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diff --git a/vendor/rayon/src/iter/mod.rs b/vendor/rayon/src/iter/mod.rs new file mode 100644 index 0000000..7b5a29a --- /dev/null +++ b/vendor/rayon/src/iter/mod.rs @@ -0,0 +1,3531 @@ +//! Traits for writing parallel programs using an iterator-style interface +//! +//! You will rarely need to interact with this module directly unless you have +//! need to name one of the iterator types. +//! +//! Parallel iterators make it easy to write iterator-like chains that +//! execute in parallel: typically all you have to do is convert the +//! first `.iter()` (or `iter_mut()`, `into_iter()`, etc) method into +//! `par_iter()` (or `par_iter_mut()`, `into_par_iter()`, etc). For +//! example, to compute the sum of the squares of a sequence of +//! integers, one might write: +//! +//! ```rust +//! use rayon::prelude::*; +//! fn sum_of_squares(input: &[i32]) -> i32 { +//! input.par_iter() +//! .map(|i| i * i) +//! .sum() +//! } +//! ``` +//! +//! Or, to increment all the integers in a slice, you could write: +//! +//! ```rust +//! use rayon::prelude::*; +//! fn increment_all(input: &mut [i32]) { +//! input.par_iter_mut() +//! .for_each(|p| *p += 1); +//! } +//! ``` +//! +//! To use parallel iterators, first import the traits by adding +//! something like `use rayon::prelude::*` to your module. You can +//! then call `par_iter`, `par_iter_mut`, or `into_par_iter` to get a +//! parallel iterator. Like a [regular iterator][], parallel +//! iterators work by first constructing a computation and then +//! executing it. +//! +//! In addition to `par_iter()` and friends, some types offer other +//! ways to create (or consume) parallel iterators: +//! +//! - Slices (`&[T]`, `&mut [T]`) offer methods like `par_split` and +//! `par_windows`, as well as various parallel sorting +//! operations. See [the `ParallelSlice` trait] for the full list. +//! - Strings (`&str`) offer methods like `par_split` and `par_lines`. +//! See [the `ParallelString` trait] for the full list. +//! - Various collections offer [`par_extend`], which grows a +//! collection given a parallel iterator. (If you don't have a +//! collection to extend, you can use [`collect()`] to create a new +//! one from scratch.) +//! +//! [the `ParallelSlice` trait]: ../slice/trait.ParallelSlice.html +//! [the `ParallelString` trait]: ../str/trait.ParallelString.html +//! [`par_extend`]: trait.ParallelExtend.html +//! [`collect()`]: trait.ParallelIterator.html#method.collect +//! +//! To see the full range of methods available on parallel iterators, +//! check out the [`ParallelIterator`] and [`IndexedParallelIterator`] +//! traits. +//! +//! If you'd like to build a custom parallel iterator, or to write your own +//! combinator, then check out the [split] function and the [plumbing] module. +//! +//! [regular iterator]: https://doc.rust-lang.org/std/iter/trait.Iterator.html +//! [`ParallelIterator`]: trait.ParallelIterator.html +//! [`IndexedParallelIterator`]: trait.IndexedParallelIterator.html +//! [split]: fn.split.html +//! [plumbing]: plumbing/index.html +//! +//! Note: Several of the `ParallelIterator` methods rely on a `Try` trait which +//! has been deliberately obscured from the public API. This trait is intended +//! to mirror the unstable `std::ops::Try` with implementations for `Option` and +//! `Result`, where `Some`/`Ok` values will let those iterators continue, but +//! `None`/`Err` values will exit early. +//! +//! A note about object safety: It is currently _not_ possible to wrap +//! a `ParallelIterator` (or any trait that depends on it) using a +//! `Box<dyn ParallelIterator>` or other kind of dynamic allocation, +//! because `ParallelIterator` is **not object-safe**. +//! (This keeps the implementation simpler and allows extra optimizations.) + +use self::plumbing::*; +use self::private::Try; +pub use either::Either; +use std::cmp::{self, Ordering}; +use std::iter::{Product, Sum}; +use std::ops::{Fn, RangeBounds}; + +pub mod plumbing; + +#[cfg(test)] +mod test; + +// There is a method to the madness here: +// +// - These modules are private but expose certain types to the end-user +// (e.g., `enumerate::Enumerate`) -- specifically, the types that appear in the +// public API surface of the `ParallelIterator` traits. +// - In **this** module, those public types are always used unprefixed, which forces +// us to add a `pub use` and helps identify if we missed anything. +// - In contrast, items that appear **only** in the body of a method, +// e.g. `find::find()`, are always used **prefixed**, so that they +// can be readily distinguished. + +mod chain; +mod chunks; +mod cloned; +mod collect; +mod copied; +mod empty; +mod enumerate; +mod extend; +mod filter; +mod filter_map; +mod find; +mod find_first_last; +mod flat_map; +mod flat_map_iter; +mod flatten; +mod flatten_iter; +mod fold; +mod fold_chunks; +mod fold_chunks_with; +mod for_each; +mod from_par_iter; +mod inspect; +mod interleave; +mod interleave_shortest; +mod intersperse; +mod len; +mod map; +mod map_with; +mod multizip; +mod noop; +mod once; +mod panic_fuse; +mod par_bridge; +mod positions; +mod product; +mod reduce; +mod repeat; +mod rev; +mod skip; +mod skip_any; +mod skip_any_while; +mod splitter; +mod step_by; +mod sum; +mod take; +mod take_any; +mod take_any_while; +mod try_fold; +mod try_reduce; +mod try_reduce_with; +mod unzip; +mod update; +mod while_some; +mod zip; +mod zip_eq; + +pub use self::{ + chain::Chain, + chunks::Chunks, + cloned::Cloned, + copied::Copied, + empty::{empty, Empty}, + enumerate::Enumerate, + filter::Filter, + filter_map::FilterMap, + flat_map::FlatMap, + flat_map_iter::FlatMapIter, + flatten::Flatten, + flatten_iter::FlattenIter, + fold::{Fold, FoldWith}, + fold_chunks::FoldChunks, + fold_chunks_with::FoldChunksWith, + inspect::Inspect, + interleave::Interleave, + interleave_shortest::InterleaveShortest, + intersperse::Intersperse, + len::{MaxLen, MinLen}, + map::Map, + map_with::{MapInit, MapWith}, + multizip::MultiZip, + once::{once, Once}, + panic_fuse::PanicFuse, + par_bridge::{IterBridge, ParallelBridge}, + positions::Positions, + repeat::{repeat, repeatn, Repeat, RepeatN}, + rev::Rev, + skip::Skip, + skip_any::SkipAny, + skip_any_while::SkipAnyWhile, + splitter::{split, Split}, + step_by::StepBy, + take::Take, + take_any::TakeAny, + take_any_while::TakeAnyWhile, + try_fold::{TryFold, TryFoldWith}, + update::Update, + while_some::WhileSome, + zip::Zip, + zip_eq::ZipEq, +}; + +/// `IntoParallelIterator` implements the conversion to a [`ParallelIterator`]. +/// +/// By implementing `IntoParallelIterator` for a type, you define how it will +/// transformed into an iterator. This is a parallel version of the standard +/// library's [`std::iter::IntoIterator`] trait. +/// +/// [`ParallelIterator`]: trait.ParallelIterator.html +/// [`std::iter::IntoIterator`]: https://doc.rust-lang.org/std/iter/trait.IntoIterator.html +pub trait IntoParallelIterator { + /// The parallel iterator type that will be created. + type Iter: ParallelIterator<Item = Self::Item>; + + /// The type of item that the parallel iterator will produce. + type Item: Send; + + /// Converts `self` into a parallel iterator. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// println!("counting in parallel:"); + /// (0..100).into_par_iter() + /// .for_each(|i| println!("{}", i)); + /// ``` + /// + /// This conversion is often implicit for arguments to methods like [`zip`]. + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let v: Vec<_> = (0..5).into_par_iter().zip(5..10).collect(); + /// assert_eq!(v, [(0, 5), (1, 6), (2, 7), (3, 8), (4, 9)]); + /// ``` + /// + /// [`zip`]: trait.IndexedParallelIterator.html#method.zip + fn into_par_iter(self) -> Self::Iter; +} + +/// `IntoParallelRefIterator` implements the conversion to a +/// [`ParallelIterator`], providing shared references to the data. +/// +/// This is a parallel version of the `iter()` method +/// defined by various collections. +/// +/// This trait is automatically implemented +/// `for I where &I: IntoParallelIterator`. In most cases, users +/// will want to implement [`IntoParallelIterator`] rather than implement +/// this trait directly. +/// +/// [`ParallelIterator`]: trait.ParallelIterator.html +/// [`IntoParallelIterator`]: trait.IntoParallelIterator.html +pub trait IntoParallelRefIterator<'data> { + /// The type of the parallel iterator that will be returned. + type Iter: ParallelIterator<Item = Self::Item>; + + /// The type of item that the parallel iterator will produce. + /// This will typically be an `&'data T` reference type. + type Item: Send + 'data; + + /// Converts `self` into a parallel iterator. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let v: Vec<_> = (0..100).collect(); + /// assert_eq!(v.par_iter().sum::<i32>(), 100 * 99 / 2); + /// + /// // `v.par_iter()` is shorthand for `(&v).into_par_iter()`, + /// // producing the exact same references. + /// assert!(v.par_iter().zip(&v) + /// .all(|(a, b)| std::ptr::eq(a, b))); + /// ``` + fn par_iter(&'data self) -> Self::Iter; +} + +impl<'data, I: 'data + ?Sized> IntoParallelRefIterator<'data> for I +where + &'data I: IntoParallelIterator, +{ + type Iter = <&'data I as IntoParallelIterator>::Iter; + type Item = <&'data I as IntoParallelIterator>::Item; + + fn par_iter(&'data self) -> Self::Iter { + self.into_par_iter() + } +} + +/// `IntoParallelRefMutIterator` implements the conversion to a +/// [`ParallelIterator`], providing mutable references to the data. +/// +/// This is a parallel version of the `iter_mut()` method +/// defined by various collections. +/// +/// This trait is automatically implemented +/// `for I where &mut I: IntoParallelIterator`. In most cases, users +/// will want to implement [`IntoParallelIterator`] rather than implement +/// this trait directly. +/// +/// [`ParallelIterator`]: trait.ParallelIterator.html +/// [`IntoParallelIterator`]: trait.IntoParallelIterator.html +pub trait IntoParallelRefMutIterator<'data> { + /// The type of iterator that will be created. + type Iter: ParallelIterator<Item = Self::Item>; + + /// The type of item that will be produced; this is typically an + /// `&'data mut T` reference. + type Item: Send + 'data; + + /// Creates the parallel iterator from `self`. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let mut v = vec![0usize; 5]; + /// v.par_iter_mut().enumerate().for_each(|(i, x)| *x = i); + /// assert_eq!(v, [0, 1, 2, 3, 4]); + /// ``` + fn par_iter_mut(&'data mut self) -> Self::Iter; +} + +impl<'data, I: 'data + ?Sized> IntoParallelRefMutIterator<'data> for I +where + &'data mut I: IntoParallelIterator, +{ + type Iter = <&'data mut I as IntoParallelIterator>::Iter; + type Item = <&'data mut I as IntoParallelIterator>::Item; + + fn par_iter_mut(&'data mut self) -> Self::Iter { + self.into_par_iter() + } +} + +/// Parallel version of the standard iterator trait. +/// +/// The combinators on this trait are available on **all** parallel +/// iterators. Additional methods can be found on the +/// [`IndexedParallelIterator`] trait: those methods are only +/// available for parallel iterators where the number of items is +/// known in advance (so, e.g., after invoking `filter`, those methods +/// become unavailable). +/// +/// For examples of using parallel iterators, see [the docs on the +/// `iter` module][iter]. +/// +/// [iter]: index.html +/// [`IndexedParallelIterator`]: trait.IndexedParallelIterator.html +pub trait ParallelIterator: Sized + Send { + /// The type of item that this parallel iterator produces. + /// For example, if you use the [`for_each`] method, this is the type of + /// item that your closure will be invoked with. + /// + /// [`for_each`]: #method.for_each + type Item: Send; + + /// Executes `OP` on each item produced by the iterator, in parallel. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// (0..100).into_par_iter().for_each(|x| println!("{:?}", x)); + /// ``` + fn for_each<OP>(self, op: OP) + where + OP: Fn(Self::Item) + Sync + Send, + { + for_each::for_each(self, &op) + } + + /// Executes `OP` on the given `init` value with each item produced by + /// the iterator, in parallel. + /// + /// The `init` value will be cloned only as needed to be paired with + /// the group of items in each rayon job. It does not require the type + /// to be `Sync`. + /// + /// # Examples + /// + /// ``` + /// use std::sync::mpsc::channel; + /// use rayon::prelude::*; + /// + /// let (sender, receiver) = channel(); + /// + /// (0..5).into_par_iter().for_each_with(sender, |s, x| s.send(x).unwrap()); + /// + /// let mut res: Vec<_> = receiver.iter().collect(); + /// + /// res.sort(); + /// + /// assert_eq!(&res[..], &[0, 1, 2, 3, 4]) + /// ``` + fn for_each_with<OP, T>(self, init: T, op: OP) + where + OP: Fn(&mut T, Self::Item) + Sync + Send, + T: Send + Clone, + { + self.map_with(init, op).collect() + } + + /// Executes `OP` on a value returned by `init` with each item produced by + /// the iterator, in parallel. + /// + /// The `init` function will be called only as needed for a value to be + /// paired with the group of items in each rayon job. There is no + /// constraint on that returned type at all! + /// + /// # Examples + /// + /// ``` + /// use rand::Rng; + /// use rayon::prelude::*; + /// + /// let mut v = vec![0u8; 1_000_000]; + /// + /// v.par_chunks_mut(1000) + /// .for_each_init( + /// || rand::thread_rng(), + /// |rng, chunk| rng.fill(chunk), + /// ); + /// + /// // There's a remote chance that this will fail... + /// for i in 0u8..