])
      end

      def run(arg) do
        # ...
      end
    end

And then passing it to the supervisor:

    Supervisor.start_link([
      {MyTask, arg}
    ], strategy: :one_for_one)

Since these tasks are supervised and not directly linked to the caller,
they cannot be awaited on. By default, the functions `Task.start/1`
and `Task.start_link/1` are for fire-and-forget tasks, where you don't
care about the results or if it completes successfully or not.

Keep in mind the Supervisor will not wait for the task to finish running
before starting the next child or returning. If you need synchronous
initialization, then either use an `Agent` or a `GenServer`.

> #### `use Task` {: .info}
>
> When you `use Task`, the `Task` module will define a
> `child_spec/1` function, so your module can be used
> as a child in a supervision tree.

The generated `child_spec/1` can be customized with the following options:

  * `:id` - the child specification identifier, defaults to the current module
  * `:restart` - when the child should be restarted, defaults to `:temporary`
  * `:shutdown` - how to shut down the child, either immediately or by giving it time to shut down

Opposite to `GenServer`, `Agent` and `Supervisor`, a Task has
a default `:restart` of `:temporary`. This means the task will
not be restarted even if it crashes. If you desire the task to
be restarted for non-successful exits, do:

    use Task, restart: :transient

If you want the task to always be restarted:

    use Task, restart: :permanent

See the "Child specification" section in the `Supervisor` module
for more detailed information. The `@doc` annotation immediately
preceding `use Task` will be attached to the generated `child_spec/1`
function.

## Ancestor and Caller Tracking

Whenever you start a new process, Elixir annotates the process with the parent
through the `$ancestors` key in the process dictionary. This is often used to
track the hierarchy inside a supervision tree.

For example, we recommend developers to always start tasks under a supervisor.
This provides more visibility and allows you to control how those tasks are
terminated when a node shuts down. That might look something like
`Task.Supervisor.start_child(MySupervisor, task_function)`. This means
that, although your code is the one invoking the task, the actual ancestor of
the task is the supervisor, as the supervisor is the one effectively starting it.

To track the relationship between your code and the task, we use the `$callers`
key in the process dictionary. Therefore, assuming the `Task.Supervisor` call
above, we have:

    [your code] -- calls --> [supervisor] ---- spawns --> [task]

Which means we store the following relationships:

    [your code]              [supervisor] <-- ancestor -- [task]
        ^                                                  |
        |--------------------- caller ---------------------|

The list of callers of the current process can be retrieved from the Process
dictionary with `Process.get(:"$callers")`. This will return either `nil` or
a list `[pid_n, ..., pid2, pid1]` with at least one entry where `pid_n` is
the PID that called the current process, `pid2` called `pid_n`, and `pid2` was
called by `pid1`.

If a task crashes, the callers field is included as part of the log message
metadata under the `:callers` key.

# `async_stream_option`
*since 1.17.0* 

```elixir
@type async_stream_option() ::
  {:max_concurrency, pos_integer()}
  | {:ordered, boolean()}
  | {:timeout, timeout()}
  | {:on_timeout, :exit | :kill_task}
  | {:zip_input_on_exit, boolean()}
```

Options given to `async_stream` functions.

# `ref`

```elixir
@opaque ref()
```

The task opaque reference.

# `t`

```elixir
@type t() :: %Task{mfa: mfa(), owner: pid(), pid: pid() | nil, ref: ref()}
```

The Task type.

See [`%Task{}`](`__struct__/0`) for information about each field of the structure.

# `__struct__`
*struct* 

The Task struct.

It contains these fields:

  * `:mfa` - a three-element tuple containing the module, function name,
    and arity invoked to start the task in `async/1` and `async/3`

  * `:owner` - the PID of the process that started the task

  * `:pid` - the PID of the task process; `nil` if there is no process
    specifically assigned for the task

  * `:ref` - an opaque term used as the task monitor reference

# `async`

```elixir
@spec async((-&gt; any())) :: t()
```

Starts a task that must be awaited on.

`fun` must be a zero-arity anonymous function. This function
spawns a process that is linked to and monitored by the caller
process. A `Task` struct is returned containing the relevant
information.

If you start an `async`, you **must await**. This is either done
by calling `Task.await/2` or `Task.yield/2` followed by
`Task.shutdown/2` on the returned task. Alternatively, if you
spawn a task inside a `GenServer`, then the `GenServer` will
automatically await for you and call `c:GenServer.handle_info/2`
with the task response and associated `:DOWN` message.

