Files
addr2line
adler
adler32
ahash
aho_corasick
angle
approx
backtrace
bitflags
blender
bytemuck
byteorder
case
cast_trait
cfg_if
chrono
color
color_quant
const_fn
crc32fast
crossbeam
crossbeam_channel
crossbeam_deque
crossbeam_epoch
crossbeam_queue
crossbeam_skiplist
crossbeam_utils
darling
darling_core
darling_macro
dds
deflate
densevec
derive_builder
derive_builder_core
dot
downcast_rs
dual_quat
either
erased_serde
failure
failure_derive
fixedbitset
float_cmp
fnv
freeimage
freeimage_sys
freetype
freetype_gl_sys
freetype_sys
freetypegl
futures
futures_channel
futures_core
futures_executor
futures_io
futures_macro
futures_sink
futures_task
futures_util
async_await
future
io
lock
sink
stream
task
fxhash
generational_arena
generic_array
getrandom
gif
gimli
glfw
glfw_sys
glin
glin_derive
glsl
half
harfbuzz
harfbuzz_ft_sys
harfbuzz_sys
hashbrown
human_sort
ident_case
image
indexmap
instant
itertools
itoa
jpeg_decoder
lazy_static
libc
libm
lock_api
log
lut_parser
matrixmultiply
memchr
memoffset
meshopt
miniz_oxide
monotonic_clock
mopa
mutiny_derive
na
nalgebra
base
geometry
linalg
ncollide3d
bounding_volume
interpolation
partitioning
pipeline
procedural
query
algorithms
closest_points
contact
distance
nonlinear_time_of_impact
point
proximity
ray
time_of_impact
visitors
shape
transformation
utils
nom
num_complex
num_cpus
num_integer
num_iter
num_rational
num_traits
numext_constructor
numext_fixed_uint
numext_fixed_uint_core
numext_fixed_uint_hack
object
once_cell
parking_lot
parking_lot_core
pathfinding
pennereq
petgraph
pin_project_lite
pin_utils
png
polygon2
ppv_lite86
proc_macro2
proc_macro_crate
proc_macro_hack
proc_macro_nested
quote
rand
rand_chacha
rand_core
rand_distr
raw_window_handle
rawpointer
rayon
rayon_core
rect_packer
regex
regex_syntax
retain_mut
rin
rin_app
rin_blender
rin_core
rin_gl
rin_graphics
rin_gui
rin_material
rin_math
rin_postpo
rin_scene
rin_util
rin_window
rinblender
rinecs
rinecs_derive
rinecs_derive_utils
ringui_derive
rustc_demangle
rusty_pool
ryu
scopeguard
seitan
seitan_derive
semver
semver_parser
serde
serde_derive
serde_json
shaderdata_derive
simba
slab
slice_of_array
slotmap
smallvec
std140_data
streaming_iterator
strsim
syn
synstructure
thiserror
thiserror_impl
thread_local
tiff
time
toml
typenum
unchecked_unwrap
unicode_xid
vec2
vec3
weezl
x11
zlib_sys
  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
#![doc(html_root_url = "https://docs.rs/rayon/1.5")]
#![deny(missing_debug_implementations)]
#![deny(missing_docs)]
#![deny(unreachable_pub)]
#![warn(rust_2018_idioms)]

//! 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/trait.ParallelIterator.html#method.map
//! [`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`]: https://doc.rust-lang.org/std/option/index.html
//! [the `collections` from `std`]: https://doc.rust-lang.org/std/collections/index.html
//! [`std`]: https://doc.rust-lang.org/std/
//!
//! # Other questions?
//!
//! See [the Rayon FAQ][faq].
//!
//! [faq]: https://github.com/rayon-rs/rayon/blob/master/FAQ.md

#[macro_use]
mod delegate;

#[macro_use]
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};