=255 { + /// assert!(v.contains(&i)); + /// } + /// ``` + fn for_each_init<OP, INIT, T>(self, init: INIT, op: OP) + where + OP: Fn(&mut T, Self::Item) + Sync + Send, + INIT: Fn() -> T + Sync + Send, + { + self.map_init(init, op).collect() + } + + /// Executes a fallible `OP` on each item produced by the iterator, in parallel. + /// + /// If the `OP` returns `Result::Err` or `Option::None`, we will attempt to + /// stop processing the rest of the items in the iterator as soon as + /// possible, and we will return that terminating value. Otherwise, we will + /// return an empty `Result::Ok(())` or `Option::Some(())`. If there are + /// multiple errors in parallel, it is not specified which will be returned. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// use std::io::{self, Write}; + /// + /// // This will stop iteration early if there's any write error, like + /// // having piped output get closed on the other end. + /// (0..100).into_par_iter() + /// .try_for_each(|x| writeln!(io::stdout(), "{:?}", x)) + /// .expect("expected no write errors"); + /// ``` + fn try_for_each<OP, R>(self, op: OP) -> R + where + OP: Fn(Self::Item) -> R + Sync + Send, + R: Try<Output = ()> + Send, + { + fn ok<R: Try<Output = ()>>(_: (), _: ()) -> R { + R::from_output(()) + } + + self.map(op).try_reduce(<()>::default, ok) + } + + /// Executes a fallible `OP` on the given `init` value with each item + /// produced by the iterator, in parallel. + /// + /// This combines the `init` semantics of [`for_each_with()`] and the + /// failure semantics of [`try_for_each()`]. + /// + /// [`for_each_with()`]: #method.for_each_with + /// [`try_for_each()`]: #method.try_for_each + /// + /// # Examples + /// + /// ``` + /// use std::sync::mpsc::channel; + /// use rayon::prelude::*; + /// + /// let (sender, receiver) = channel(); + /// + /// (0..5).into_par_iter() + /// .try_for_each_with(sender, |s, x| s.send(x)) + /// .expect("expected no send errors"); + /// + /// let mut res: Vec<_> = receiver.iter().collect(); + /// + /// res.sort(); + /// + /// assert_eq!(&res[..], &[0, 1, 2, 3, 4]) + /// ``` + fn try_for_each_with<OP, T, R>(self, init: T, op: OP) -> R + where + OP: Fn(&mut T, Self::Item) -> R + Sync + Send, + T: Send + Clone, + R: Try<Output = ()> + Send, + { + fn ok<R: Try<Output = ()>>(_: (), _: ()) -> R { + R::from_output(()) + } + + self.map_with(init, op).try_reduce(<()>::default, ok) + } + + /// Executes a fallible `OP` on a value returned by `init` with each item + /// produced by the iterator, in parallel. + /// + /// This combines the `init` semantics of [`for_each_init()`] and the + /// failure semantics of [`try_for_each()`]. + /// + /// [`for_each_init()`]: #method.for_each_init + /// [`try_for_each()`]: #method.try_for_each + /// + /// # Examples + /// + /// ``` + /// use rand::Rng; + /// use rayon::prelude::*; + /// + /// let mut v = vec![0u8; 1_000_000]; + /// + /// v.par_chunks_mut(1000) + /// .try_for_each_init( + /// || rand::thread_rng(), + /// |rng, chunk| rng.try_fill(chunk), + /// ) + /// .expect("expected no rand errors"); + /// + /// // There's a remote chance that this will fail... + /// for i in 0u8..=255 { + /// assert!(v.contains(&i)); + /// } + /// ``` + fn try_for_each_init<OP, INIT, T, R>(self, init: INIT, op: OP) -> R + where + OP: Fn(&mut T, Self::Item) -> R + Sync + Send, + INIT: Fn() -> T + Sync + Send, + R: Try<Output = ()> + Send, + { + fn ok<R: Try<Output = ()>>(_: (), _: ()) -> R { + R::from_output(()) + } + + self.map_init(init, op).try_reduce(<()>::default, ok) + } + + /// Counts the number of items in this parallel iterator. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let count = (0..100).into_par_iter().count(); + /// + /// assert_eq!(count, 100); + /// ``` + fn count(self) -> usize { + fn one<T>(_: T) -> usize { + 1 + } + + self.map(one).sum() + } + + /// Applies `map_op` to each item of this iterator, producing a new + /// iterator with the results. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let mut par_iter = (0..5).into_par_iter().map(|x| x * 2); + /// + /// let doubles: Vec<_> = par_iter.collect(); + /// + /// assert_eq!(&doubles[..], &[0, 2, 4, 6, 8]); + /// ``` + fn map<F, R>(self, map_op: F) -> Map<Self, F> + where + F: Fn(Self::Item) -> R + Sync + Send, + R: Send, + { + Map::new(self, map_op) + } + + /// Applies `map_op` to the given `init` value with each item of this + /// iterator, producing a new iterator with the results. + /// + /// The `init` value will be cloned only as needed to be paired with + /// the group of items in each rayon job. It does not require the type + /// to be `Sync`. + /// + /// # Examples + /// + /// ``` + /// use std::sync::mpsc::channel; + /// use rayon::prelude::*; + /// + /// let (sender, receiver) = channel(); + /// + /// let a: Vec<_> = (0..5) + /// .into_par_iter() // iterating over i32 + /// .map_with(sender, |s, x| { + /// s.send(x).unwrap(); // sending i32 values through the channel + /// x // returning i32 + /// }) + /// .collect(); // collecting the returned values into a vector + /// + /// let mut b: Vec<_> = receiver.iter() // iterating over the values in the channel + /// .collect(); // and collecting them + /// b.sort(); + /// + /// assert_eq!(a, b); + /// ``` + fn map_with<F, T, R>(self, init: T, map_op: F) -> MapWith<Self, T, F> + where + F: Fn(&mut T, Self::Item) -> R + Sync + Send, + T: Send + Clone, + R: Send, + { + MapWith::new(self, init, map_op) + } + + /// Applies `map_op` to a value returned by `init` with each item of this + /// iterator, producing a new iterator with the results. + /// + /// The `init` function will be called only as needed for a value to be + /// paired with the group of items in each rayon job. There is no + /// constraint on that returned type at all! + /// + /// # Examples + /// + /// ``` + /// use rand::Rng; + /// use rayon::prelude::*; + /// + /// let a: Vec<_> = (1i32..1_000_000) + /// .into_par_iter() + /// .map_init( + /// || rand::thread_rng(), // get the thread-local RNG + /// |rng, x| if rng.gen() { // randomly negate items + /// -x + /// } else { + /// x + /// }, + /// ).collect(); + /// + /// // There's a remote chance that this will fail... + /// assert!(a.iter().any(|&x| x < 0)); + /// assert!