Read the `Task` module documentation for more information about
the general usage of async tasks.

## Linking

This function spawns a process that is linked to and monitored
by the caller process. The linking part is important because it
aborts the task if the parent process dies. It also guarantees
the code before async/await has the same properties after you
add the async call. For example, imagine you have this:

    x = heavy_function()
    y = some_function()
    x + y

Now you want to make the `heavy_function()` async:

    x = Task.async(&heavy_function/0)
    y = some_function()
    Task.await(x) + y

As before, if `heavy_function/0` fails, the whole computation will
fail, including the caller process. If you don't want the task
to fail then you must change the `heavy_fun/0` code in the
same way you would achieve it if you didn't have the async call.
For example, to either return `{:ok, val} | :error` results or,
in more extreme cases, by using `try/rescue`. In other words,
an asynchronous task should be thought of as an extension of the
caller process rather than a mechanism to isolate it from all errors.

If you don't want to link the caller to the task, then you
must use a supervised task with `Task.Supervisor` and call
`Task.Supervisor.async_nolink/2`.

In any case, avoid any of the following:

  * Setting `:trap_exit` to `true` - trapping exits should be
    used only in special circumstances as it would make your
    process immune to not only exits from the task but from
    any other processes.

    Moreover, even when trapping exits, calling `await` will
    still exit if the task has terminated without sending its
    result back.

  * Unlinking the task process started with `async`/`await`.
    If you unlink the processes and the task does not belong
    to any supervisor, you may leave dangling tasks in case
    the caller process dies.

## Metadata

The task created with this function stores `:erlang.apply/2` in
its `:mfa` metadata field, which is used internally to apply
the anonymous function. Use `async/3` if you want another function
to be used as metadata.

# `async`

```elixir
@spec async(module(), atom(), [term()]) :: t()
```

Starts a task that must be awaited on.

Similar to `async/1` except the function to be started is
specified by the given `module`, `function_name`, and `args`.
The `module`, `function_name`, and its arity are stored as
a tuple in the `:mfa` field for reflection purposes.

# `async_stream`
*since 1.4.0* 

```elixir
@spec async_stream(Enumerable.t(), (term() -&gt; term()), [async_stream_option()]) ::
  Enumerable.t()
```

Returns a stream that runs the given function `fun` concurrently
on each element in `enumerable`.

Works the same as `async_stream/5` but with an anonymous function instead of a
module-function-arguments tuple. `fun` must be a one-arity anonymous function.

Each `enumerable` element is passed as argument to the given function `fun` and
processed by its own task. The tasks will be linked to the caller process, similarly
to `async/1`.

## Example

Count the code points in each string asynchronously, then add the counts together using reduce.

    iex> strings = ["long string", "longer string", "there are many of these"]
    iex> stream = Task.async_stream(strings, fn text -> text |> String.codepoints() |> Enum.count() end)
    iex> Enum.sum_by(stream, fn {:ok, num} -> num end)
    47

See `async_stream/5` for discussion, options, and more examples.

# `async_stream`
*since 1.4.0* 

```elixir
@spec async_stream(Enumerable.t(), module(), atom(), [term()], [async_stream_option()]) ::
  Enumerable.t()
```

Returns a stream where the given function (`module` and `function_name`)
is mapped concurrently on each element in `enumerable`.

Each element of `enumerable` will be prepended to the given `args` and
processed by its own task. Those tasks will be linked to an intermediate
process that is then linked to the caller process. This means a failure
in a task terminates the caller process and a failure in the caller
process terminates all tasks.

When streamed, each task will emit `{:ok, value}` upon successful
completion or `{:exit, reason}` if the caller is trapping exits.
It's possible to have `{:exit, {element, reason}}` for exits
using the `:zip_input_on_exit` option. The order of results depends
on the value of the `:ordered` option.

The level of concurrency and the time tasks are allowed to run can
be controlled via options (see the "Options" section below).

Consider using `Task.Supervisor.async_stream/6` to start tasks
under a supervisor. If you find yourself trapping exits to ensure
errors in the tasks do not terminate the caller process, consider
using `Task.Supervisor.async_stream_nolink/6` to start tasks that
are not linked to the caller process.

## Options

  * `:max_concurrency` - sets the maximum number of tasks to run
    at the same time. Defaults to `System.schedulers_online/0`.

