# Rayon [![Rayon crate](https://img.shields.io/crates/v/rayon.svg)](https://crates.io/crates/rayon) [![Rayon documentation](https://docs.rs/rayon/badge.svg)](https://docs.rs/rayon) ![minimum rustc 1.36](https://img.shields.io/badge/rustc-1.36+-red.svg) [![build status](https://github.com/rayon-rs/rayon/workflows/master/badge.svg)](https://github.com/rayon-rs/rayon/actions) [![Join the chat at https://gitter.im/rayon-rs/Lobby](https://badges.gitter.im/rayon-rs/Lobby.svg)](https://gitter.im/rayon-rs/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) Rayon is a data-parallelism library for Rust. It is extremely lightweight and makes it easy to convert a sequential computation into a parallel one. It also guarantees data-race freedom. (You may also enjoy [this blog post][blog] about Rayon, which gives more background and details about how it works, or [this video][video], from the Rust Belt Rust conference.) Rayon is [available on crates.io](https://crates.io/crates/rayon), and [API Documentation is available on docs.rs](https://docs.rs/rayon/). [blog]: https://smallcultfollowing.com/babysteps/blog/2015/12/18/rayon-data-parallelism-in-rust/ [video]: https://www.youtube.com/watch?v=gof_OEv71Aw ## Parallel iterators and more Rayon makes it drop-dead simple to convert sequential iterators into parallel ones: usually, you just change your `foo.iter()` call into `foo.par_iter()`, and Rayon does the rest: ```rust use rayon::prelude::*; fn sum_of_squares(input: &[i32]) -> i32 { input.par_iter() // <-- just change that! .map(|&i| i * i) .sum() } ``` [Parallel iterators] take care of deciding how to divide your data into tasks; it will dynamically adapt for maximum performance. If you need more flexibility than that, Rayon also offers the [join] and [scope] functions, which let you create parallel tasks on your own. For even more control, you can create [custom threadpools] rather than using Rayon's default, global threadpool. [Parallel iterators]: https://docs.rs/rayon/*/rayon/iter/index.html [join]: https://docs.rs/rayon/*/rayon/fn.join.html [scope]: https://docs.rs/rayon/*/rayon/fn.scope.html [custom threadpools]: https://docs.rs/rayon/*/rayon/struct.ThreadPool.html ## No data races You may have heard that parallel execution can produce all kinds of crazy bugs. Well, rest easy. Rayon's APIs all guarantee **data-race freedom**, which generally rules out most parallel bugs (though not all). In other words, **if your code compiles**, it typically does the same thing it did before. For the most, parallel iterators in particular are guaranteed to produce the same results as their sequential counterparts. One caveat: If your iterator has side effects (for example, sending methods to other threads through a [Rust channel] or writing to disk), those side effects may occur in a different order. Note also that, in some cases, parallel iterators offer alternative versions of the sequential iterator methods that can have higher performance. [Rust channel]: https://doc.rust-lang.org/std/sync/mpsc/fn.channel.html ## Using Rayon [Rayon is available on crates.io](https://crates.io/crates/rayon). The recommended way to use it is to add a line into your Cargo.toml such as: ```toml [dependencies] rayon = "1.5" ``` To use the Parallel Iterator APIs, a number of traits have to be in scope. The easiest way to bring those things into scope is to use the [Rayon prelude](https://docs.rs/rayon/*/rayon/prelude/index.html). In each module where you would like to use the parallel iterator APIs, just add: ```rust use rayon::prelude::*; ``` Rayon currently requires `rustc 1.36.0` or greater. ## Contribution Rayon is an open source project! If you'd like to contribute to Rayon, check out [the list of "help wanted" issues](https://github.com/rayon-rs/rayon/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22). These are all (or should be) issues that are suitable for getting started, and they generally include a detailed set of instructions for what to do. Please ask questions if anything is unclear! Also, check out the [Guide to Development](https://github.com/rayon-rs/rayon/wiki/Guide-to-Development) page on the wiki. Note that all code submitted in PRs to Rayon is assumed to [be licensed under Rayon's dual MIT/Apache2 licensing](https://github.com/rayon-rs/rayon/blob/master/README.md#license). ## Quick demo To see Rayon in action, check out the `rayon-demo` directory, which includes a number of demos of code using Rayon. For example, run this command to get a visualization of an nbody simulation. To see the effect of using Rayon, press `s` to run sequentially and `p` to run in parallel. ```text > cd rayon-demo > cargo run --release -- nbody visualize ``` For more information on demos, try: ```text > cd rayon-demo > cargo run --release -- --help ``` ## Other questions? See [the Rayon FAQ][faq]. [faq]: https://github.com/rayon-rs/rayon/blob/master/FAQ.md ## License Rayon is distributed under the terms of both the MIT license and the Apache License (Version 2.0). See [LICENSE-APACHE](LICENSE-APACHE) and [LICENSE-MIT](LICENSE-MIT) for details. Opening a pull requests is assumed to signal agreement with these licensing terms.