(a.iter().any(|&x| x > 0)); + /// ``` + fn map_init<F, INIT, T, R>(self, init: INIT, map_op: F) -> MapInit<Self, INIT, F> + where + F: Fn(&mut T, Self::Item) -> R + Sync + Send, + INIT: Fn() -> T + Sync + Send, + R: Send, + { + MapInit::new(self, init, map_op) + } + + /// Creates an iterator which clones all of its elements. This may be + /// useful when you have an iterator over `&T`, but you need `T`, and + /// that type implements `Clone`. See also [`copied()`]. + /// + /// [`copied()`]: #method.copied + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [1, 2, 3]; + /// + /// let v_cloned: Vec<_> = a.par_iter().cloned().collect(); + /// + /// // cloned is the same as .map(|&x| x), for integers + /// let v_map: Vec<_> = a.par_iter().map(|&x| x).collect(); + /// + /// assert_eq!(v_cloned, vec![1, 2, 3]); + /// assert_eq!(v_map, vec![1, 2, 3]); + /// ``` + fn cloned<'a, T>(self) -> Cloned<Self> + where + T: 'a + Clone + Send, + Self: ParallelIterator<Item = &'a T>, + { + Cloned::new(self) + } + + /// Creates an iterator which copies all of its elements. This may be + /// useful when you have an iterator over `&T`, but you need `T`, and + /// that type implements `Copy`. See also [`cloned()`]. + /// + /// [`cloned()`]: #method.cloned + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [1, 2, 3]; + /// + /// let v_copied: Vec<_> = a.par_iter().copied().collect(); + /// + /// // copied is the same as .map(|&x| x), for integers + /// let v_map: Vec<_> = a.par_iter().map(|&x| x).collect(); + /// + /// assert_eq!(v_copied, vec![1, 2, 3]); + /// assert_eq!(v_map, vec![1, 2, 3]); + /// ``` + fn copied<'a, T>(self) -> Copied<Self> + where + T: 'a + Copy + Send, + Self: ParallelIterator<Item = &'a T>, + { + Copied::new(self) + } + + /// Applies `inspect_op` to a reference to each item of this iterator, + /// producing a new iterator passing through the original items. This is + /// often useful for debugging to see what's happening in iterator stages. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [1, 4, 2, 3]; + /// + /// // this iterator sequence is complex. + /// let sum = a.par_iter() + /// .cloned() + /// .filter(|&x| x % 2 == 0) + /// .reduce(|| 0, |sum, i| sum + i); + /// + /// println!("{}", sum); + /// + /// // let's add some inspect() calls to investigate what's happening + /// let sum = a.par_iter() + /// .cloned() + /// .inspect(|x| println!("about to filter: {}", x)) + /// .filter(|&x| x % 2 == 0) + /// .inspect(|x| println!("made it through filter: {}", x)) + /// .reduce(|| 0, |sum, i| sum + i); + /// + /// println!("{}", sum); + /// ``` + fn inspect<OP>(self, inspect_op: OP) -> Inspect<Self, OP> + where + OP: Fn(&Self::Item) + Sync + Send, + { + Inspect::new(self, inspect_op) + } + + /// Mutates each item of this iterator before yielding it. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let par_iter = (0..5).into_par_iter().update(|x| {*x *= 2;}); + /// + /// let doubles: Vec<_> = par_iter.collect(); + /// + /// assert_eq!(&doubles[..], &[0, 2, 4, 6, 8]); + /// ``` + fn update<F>(self, update_op: F) -> Update<Self, F> + where + F: Fn(&mut Self::Item) + Sync + Send, + { + Update::new(self, update_op) + } + + /// Applies `filter_op` to each item of this iterator, producing a new + /// iterator with only the items that gave `true` results. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let mut par_iter = (0..10).into_par_iter().filter(|x| x % 2 == 0); + /// + /// let even_numbers: Vec<_> = par_iter.collect(); + /// + /// assert_eq!(&even_numbers[..], &[0, 2, 4, 6, 8]); + /// ``` + fn filter<P>(self, filter_op: P) -> Filter<Self, P> + where + P: Fn(&Self::Item) -> bool + Sync + Send, + { + Filter::new(self, filter_op) + } + + /// Applies `filter_op` to each item of this iterator to get an `Option`, + /// producing a new iterator with only the items from `Some` results. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let mut par_iter = (0..10).into_par_iter() + /// .filter_map(|x| { + /// if x % 2 == 0 { Some(x * 3) } + /// else { None } + /// }); + /// + /// let even_numbers: Vec<_> = par_iter.collect(); + /// + /// assert_eq!(&even_numbers[..], &[0, 6, 12, 18, 24]); + /// ``` + fn filter_map<P, R>(self, filter_op: P) -> FilterMap<Self, P> + where + P: Fn(Self::Item) -> Option<R> + Sync + Send, + R: Send, + { + FilterMap::new(self, filter_op) + } + + /// Applies `map_op` to each item of this iterator to get nested parallel iterators, + /// producing a new parallel iterator that flattens these back into one. + /// + /// See also [`flat_map_iter`](#method.flat_map_iter). + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [[1, 2], [3, 4], [5, 6], [7, 8]]; + /// + /// let par_iter = a.par_iter().cloned().flat_map(|a| a.to_vec()); + /// + /// let vec: Vec<_> = par_iter.collect(); + /// + /// assert_eq!(&vec[..], &[1, 2, 3, 4, 5, 6, 7, 8]); + /// ``` + fn flat_map<F, PI>(self, map_op: F) -> FlatMap<Self, F> + where + F: Fn(Self::Item) -> PI + Sync + Send, + PI: IntoParallelIterator, + { + FlatMap::new(self, map_op) + } + + /// Applies `map_op` to each item of this iterator to get nested serial iterators, + /// producing a new parallel iterator that flattens these back into one. + /// + /// # `flat_map_iter` versus `flat_map` + /// + /// These two methods are similar but behave slightly differently. With [`flat_map`], + /// each of the nested iterators must be a parallel iterator, and they will be further + /// split up with nested parallelism. With `flat_map_iter`, each nested iterator is a + /// sequential `Iterator`, and we only parallelize _between_ them, while the items + /// produced by each nested iterator are processed sequentially. + /// + /// When choosing between these methods, consider whether nested parallelism suits the + /// potential iterators at hand. If there's little computation involved, or its length + /// is much less than the outer parallel iterator, then it may perform better to avoid + /// the overhead of parallelism, just flattening sequentially with `flat_map_iter`. + /// If there is a lot of computation, potentially outweighing the outer parallel + /// iterator, then the nested parallelism of `flat_map` may be worthwhile. + /// + /// [`flat_map`]: #method.flat_map + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// use std::cell::RefCell; + /// + /// let a = [[1, 2], [3, 4], [5, 6], [7, 8]]; + /// + /// let par_iter = a.par_iter().flat_map_iter(|a| { + /// // The serial iterator doesn't have to be thread-safe, just its items. + /// let cell_iter = RefCell::new(a.iter().cloned()); + /// std::iter::from_fn(move || cell_iter.borrow_mut().next()) + /// }); + /// + /// let vec: Vec<_> = par_iter.collect(); + /// + /// assert_eq!