  * `:ordered` - whether the results should be returned in the same order
    as the input stream. When the output is ordered, Elixir may need to
    buffer results to emit them in the original order. Setting this option
    to false disables the need to buffer at the cost of removing ordering.
    This is also useful when you're using the tasks only for the side effects.
    Note that regardless of what `:ordered` is set to, the tasks will
    process asynchronously. If you need to process elements in order,
    consider using `Enum.map/2` or `Enum.each/2` instead. Defaults to `true`.

  * `:timeout` - the maximum amount of time (in milliseconds or `:infinity`)
    each task is allowed to execute for. Defaults to `5000`.

  * `:on_timeout` - what to do when a task times out. The possible
    values are:
    * `:exit` (default) - the caller (the process that spawned the tasks) exits.
    * `:kill_task` - the task that timed out is killed. The value
      emitted for that task is `{:exit, :timeout}`.

  * `:zip_input_on_exit` - (since v1.14.0) adds the original
    input to `:exit` tuples. The value emitted for that task is
    `{:exit, {input, reason}}`, where `input` is the collection element
    that caused an exit during processing. Defaults to `false`.

## Example

Let's build a stream and then enumerate it:

    stream = Task.async_stream(collection, Mod, :expensive_fun, [])
    Enum.to_list(stream)

The concurrency can be increased or decreased using the `:max_concurrency`
option. For example, if the tasks are IO heavy, the value can be increased:

    max_concurrency = System.schedulers_online() * 2
    stream = Task.async_stream(collection, Mod, :expensive_fun, [], max_concurrency: max_concurrency)
    Enum.to_list(stream)

If you do not care about the results of the computation, you can run
the stream with `Stream.run/1`. Also set `ordered: false`, as you don't
care about the order of the results either:

    stream = Task.async_stream(collection, Mod, :expensive_fun, [], ordered: false)
    Stream.run(stream)

## First async tasks to complete

You can also use `async_stream/3` to execute M tasks and find the N tasks
to complete. For example:

    [
      &heavy_call_1/0,
      &heavy_call_2/0,
      &heavy_call_3/0
    ]
    |> Task.async_stream(fn fun -> fun.() end, ordered: false, max_concurrency: 3)
    |> Stream.filter(&match?({:ok, _}, &1))
    |> Enum.take(2)

In the example above, we are executing three tasks and waiting for the
first 2 to complete. We use `Stream.filter/2` to restrict ourselves only
to successfully completed tasks, and then use `Enum.take/2` to retrieve
N items. Note it is important to set both `ordered: false` and
`max_concurrency: M`, where M is the number of tasks, to make sure all
calls execute concurrently.

### Attention: unbound async + take

If you want to potentially process a high number of items and keep only
part of the results, you may end-up processing more items than desired.
Let's see an example:

    1..100
    |> Task.async_stream(fn i ->
      Process.sleep(100)
      IO.puts(to_string(i))
    end)
    |> Enum.take(10)

Running the example above in a machine with 8 cores will process 16 items,
even though you want only 10 elements, since `async_stream/3` process items
concurrently. That's because it will process 8 elements at once. Then all 8
elements complete at roughly the same time, causing 8 elements to be kicked
off for processing. Out of these extra 8, only 2 will be used, and the rest
will be terminated.

Depending on the problem, you can filter or limit the number of elements
upfront:

    1..100
    |> Stream.take(10)
    |> Task.async_stream(fn i ->
      Process.sleep(100)
      IO.puts(to_string(i))
    end)
    |> Enum.to_list()

In other cases, you likely want to tweak `:max_concurrency` to limit how
many elements may be over processed at the cost of reducing concurrency.
You can also set the number of elements to take to be a multiple of
`:max_concurrency`. For instance, setting `max_concurrency: 5` in the
example above.

# `await`

```elixir
@spec await(t(), timeout()) :: term()
```

Awaits a task reply and returns it.

In case the task process dies, the caller process will exit with the same
reason as the task.

A timeout, in milliseconds or `:infinity`, can be given with a default value
of `5000`. If the timeout is exceeded, then the caller process will exit.
If the task process is linked to the caller process which is the case when
a task is started with `async`, then the task process will also exit. If the
task process is trapping exits or not linked to the caller process, then it
will continue to run.

This function assumes the task's monitor is still active or the monitor's
`:DOWN` message is in the message queue. If it has been demonitored, or the
message already received, this function will wait for the duration of the
timeout awaiting the message.

This function can only be called once for any given task. If you want
to be able to check multiple times if a long-running task has finished
its computation, use `yield/2` instead.

