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#![doc(html_root_url = "")]
//! Data-parallelism library that makes it easy to convert sequential
//! computations into parallel
//! Rayon is lightweight and convenient for introducing parallelism into existing
//! code. It guarantees data-race free executions and takes advantage of
//! parallelism when sensible, based on work-load at runtime.
//! # How to use Rayon
//! There are two ways to use Rayon:
//! - **High-level parallel constructs** are the simplest way to use Rayon and also
//! typically the most efficient.
//! - [Parallel iterators][iter module] make it easy to convert a sequential iterator to
//! execute in parallel.
//! - The [`ParallelIterator`] trait defines general methods for all parallel iterators.
//! - The [`IndexedParallelIterator`] trait adds methods for iterators that support random
//! access.
//! - The [`par_sort`] method sorts `&mut [T]` slices (or vectors) in parallel.
//! - [`par_extend`] can be used to efficiently grow collections with items produced
//! by a parallel iterator.
//! - **Custom tasks** let you divide your work into parallel tasks yourself.
//! - [`join`] is used to subdivide a task into two pieces.
//! - [`scope`] creates a scope within which you can create any number of parallel tasks.
//! - [`ThreadPoolBuilder`] can be used to create your own thread pools or customize
//! the global one.
//! [iter module]: iter/index.html
//! [`join`]: fn.join.html
//! [`scope`]: fn.scope.html
//! [`par_sort`]: slice/trait.ParallelSliceMut.html#method.par_sort
//! [`par_extend`]: iter/trait.ParallelExtend.html#tymethod.par_extend
//! [`ThreadPoolBuilder`]: struct.ThreadPoolBuilder.html
//! # Basic usage and the Rayon prelude
//! First, you will need to add `rayon` to your `Cargo.toml`.
//! Next, to use parallel iterators or the other high-level methods,
//! you need to import several traits. Those traits are bundled into
//! the module [`rayon::prelude`]. It is recommended that you import
//! all of these traits at once by adding `use rayon::prelude::*` at
//! the top of each module that uses Rayon methods.
//! These traits give you access to the `par_iter` method which provides
//! parallel implementations of many iterative functions such as [`map`],
//! [`for_each`], [`filter`], [`fold`], and [more].
//! [`rayon::prelude`]: prelude/index.html
//! [`map`]: iter/
//! [`for_each`]: iter/trait.ParallelIterator.html#method.for_each
//! [`filter`]: iter/trait.ParallelIterator.html#method.filter
//! [`fold`]: iter/trait.ParallelIterator.html#method.fold
//! [more]: iter/trait.ParallelIterator.html#provided-methods
//! [`ParallelIterator`]: iter/trait.ParallelIterator.html
//! [`IndexedParallelIterator`]: iter/trait.IndexedParallelIterator.html
//! # Crate Layout
//! Rayon extends many of the types found in the standard library with
//! parallel iterator implementations. The modules in the `rayon`
//! crate mirror [`std`] itself: so, e.g., the `option` module in
//! Rayon contains parallel iterators for the `Option` type, which is
//! found in [the `option` module of `std`]. Similarly, the
//! `collections` module in Rayon offers parallel iterator types for
//! [the `collections` from `std`]. You will rarely need to access
//! these submodules unless you need to name iterator types
//! explicitly.
//! [the `option` module of `std`]:
//! [the `collections` from `std`]:
//! # Other questions?
//! See [the Rayon FAQ][faq].
mod delegate;
mod private;
mod split_producer;
pub mod collections;
pub mod iter;
pub mod option;
pub mod prelude;
pub mod range;
pub mod range_inclusive;
pub mod result;
pub mod slice;
pub mod str;
pub mod string;
pub mod vec;
mod math;
mod par_either;
mod compile_fail;
pub use rayon_core::FnContext;
pub use rayon_core::ThreadBuilder;
pub use rayon_core::ThreadPool;
pub use rayon_core::ThreadPoolBuildError;
pub use rayon_core::ThreadPoolBuilder;
pub use rayon_core::{current_num_threads, current_thread_index};
pub use rayon_core::{join, join_context};
pub use rayon_core::{scope, Scope};
pub use rayon_core::{scope_fifo, ScopeFifo};
pub use rayon_core::{spawn, spawn_fifo};