bevy/crates/bevy_tasks
Al M 52e3f2007b
Add "all-features = true" to docs.rs metadata for most crates (#12366)
# Objective

Fix missing `TextBundle` (and many others) which are present in the main
crate as default features but optional in the sub-crate. See:

- https://docs.rs/bevy/0.13.0/bevy/ui/node_bundles/index.html
- https://docs.rs/bevy_ui/0.13.0/bevy_ui/node_bundles/index.html

~~There are probably other instances in other crates that I could track
down, but maybe "all-features = true" should be used by default in all
sub-crates? Not sure.~~ (There were many.) I only noticed this because
rust-analyzer's "open docs" features takes me to the sub-crate, not the
main one.

## Solution

Add "all-features = true" to docs.rs metadata for crates that use
features.

## Changelog

### Changed

- Unified features documented on docs.rs between main crate and
sub-crates
2024-03-08 20:03:09 +00:00
..
examples Inverse missing_docs logic (#11676) 2024-02-03 21:40:55 +00:00
src Add "all-features = true" to docs.rs metadata for most crates (#12366) 2024-03-08 20:03:09 +00:00
Cargo.toml Add "all-features = true" to docs.rs metadata for most crates (#12366) 2024-03-08 20:03:09 +00:00
README.md add and fix shields in Readmes (#9993) 2023-10-15 00:52:31 +00:00

Bevy Tasks

License Crates.io Downloads Docs Discord

A refreshingly simple task executor for bevy. :)

This is a simple threadpool with minimal dependencies. The main usecase is a scoped fork-join, i.e. spawning tasks from a single thread and having that thread await the completion of those tasks. This is intended specifically for bevy as a lighter alternative to rayon for this specific usecase. There are also utilities for generating the tasks from a slice of data. This library is intended for games and makes no attempt to ensure fairness or ordering of spawned tasks.

It is based on async-executor, a lightweight executor that allows the end user to manage their own threads. async-executor is based on async-task, a core piece of async-std.

Usage

In order to be able to optimize task execution in multi-threaded environments, bevy provides three different thread pools via which tasks of different kinds can be spawned. (The same API is used in single-threaded environments, even if execution is limited to a single thread. This currently applies to WASM targets.) The determining factor for what kind of work should go in each pool is latency requirements:

  • For CPU-intensive work (tasks that generally spin until completion) we have a standard [ComputeTaskPool] and an [AsyncComputeTaskPool]. Work that does not need to be completed to present the next frame should go to the [AsyncComputeTaskPool].

  • For IO-intensive work (tasks that spend very little time in a "woken" state) we have an [IoTaskPool] whose tasks are expected to complete very quickly. Generally speaking, they should just await receiving data from somewhere (i.e. disk) and signal other systems when the data is ready for consumption. (likely via channels)