## Examples

    iex> task = Task.async(fn -> 1 + 1 end)
    iex> Task.await(task)
    2

## Compatibility with OTP behaviours

It is not recommended to `await` a long-running task inside an OTP
behaviour such as `GenServer`. Instead, you should match on the message
coming from a task inside your `c:GenServer.handle_info/2` callback.

A GenServer will receive two messages on `handle_info/2`:

  * `{ref, result}` - the reply message where `ref` is the monitor
    reference returned by the `task.ref` and `result` is the task
    result

  * `{:DOWN, ref, :process, pid, reason}` - since all tasks are also
    monitored, you will also receive the `:DOWN` message delivered by
    `Process.monitor/1`. If you receive the `:DOWN` message without a
    a reply, it means the task crashed

Another consideration to have in mind is that tasks started by `Task.async/1`
are always linked to their callers and you may not want the GenServer to
crash if the task crashes. Therefore, it is preferable to instead use
`Task.Supervisor.async_nolink/3` inside OTP behaviours. For completeness, here
is an example of a GenServer that start tasks and handles their results:

    defmodule GenServerTaskExample do
      use GenServer

      def start_link(opts) do
        GenServer.start_link(__MODULE__, :ok, opts)
      end

      def init(_opts) do
        # We will keep all running tasks in a map
        {:ok, %{tasks: %{}}}
      end

      # Imagine we invoke a task from the GenServer to access a URL...
      def handle_call(:some_message, _from, state) do
        url = ...
        task = Task.Supervisor.async_nolink(MyApp.TaskSupervisor, fn -> fetch_url(url) end)

        # After we start the task, we store its reference and the url it is fetching
        state = put_in(state.tasks[task.ref], url)

        {:reply, :ok, state}
      end

      # If the task succeeds...
      def handle_info({ref, result}, state) do
        # The task succeed so we can demonitor its reference
        Process.demonitor(ref, [:flush])

        {url, state} = pop_in(state.tasks[ref])
        IO.puts("Got #{inspect(result)} for URL #{inspect url}")
        {:noreply, state}
      end

      # If the task fails...
      def handle_info({:DOWN, ref, _, _, reason}, state) do
        {url, state} = pop_in(state.tasks[ref])
        IO.puts("URL #{inspect url} failed with reason #{inspect(reason)}")
        {:noreply, state}
      end
    end

With the server defined, you will want to start the task supervisor
above and the GenServer in your supervision tree:

    children = [
      {Task.Supervisor, name: MyApp.TaskSupervisor},
      {GenServerTaskExample, name: MyApp.GenServerTaskExample}
    ]

    Supervisor.start_link(children, strategy: :one_for_one)

# `await_many`
*since 1.11.0* 

```elixir
@spec await_many([t()], timeout()) :: [term()]
```

Awaits replies from multiple tasks and returns them.

This function receives a list of tasks and waits for their replies in the
given time interval. It returns a list of the results, in the same order as
the tasks supplied in the `tasks` input argument.

If any of the task processes dies, the caller process will exit with the same
reason as that task.

A timeout, in milliseconds or `:infinity`, can be given with a default value
of `5000`. If the timeout is exceeded, then the caller process will exit.
Any task processes that are linked to the caller process (which is the case
when a task is started with `async`) will also exit. Any task processes that
are trapping exits or not linked to the caller process will continue to run.

This function assumes the tasks' monitors are still active or the monitor's
`:DOWN` message is in the message queue. If any tasks have been demonitored,
or the message already received, this function will wait for the duration of
the timeout.

This function can only be called once for any given task. If you want to be
able to check multiple times if a long-running task has finished its
computation, use `yield_many/2` instead.

## Compatibility with OTP behaviours

It is not recommended to `await` long-running tasks inside an OTP behaviour
such as `GenServer`. See `await/2` for more information.

## Examples

    iex> tasks = [
    ...>   Task.async(fn -> 1 + 1 end),
    ...>   Task.async(fn -> 2 + 3 end)
    ...> ]
    iex> Task.await_many(tasks)
    [2, 5]

# `child_spec`
*since 1.5.0* 

```elixir
@spec child_spec(term()) :: Supervisor.child_spec()
```

Returns a specification to start a task under a supervisor.

`arg` is passed as the argument to `Task.start_link/1` in the `:start` field
of the spec.

For more information, see the `Supervisor` module,
the `Supervisor.child_spec/2` function and the `t:Supervisor.child_spec/0` type.

# `completed`
*since 1.13.0* 

```elixir
@spec completed(any()) :: t()
```

Starts a task that immediately completes with the given `result`.

