| commit | 656da64d57149603e5eb96f6e1b49208f0b96fd9 | [log] [tgz] |
|---|---|---|
| author | James Farrell <jamesfarrell@google.com> | Wed Aug 14 18:59:42 2024 +0000 |
| committer | James Farrell <jamesfarrell@google.com> | Wed Aug 14 19:31:18 2024 +0000 |
| tree | 592703c6d9f929b9ca10de66603dcb156beb8f20 | |
| parent | 9e51ef33b6815c128035b9e2af7708e95858dcac [diff] |
Migrate 25 crates to monorepo async-stream async-stream-impl async-task async-trait atomic atty axum bencher bincode bitreader bstr buddy_system_allocator byteorder bytes camino cast cesu8 cexpr cfg-if ciborium ciborium-io ciborium-ll clap_complete clap_derive clap_lex Bug: 339424309 Test: treehugger Change-Id: I13ffbdc10522da818c1517c8f4ce8c051cb0bce0
Task abstraction for building executors.
To spawn a future onto an executor, we first need to allocate it on the heap and keep some state attached to it. The state indicates whether the future is ready for polling, waiting to be woken up, or completed. Such a stateful future is called a task.
All executors have a queue that holds scheduled tasks:
let (sender, receiver) = flume::unbounded();
A task is created using either spawn(), spawn_local(), or spawn_unchecked() which return a Runnable and a Task:
// A future that will be spawned. let future = async { 1 + 2 }; // A function that schedules the task when it gets woken up. let schedule = move |runnable| sender.send(runnable).unwrap(); // Construct a task. let (runnable, task) = async_task::spawn(future, schedule); // Push the task into the queue by invoking its schedule function. runnable.schedule();
The Runnable is used to poll the task's future, and the Task is used to await its output.
Finally, we need a loop that takes scheduled tasks from the queue and runs them:
for runnable in receiver { runnable.run(); }
Method run() polls the task's future once. Then, the Runnable vanishes and only reappears when its Waker wakes the task, thus scheduling it to be run again.
Licensed under either of
at your option.
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.