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# Objective Fix shields ## Solution - Correct shield in the Bevy ECS Readme, where only the MIT license is displayed ![Screenshot 2023-10-01 at 18 28 27](https://github.com/bevyengine/bevy/assets/104745335/a736a65e-0d47-4d9e-b32d-0b843a00922c) - Add shields to other Readmes. - homogenize shields and titles.
39 lines
2.4 KiB
Markdown
39 lines
2.4 KiB
Markdown
# Bevy Tasks
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[![License](https://img.shields.io/badge/license-MIT%2FApache-blue.svg)](https://github.com/bevyengine/bevy#license)
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[![Crates.io](https://img.shields.io/crates/v/bevy.svg)](https://crates.io/crates/bevy_tasks)
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[![Downloads](https://img.shields.io/crates/d/bevy_tasks.svg)](https://crates.io/crates/bevy_tasks)
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[![Docs](https://docs.rs/bevy_tasks/badge.svg)](https://docs.rs/bevy_tasks/latest/bevy_tasks/)
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[![Discord](https://img.shields.io/discord/691052431525675048.svg?label=&logo=discord&logoColor=ffffff&color=7389D8&labelColor=6A7EC2)](https://discord.gg/bevy)
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A refreshingly simple task executor for bevy. :)
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This is a simple threadpool with minimal dependencies. The main usecase is a scoped fork-join, i.e. spawning tasks from
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a single thread and having that thread await the completion of those tasks. This is intended specifically for
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[`bevy`][bevy] as a lighter alternative to [`rayon`][rayon] for this specific usecase. There are also utilities for
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generating the tasks from a slice of data. This library is intended for games and makes no attempt to ensure fairness
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or ordering of spawned tasks.
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It is based on [`async-executor`][async-executor], a lightweight executor that allows the end user to manage their own threads.
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`async-executor` is based on async-task, a core piece of async-std.
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## Usage
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In order to be able to optimize task execution in multi-threaded environments,
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bevy provides three different thread pools via which tasks of different kinds can be spawned.
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(The same API is used in single-threaded environments, even if execution is limited to a single thread.
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This currently applies to WASM targets.)
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The determining factor for what kind of work should go in each pool is latency requirements:
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* For CPU-intensive work (tasks that generally spin until completion) we have a standard
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[`ComputeTaskPool`] and an [`AsyncComputeTaskPool`]. Work that does not need to be completed to
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present the next frame should go to the [`AsyncComputeTaskPool`].
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* For IO-intensive work (tasks that spend very little time in a "woken" state) we have an
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[`IoTaskPool`] whose tasks are expected to complete very quickly. Generally speaking, they should just
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await receiving data from somewhere (i.e. disk) and signal other systems when the data is ready
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for consumption. (likely via channels)
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[bevy]: https://bevyengine.org
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[rayon]: https://github.com/rayon-rs/rayon
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[async-executor]: https://github.com/stjepang/async-executor
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