Unlike `async/1`, this task does not spawn a linked process. It can
be awaited or yielded like any other task.

## Usage

In some cases, it is useful to create a "completed" task that represents
a task that has already run and generated a result. For example, when
processing data you may be able to determine that certain inputs are
invalid before dispatching them for further processing:

    def process(data) do
      tasks =
        for entry <- data do
          if invalid_input?(entry) do
            Task.completed({:error, :invalid_input})
          else
            Task.async(fn -> further_process(entry) end)
          end
        end

      Task.await_many(tasks)
    end

In many cases, `Task.completed/1` may be avoided in favor of returning the
result directly.  You should generally only require this variant when working
with mixed asynchrony, when a group of inputs will be handled partially
synchronously and partially asynchronously.

# `ignore`
*since 1.13.0* 

```elixir
@spec ignore(t()) :: {:ok, term()} | {:exit, term()} | nil
```

Ignores an existing task.

This means the task will continue running, but it will be unlinked
and you can no longer yield, await or shut it down.

Returns `{:ok, reply}` if the reply is received before ignoring the task,
`{:exit, reason}` if the task died before ignoring it, otherwise `nil`.

Important: avoid using [`Task.async/1,3`](`async/1`) and then immediately ignoring
the task. If you want to start tasks you don't care about their
results, use `Task.Supervisor.start_child/2` instead.

# `shutdown`

```elixir
@spec shutdown(t(), timeout() | :brutal_kill) :: {:ok, term()} | {:exit, term()} | nil
```

Unlinks and shuts down the task, and then checks for a reply.

Returns `{:ok, reply}` if the reply is received while shutting down the task,
`{:exit, reason}` if the task died, otherwise `nil`. Once shut down,
you can no longer await or yield it.

The second argument is either a timeout or `:brutal_kill`. In case
of a timeout, a `:shutdown` exit signal is sent to the task process
and if it does not exit within the timeout, it is killed. With `:brutal_kill`
the task is killed straight away. In case the task terminates abnormally
(possibly killed by another process), this function will exit with the same reason.

It is not required to call this function when terminating the caller, unless
exiting with reason `:normal` or if the task is trapping exits. If the caller is
exiting with a reason other than `:normal` and the task is not trapping exits, the
caller's exit signal will stop the task. The caller can exit with reason
`:shutdown` to shut down all of its linked processes, including tasks, that
are not trapping exits without generating any log messages.

If there is no process linked to the task, such as tasks started by
`Task.completed/1`, we check for a response or error accordingly, but without
shutting a process down.

If a task's monitor has already been demonitored or received and there is not
a response waiting in the message queue this function will return
`{:exit, :noproc}` as the result or exit reason can not be determined.

# `start`

```elixir
@spec start((-&gt; any())) :: {:ok, pid()}
```

Starts a task.

`fun` must be a zero-arity anonymous function.

This should only used when the task is used for side-effects
(like I/O) and you have no interest on its results nor if it
completes successfully.

If the current node is shutdown, the node will terminate even
if the task was not completed. For this reason, we recommend
to use `Task.Supervisor.start_child/2` instead, which allows
you to control the shutdown time via the `:shutdown` option.

# `start`

```elixir
@spec start(module(), atom(), [term()]) :: {:ok, pid()}
```

Starts a task.

This should only used when the task is used for side-effects
(like I/O) and you have no interest on its results nor if it
completes successfully.

If the current node is shutdown, the node will terminate even
if the task was not completed. For this reason, we recommend
to use `Task.Supervisor.start_child/2` instead, which allows
you to control the shutdown time via the `:shutdown` option.

# `start_link`

```elixir
@spec start_link((-&gt; any())) :: {:ok, pid()}
```

Starts a task as part of a supervision tree with the given `fun`.

`fun` must be a zero-arity anonymous function.

This is used to start a statically supervised task under a supervision tree.

# `start_link`

```elixir
@spec start_link(module(), atom(), [term()]) :: {:ok, pid()}
```

Starts a task as part of a supervision tree with the given
`module`, `function`, and `args`.

This is used to start a statically supervised task under a supervision tree.

# `yield`

```elixir
@spec yield(t(), timeout()) :: {:ok, term()} | {:exit, term()} | nil
```

Temporarily blocks the caller process waiting for a task reply.

Returns `{:ok, reply}` if the reply is received, `nil` if
no reply has arrived, or `{:exit, reason}` if the task has already
exited. Keep in mind that normally a task failure also causes
the process owning the task to exit. Therefore this function can
return `{:exit, reason}` if at least one of the conditions below apply:

  * the task process exited with the reason `:normal`
  * the task isn't linked to the caller (the task was started
    with `Task.Supervisor.async_nolink/2` or `Task.Supervisor.async_nolink/4`)
  * the caller is trapping exits

A timeout, in milliseconds or `:infinity`, can be given with a default value
of `5000`. If the time runs out before a message from the task is received,
this function will return `nil` and the monitor will remain active. Therefore
`yield/2` can be called multiple times on the same task.

This function assumes the task's monitor is still active or the
monitor's `:DOWN` message is in the message queue. If it has been
demonitored or the message already received, this function will wait
for the duration of the timeout awaiting the message.

If you intend to shut the task down if it has not responded within `timeout`
milliseconds, you should chain this together with `shutdown/1`, like so:

    case Task.yield(task, timeout) || Task.shutdown(task) do
      {:ok, result} ->
        result

      nil ->
        Logger.warning("Failed to get a result in #{timeout}ms")
        nil
    end

If you intend to check on the task but leave it running after the timeout,
you can chain this together with `ignore/1`, like so:

    case Task.yield(task, timeout) || Task.ignore(task) do
      {:ok, result} ->
        result

      nil ->
        Logger.warning("Failed to get a result in #{timeout}ms")
        nil
    end

That ensures that if the task completes after the `timeout` but before `shutdown/1`
has been called, you will still get the result, since `shutdown/1` is designed to
handle this case and return the result.

# `yield_many`

```elixir
@spec yield_many([t()], timeout()) :: [{t(), {:ok, term()} | {:exit, term()} | nil}]
@spec yield_many([t()],
  limit: pos_integer(),
  timeout: timeout(),
  on_timeout: :nothing | :ignore | :kill_task
) :: [{t(), {:ok, term()} | {:exit, term()} | nil}]
```

Yields to multiple tasks in the given time interval.

This function receives a list of tasks and waits for their
replies in the given time interval. It returns a list
of two-element tuples, with the task as the first element
and the yielded result as the second. The tasks in the returned
list will be in the same order as the tasks supplied in the `tasks`
input argument.

Similarly to `yield/2`, each task's result will be

  * `{:ok, term}` if the task has successfully reported its
    result back in the given time interval
  * `{:exit, reason}` if the task has died
  * `nil` if the task keeps running, either because a limit
    has been reached or past the timeout

Check `yield/2` for more information.

## Example

`Task.yield_many/2` allows developers to spawn multiple tasks
and retrieve the results received in a given time frame.
If we combine it with `Task.shutdown/2` (or `Task.ignore/1`),
it allows us to gather those results and cancel (or ignore)
the tasks that have not replied in time.

Let's see an example.

    tasks =
      for i <- 1..10 do
        Task.async(fn ->
          Process.sleep(i * 1000)
          i
        end)
      end

    tasks_with_results = Task.yield_many(tasks, timeout: 5000)

    results =
      Enum.map(tasks_with_results, fn {task, res} ->
        # Shut down the tasks that did not reply nor exit
        res || Task.shutdown(task, :brutal_kill)
      end)

    # Here we are matching only on {:ok, value} and
    # ignoring {:exit, _} (crashed tasks) and `nil` (no replies)
    for {:ok, value} <- results do
      IO.inspect(value)
    end

In the example above, we create tasks that sleep from 1
up to 10 seconds and return the number of seconds they slept for.
If you execute the code all at once, you should see 1 up to 5
printed, as those were the tasks that have replied in the
given time. All other tasks will have been shut down using
the `Task.shutdown/2` call.

As a convenience, you can achieve a similar behavior to above
by specifying the `:on_timeout` option to be `:kill_task` (or
`:ignore`). See `Task.await_many/2` if you would rather exit
the caller process on timeout.

## Options

The second argument is either a timeout or options, which defaults
to this:

  * `:limit` - the maximum amount of tasks to wait for.
    If the limit is reached before the timeout, this function
    returns immediately without triggering the `:on_timeout` behaviour

  * `:timeout` - the maximum amount of time (in milliseconds or `:infinity`)
    each task is allowed to execute for. Defaults to `5000`.

  * `:on_timeout` - what to do when a task times out. The possible
    values are:
    * `:nothing` - do nothing (default). The tasks can still be
      awaited on, yielded on, ignored, or shut down later.
    * `:ignore` - the results of the task will be ignored.
    * `:kill_task` - the task that timed out is killed.

---

*Consult [api-reference.md](api-reference.md) for complete listing*