(&vec[..], &[1, 2, 3, 4, 5, 6, 7, 8]); + /// ``` + fn flat_map_iter<F, SI>(self, map_op: F) -> FlatMapIter<Self, F> + where + F: Fn(Self::Item) -> SI + Sync + Send, + SI: IntoIterator, + SI::Item: Send, + { + FlatMapIter::new(self, map_op) + } + + /// An adaptor that flattens parallel-iterable `Item`s into one large iterator. + /// + /// See also [`flatten_iter`](#method.flatten_iter). + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let x: Vec<Vec<_>> = vec![vec![1, 2], vec![3, 4]]; + /// let y: Vec<_> = x.into_par_iter().flatten().collect(); + /// + /// assert_eq!(y, vec![1, 2, 3, 4]); + /// ``` + fn flatten(self) -> Flatten<Self> + where + Self::Item: IntoParallelIterator, + { + Flatten::new(self) + } + + /// An adaptor that flattens serial-iterable `Item`s into one large iterator. + /// + /// See also [`flatten`](#method.flatten) and the analogous comparison of + /// [`flat_map_iter` versus `flat_map`](#flat_map_iter-versus-flat_map). + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let x: Vec<Vec<_>> = vec![vec![1, 2], vec![3, 4]]; + /// let iters: Vec<_> = x.into_iter().map(Vec::into_iter).collect(); + /// let y: Vec<_> = iters.into_par_iter().flatten_iter().collect(); + /// + /// assert_eq!(y, vec![1, 2, 3, 4]); + /// ``` + fn flatten_iter(self) -> FlattenIter<Self> + where + Self::Item: IntoIterator, + <Self::Item as IntoIterator>::Item: Send, + { + FlattenIter::new(self) + } + + /// Reduces the items in the iterator into one item using `op`. + /// The argument `identity` should be a closure that can produce + /// "identity" value which may be inserted into the sequence as + /// needed to create opportunities for parallel execution. So, for + /// example, if you are doing a summation, then `identity()` ought + /// to produce something that represents the zero for your type + /// (but consider just calling `sum()` in that case). + /// + /// # Examples + /// + /// ``` + /// // Iterate over a sequence of pairs `(x0, y0), ..., (xN, yN)` + /// // and use reduce to compute one pair `(x0 + ... + xN, y0 + ... + yN)` + /// // where the first/second elements are summed separately. + /// use rayon::prelude::*; + /// let sums = [(0, 1), (5, 6), (16, 2), (8, 9)] + /// .par_iter() // iterating over &(i32, i32) + /// .cloned() // iterating over (i32, i32) + /// .reduce(|| (0, 0), // the "identity" is 0 in both columns + /// |a, b| (a.0 + b.0, a.1 + b.1)); + /// assert_eq!(sums, (0 + 5 + 16 + 8, 1 + 6 + 2 + 9)); + /// ``` + /// + /// **Note:** unlike a sequential `fold` operation, the order in + /// which `op` will be applied to reduce the result is not fully + /// specified. So `op` should be [associative] or else the results + /// will be non-deterministic. And of course `identity()` should + /// produce a true identity. + /// + /// [associative]: https://en.wikipedia.org/wiki/Associative_property + fn reduce<OP, ID>(self, identity: ID, op: OP) -> Self::Item + where + OP: Fn(Self::Item, Self::Item) -> Self::Item + Sync + Send, + ID: Fn() -> Self::Item + Sync + Send, + { + reduce::reduce(self, identity, op) + } + + /// Reduces the items in the iterator into one item using `op`. + /// If the iterator is empty, `None` is returned; otherwise, + /// `Some` is returned. + /// + /// This version of `reduce` is simple but somewhat less + /// efficient. If possible, it is better to call `reduce()`, which + /// requires an identity element. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// let sums = [(0, 1), (5, 6), (16, 2), (8, 9)] + /// .par_iter() // iterating over &(i32, i32) + /// .cloned() // iterating over (i32, i32) + /// .reduce_with(|a, b| (a.0 + b.0, a.1 + b.1)) + /// .unwrap(); + /// assert_eq!(sums, (0 + 5 + 16 + 8, 1 + 6 + 2 + 9)); + /// ``` + /// + /// **Note:** unlike a sequential `fold` operation, the order in + /// which `op` will be applied to reduce the result is not fully + /// specified. So `op` should be [associative] or else the results + /// will be non-deterministic. + /// + /// [associative]: https://en.wikipedia.org/wiki/Associative_property + fn reduce_with<OP>(self, op: OP) -> Option<Self::Item> + where + OP: Fn(Self::Item, Self::Item) -> Self::Item + Sync + Send, + { + fn opt_fold<T>(op: impl Fn(T, T) -> T) -> impl Fn(Option<T>, T) -> Option<T> { + move |opt_a, b| match opt_a { + Some(a) => Some(op(a, b)), + None => Some(b), + } + } + + fn opt_reduce<T>(op: impl Fn(T, T) -> T) -> impl Fn(Option<T>, Option<T>) -> Option<T> { + move |opt_a, opt_b| match (opt_a, opt_b) { + (Some(a), Some(b)) => Some(op(a, b)), + (Some(v), None) | (None, Some(v)) => Some(v), + (None, None) => None, + } + } + + self.fold(<_>::default, opt_fold(&op)) + .reduce(<_>::default, opt_reduce(&op)) + } + + /// Reduces the items in the iterator into one item using a fallible `op`. + /// The `identity` argument is used the same way as in [`reduce()`]. + /// + /// [`reduce()`]: #method.reduce + /// + /// If a `Result::Err` or `Option::None` item is found, or if `op` reduces + /// to one, we will attempt to stop processing the rest of the items in the + /// iterator as soon as possible, and we will return that terminating value. + /// Otherwise, we will return the final reduced `Result::Ok(T)` or + /// `Option::Some(T)`. If there are multiple errors in parallel, it is not + /// specified which will be returned. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// // Compute the sum of squares, being careful about overflow. + /// fn sum_squares<I: IntoParallelIterator<Item = i32>>(iter: I) -> Option<i32> { + /// iter.into_par_iter() + /// .map(|i| i.checked_mul(i)) // square each item, + /// .try_reduce(|| 0, i32::checked_add) // and add them up! + /// } + /// assert_eq!(sum_squares(0..5), Some(0 + 1 + 4 + 9 + 16)); + /// + /// // The sum might overflow + /// assert_eq!(sum_squares(0..10_000), None); + /// + /// // Or the squares might overflow before it even reaches `try_reduce` + /// assert_eq!(sum_squares(1_000_000..1_000_001), None); + /// ``` + fn try_reduce<T, OP, ID>(self, identity: ID, op: OP) -> Self::Item + where + OP: Fn(T, T) -> Self::Item + Sync + Send, + ID: Fn() -> T + Sync + Send, + Self::Item: Try<Output = T>, + { + try_reduce::try_reduce(self, identity, op) + } + + /// Reduces the items in the iterator into one item using a fallible `op`. + /// + /// Like [`reduce_with()`], if the iterator is empty, `None` is returned; + /// otherwise, `Some` is returned. Beyond that, it behaves like + /// [`try_reduce()`] for handling `Err`/`None`. + /// + /// [`reduce_with()`]: #method.reduce_with + /// [`try_reduce()`]: #method.try_reduce + /// + /// For instance, with `Option` items, the return value may be: + /// - `None`, the iterator was empty + /// - `Some(None)`, we stopped after encountering `None`. + /// - `Some(Some(x))`, the entire iterator reduced to `x`. + /// + /// With `Result` items, the nesting is more obvious: + /// - `None`, the iterator was empty + /// - `Some(Err(e))`, we stopped after encountering an error `e`. + /// - `Some(Ok(x))`, the entire iterator reduced to `x`. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let files = ["/dev/null", "/does/not/exist"]; + /// + /// // Find the biggest file + /// files.into_par_iter() + /// .map(|path| std::fs::metadata(path).map(|m| (path, m.len()))) + /// .try_reduce_with(|a, b| { + /// Ok(if a.1 >= b.1 { a } else { b }) + /// }) + /// .expect("Some value, since the iterator is not empty") + /// .expect_err("not found"); + /// ``` + fn try_reduce_with<T, OP>(self, op: OP) -> Option<Self::Item> + where + OP: Fn(T, T) -> Self::Item + Sync + Send, + Self::Item: Try<Output = T>, + { + try_reduce_with::try_reduce_with(self, op) + } + + /// Parallel fold is similar to sequential fold except that the + /// sequence of items may be subdivided before it is + /// folded. Consider a list of numbers like `22 3 77 89 46`. If + /// you used sequential fold to add them (`fold(0, |a,b| a+b)`, + /// you would wind up first adding 0 + 22, then 22 + 3, then 25 + + /// 77, and so forth. The **parallel fold** works similarly except + /// that it first breaks up your list into sublists, and hence + /// instead of yielding up a single sum at the end, it yields up + /// multiple sums. The number of results is nondeterministic, as + /// is the point where the breaks occur. + /// + /// So if we did the same parallel fold (`fold(0, |a,b| a+b)`) on + /// our example list, we might wind up with a sequence of two numbers, + /// like so: + /// + /// ```notrust + /// 22 3 77 89 46 + /// | | + /// 102 135 + /// ``` + /// + /// Or perhaps these three numbers: + /// + /// ```notrust + /// 22 3 77 89 46 + /// | | | + /// 102 89 46 + /// ``` + /// + /// In general, Rayon will attempt to find good breaking points + /// that keep all of your cores busy. + /// + /// ### Fold versus reduce + /// + /// The `fold()` and `reduce()` methods each take an identity element + /// and a combining function, but they operate rather differently. + /// + /// `reduce()` requires that the identity function has the same + /// type as the things you are iterating over, and it fully + /// reduces the list of items into a single item. So, for example, + /// imagine we are iterating over a list of bytes `bytes: [128_u8, + /// 64_u8, 64_u8]`. If we used `bytes.reduce(|| 0_u8, |a: u8, b: + /// u8| a + b)`, we would get an overflow. This is because `0`, + /// `a`, and `b` here are all bytes, just like the numbers in the + /// list (I wrote the types explicitly above, but those are the + /// only types you can use). To avoid the overflow, we would need + /// to do something like `bytes.map(|b| b as u32).reduce(|| 0, |a, + /// b| a + b)`, in which case our result would be `256`. + /// + /// In contrast, with `fold()`, the identity function does not + /// have to have the same type as the things you are iterating + /// over, and you potentially get back many results. So, if we + /// continue with the `bytes` example from the previous paragraph, + /// we could do `bytes.fold(|| 0_u32, |a, b| a + (b as u32))` to + /// convert our bytes into `u32`. And of course we might not get + /// back a single sum. + /// + /// There is a more subtle distinction as well, though it's + /// actually implied by the above points. When you use `reduce()`, + /// your reduction function is sometimes called with values that + /// were never part of your original parallel iterator (for + /// example, both the left and right might be a partial sum). With + /// `fold()`, in contrast, the left value in the fold function is + /// always the accumulator, and the right value is always from + /// your original sequence. + /// + /// ### Fold vs Map/Reduce + /// + /// Fold makes sense if you have some operation where it is + /// cheaper to create groups of elements at a time. For example, + /// imagine collecting characters into a string. If you were going + /// to use map/reduce, you might try this: + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let s = + /// ['a', 'b', 'c', 'd', 'e'] + /// .par_iter() + /// .map(|c: &char| format!("{}", c)) + /// .reduce(|| String::new(), + /// |mut a: String, b: String| { a.push_str(&b); a }); + /// + /// assert_eq!(s, "abcde"); + /// ``` + /// + /// Because reduce produces the same type of element as its input, + /// you have to first map each character into a string, and then + /// you can reduce them. This means we create one string per + /// element in our iterator -- not so great. Using `fold`, we can + /// do this instead: + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let s = + /// ['a', 'b', 'c', 'd', 'e'] + /// .par_iter() + /// .fold(|| String::new(), + /// |mut s: String, c: &char| { s.push(*c); s }) + /// .reduce(|| String::new(), + /// |mut a: String, b: String| { a.push_str(&b); a }); + /// + /// assert_eq!(s, "abcde"); + /// ``` + /// + /// Now `fold` will process groups of our characters at a time, + /// and we only make one string per group. We should wind up with + /// some small-ish number of strings roughly proportional to the + /// number of CPUs you have (it will ultimately depend on how busy + /// your processors are). Note that we still need to do a reduce + /// afterwards to combine those groups of strings into a single + /// string. + /// + /// You could use a similar trick to save partial results (e.g., a + /// cache) or something similar. + /// + /// ### Combining fold with other operations + /// + /// You can combine `fold` with `reduce` if you want to produce a + /// single value. This is then roughly equivalent to a map/reduce + /// combination in effect: + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let bytes = 0..22_u8; + /// let sum = bytes.into_par_iter() + /// .fold(|| 0_u32, |a: u32, b: u8| a + (b as u32)) + /// .sum::<u32>(); + /// + /// assert_eq!(sum, (0..22).sum()); // compare to sequential + /// ``` + fn fold<T, ID, F>(self, identity: ID, fold_op: F) -> Fold<Self, ID, F> + where + F: Fn(T, Self::Item) -> T + Sync + Send, + ID: Fn() -> T + Sync + Send, + T: Send, + { + Fold::new(self, identity, fold_op) + } + + /// Applies `fold_op` to the given `init` value with each item of this + /// iterator, finally producing the value for further use. + /// + /// This works essentially like `fold(|| init.clone(), fold_op)`, except + /// it doesn't require the `init` type to be `Sync`, nor any other form + /// of added synchronization. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let bytes = 0..22_u8; + /// let sum = bytes.into_par_iter() + /// .fold_with(0_u32, |a: u32, b: u8| a + (b as u32)) + /// .sum::<u32>(); + /// + /// assert_eq!(sum, (0..22).sum()); // compare to sequential + /// ``` + fn fold_with<F, T>(self, init: T, fold_op: F) -> FoldWith<Self, T, F> + where + F: Fn(T, Self::Item) -> T + Sync + Send, + T: Send + Clone, + { + FoldWith::new(self, init, fold_op) + } + + /// Performs a fallible parallel fold. + /// + /// This is a variation of [`fold()`] for operations which can fail with + /// `Option::None` or `Result::Err`. The first such failure stops + /// processing the local set of items, without affecting other folds in the + /// iterator's subdivisions. + /// + /// Often, `try_fold()` will be followed by [`try_reduce()`] + /// for a final reduction and global short-circuiting effect. + /// + /// [`fold()`]: #method.fold + /// [`try_reduce()`]: #method.try_reduce + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let bytes = 0..22_u8; + /// let sum = bytes.into_par_iter() + /// .try_fold(|| 0_u32, |a: u32, b: u8| a.checked_add(b as u32)) + /// .try_reduce(|| 0, u32::checked_add); + /// + /// assert_eq!(sum, Some((0..22).sum())); // compare to sequential + /// ``` + fn try_fold<T, R, ID, F>(self, identity: ID, fold_op: F) -> TryFold<Self, R, ID, F> + where + F: Fn(T, Self::Item) -> R + Sync + Send, + ID: Fn() -> T + Sync + Send, + R: Try<Output = T> + Send, + { + TryFold::new(self, identity, fold_op) + } + + /// Performs a fallible parallel fold with a cloneable `init` value. + /// + /// This combines the `init` semantics of [`fold_with()`] and the failure + /// semantics of [`try_fold()`]. + /// + /// [`fold_with()`]: #method.fold_with + /// [`try_fold()`]: #method.try_fold + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let bytes = 0..22_u8; + /// let sum = bytes.into_par_iter() + /// .try_fold_with(0_u32, |a: u32, b: u8| a.checked_add(b as u32)) + /// .try_reduce(|| 0, u32::checked_add); + /// + /// assert_eq!(sum, Some((0..22).sum())); // compare to sequential + /// ``` + fn try_fold_with<F, T, R>(self, init: T, fold_op: F) -> TryFoldWith<Self, R, F> + where + F: Fn(T, Self::Item) -> R + Sync + Send, + R: Try<Output = T> + Send, + T: Clone + Send, + { + TryFoldWith::new(self, init, fold_op) + } + + /// Sums up the items in the iterator. + /// + /// Note that the order in items will be reduced is not specified, + /// so if the `+` operator is not truly [associative] \(as is the + /// case for floating point numbers), then the results are not + /// fully deterministic. + /// + /// [associative]: https://en.wikipedia.org/wiki/Associative_property + /// + /// Basically equivalent to `self.reduce(|| 0, |a, b| a + b)`, + /// except that the type of `0` and the `+` operation may vary + /// depending on the type of value being produced. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [1, 5, 7]; + /// + /// let sum: i32 = a.par_iter().sum(); + /// + /// assert_eq!(sum, 13); + /// ``` + fn sum<S>(self) -> S + where + S: Send + Sum<Self::Item> + Sum<S>, + { + sum::sum(self) + } + + /// Multiplies all the items in the iterator. + /// + /// Note that the order in items will be reduced is not specified, + /// so if the `*` operator is not truly [associative] \(as is the + /// case for floating point numbers), then the results are not + /// fully deterministic. + /// + /// [associative]: https://en.wikipedia.org/wiki/Associative_property + /// + /// Basically equivalent to `self.reduce(|| 1, |a, b| a * b)`, + /// except that the type of `1` and the `*` operation may vary + /// depending on the type of value being produced. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// fn factorial(n: u32) -> u32 { + /// (1..n+1).into_par_iter().product() + /// } + /// + /// assert_eq!(factorial(0), 1); + /// assert_eq!(factorial(1), 1); + /// assert_eq!(factorial(5), 120); + /// ``` + fn product<P>(self) -> P + where + P: Send + Product<Self::Item> + Product<P>, + { + product::product(self) + } + + /// Computes the minimum of all the items in the iterator. If the + /// iterator is empty, `None` is returned; otherwise, `Some(min)` + /// is returned. + /// + /// Note that the order in which the items will be reduced is not + /// specified, so if the `Ord` impl is not truly associative, then + /// the results are not deterministic. + /// + /// Basically equivalent to `self.reduce_with(|a, b| cmp::min(a, b))`. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [45, 74, 32]; + /// + /// assert_eq!(a.par_iter().min(), Some(&32)); + /// + /// let b: [i32; 0] = []; + /// + /// assert_eq!(b.par_iter().min(), None); + /// ``` + fn min(self) -> Option<Self::Item> + where + Self::Item: Ord, + { + self.reduce_with(cmp::min) + } + + /// Computes the minimum of all the items in the iterator with respect to + /// the given comparison function. If the iterator is empty, `None` is + /// returned; otherwise, `Some(min)` is returned. + /// + /// Note that the order in which the items will be reduced is not + /// specified, so if the comparison function is not associative, then + /// the results are not deterministic. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [-3_i32, 77, 53, 240, -1]; + /// + /// assert_eq!(a.par_iter().min_by(|x, y| x.cmp(y)), Some(&-3)); + /// ``` + fn min_by<F>(self, f: F) -> Option<Self::Item> + where + F: Sync + Send + Fn(&Self::Item, &Self::Item) -> Ordering, + { + fn min<T>(f: impl Fn(&T, &T) -> Ordering) -> impl Fn(T, T) -> T { + move |a, b| match f(&a, &b) { + Ordering::Greater => b, + _ => a, + } + } + + self.reduce_with(min(f)) + } + + /// Computes the item that yields the minimum value for the given + /// function. If the iterator is empty, `None` is returned; + /// otherwise, `Some(item)` is returned. + /// + /// Note that the order in which the items will be reduced is not + /// specified, so if the `Ord` impl is not truly associative, then + /// the results are not deterministic. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [-3_i32, 34, 2, 5, -10, -3, -23]; + /// + /// assert_eq!(a.par_iter().min_by_key(|x| x.abs()), Some(&2)); + /// ``` + fn min_by_key<K, F>(self, f: F) -> Option<Self::Item> + where + K: Ord + Send, + F: Sync + Send + Fn(&Self::Item) -> K, + { + fn key<T, K>(f: impl Fn(&T) -> K) -> impl Fn(T) -> (K, T) { + move |x| (f(&x), x) + } + + fn min_key<T, K: Ord>(a: (K, T), b: (K, T)) -> (K, T) { + match (a.0).cmp(&b.0) { + Ordering::Greater => b, + _ => a, + } + } + + let (_, x) = self.map(key(f)).reduce_with(min_key)?; + Some(x) + } + + /// Computes the maximum of all the items in the iterator. If the + /// iterator is empty, `None` is returned; otherwise, `Some(max)` + /// is returned. + /// + /// Note that the order in which the items will be reduced is not + /// specified, so if the `Ord` impl is not truly associative, then + /// the results are not deterministic. + /// + /// Basically equivalent to `self.reduce_with(|a, b| cmp::max(a, b))`. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [45, 74, 32]; + /// + /// assert_eq!(a.par_iter().max(), Some(&74)); + /// + /// let b: [i32; 0] = []; + /// + /// assert_eq!(b.par_iter().max(), None); + /// ``` + fn max(self) -> Option<Self::Item> + where + Self::Item: Ord, + { + self.reduce_with(cmp::max) + } + + /// Computes the maximum of all the items in the iterator with respect to + /// the given comparison function. If the iterator is empty, `None` is + /// returned; otherwise, `Some(max)` is returned. + /// + /// Note that the order in which the items will be reduced is not + /// specified, so if the comparison function is not associative, then + /// the results are not deterministic. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [-3_i32, 77, 53, 240, -1]; + /// + /// assert_eq!(a.par_iter().max_by(|x, y| x.abs().cmp(&y.abs())), Some(&240)); + /// ``` + fn max_by<F>(self, f: F) -> Option<Self::Item> + where + F: Sync + Send + Fn(&Self::Item, &Self::Item) -> Ordering, + { + fn max<T>(f: impl Fn(&T, &T) -> Ordering) -> impl Fn(T, T) -> T { + move |a, b| match f(&a, &b) { + Ordering::Greater => a, + _ => b, + } + } + + self.reduce_with(max(f)) + } + + /// Computes the item that yields the maximum value for the given + /// function. If the iterator is empty, `None` is returned; + /// otherwise, `Some(item)` is returned. + /// + /// Note that the order in which the items will be reduced is not + /// specified, so if the `Ord` impl is not truly associative, then + /// the results are not deterministic. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [-3_i32, 34, 2, 5, -10, -3, -23]; + /// + /// assert_eq!(a.par_iter().max_by_key(|x| x.abs()), Some(&34)); + /// ``` + fn max_by_key<K, F>(self, f: F) -> Option<Self::Item> + where + K: Ord + Send, + F: Sync + Send + Fn(&Self::Item) -> K, + { + fn key<T, K>(f: impl Fn(&T) -> K) -> impl Fn(T) -> (K, T) { + move |x| (f(&x), x) + } + + fn max_key<T, K: Ord>(a: (K, T), b: (K, T)) -> (K, T) { + match (a.0).cmp(&b.0) { + Ordering::Greater => a, + _ => b, + } + } + + let (_, x) = self.map(key(f)).reduce_with(max_key)?; + Some(x) + } + + /// Takes two iterators and creates a new iterator over both. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [0, 1, 2]; + /// let b = [9, 8, 7]; + /// + /// let par_iter = a.par_iter().chain(b.par_iter()); + /// + /// let chained: Vec<_> = par_iter.cloned().collect(); + /// + /// assert_eq!(&chained[..], &[0, 1, 2, 9, 8, 7]); + /// ``` + fn chain<C>(self, chain: C) -> Chain<Self, C::Iter> + where + C: IntoParallelIterator<Item = Self::Item>, + { + Chain::new(self, chain.into_par_iter()) + } + + /// Searches for **some** item in the parallel iterator that + /// matches the given predicate and returns it. This operation + /// is similar to [`find` on sequential iterators][find] but + /// the item returned may not be the **first** one in the parallel + /// sequence which matches, since we search the entire sequence in parallel. + /// + /// Once a match is found, we will attempt to stop processing + /// the rest of the items in the iterator as soon as possible + /// (just as `find` stops iterating once a match is found). + /// + /// [find]: https://doc.rust-lang.org/std/iter/trait.Iterator.html#method.find + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [1, 2, 3, 3]; + /// + /// assert_eq!(a.par_iter().find_any(|&&x| x == 3), Some(&3)); + /// + /// assert_eq!(a.par_iter().find_any(|&&x| x == 100), None); + /// ``` + fn find_any<P>(self, predicate: P) -> Option<Self::Item> + where + P: Fn(&Self::Item) -> bool + Sync + Send, + { + find::find(self, predicate) + } + + /// Searches for the sequentially **first** item in the parallel iterator + /// that matches the given predicate and returns it. + /// + /// Once a match is found, all attempts to the right of the match + /// will be stopped, while attempts to the left must continue in case + /// an earlier match is found. + /// + /// Note that not all parallel iterators have a useful order, much like + /// sequential `HashMap` iteration, so "first" may be nebulous. If you + /// just want the first match that discovered anywhere in the iterator, + /// `find_any` is a better choice. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [1, 2, 3, 3]; + /// + /// assert_eq!(a.par_iter().find_first(|&&x| x == 3), Some(&3)); + /// + /// assert_eq!(a.par_iter().find_first(|&&x| x == 100), None); + /// ``` + fn find_first<P>(self, predicate: P) -> Option<Self::Item> + where + P: Fn(&Self::Item) -> bool + Sync + Send, + { + find_first_last::find_first(self, predicate) + } + + /// Searches for the sequentially **last** item in the parallel iterator + /// that matches the given predicate and returns it. + /// + /// Once a match is found, all attempts to the left of the match + /// will be stopped, while attempts to the right must continue in case + /// a later match is found. + /// + /// Note that not all parallel iterators have a useful order, much like + /// sequential `HashMap` iteration, so "last" may be nebulous. When the + /// order doesn't actually matter to you, `find_any` is a better choice. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [1, 2, 3, 3]; + /// + /// assert_eq!(a.par_iter().find_last(|&&x| x == 3), Some(&3)); + /// + /// assert_eq!(a.par_iter().find_last(|&&x| x == 100), None); + /// ``` + fn find_last<P>(self, predicate: P) -> Option<Self::Item> + where + P: Fn(&Self::Item) -> bool + Sync + Send, + { + find_first_last::find_last(self, predicate) + } + + /// Applies the given predicate to the items in the parallel iterator + /// and returns **any** non-None result of the map operation. + /// + /// Once a non-None value is produced from the map operation, we will + /// attempt to stop processing the rest of the items in the iterator + /// as soon as possible. + /// + /// Note that this method only returns **some** item in the parallel + /// iterator that is not None from the map predicate. The item returned + /// may not be the **first** non-None value produced in the parallel + /// sequence, since the entire sequence is mapped over in parallel. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let c = ["lol", "NaN", "5", "5"]; + /// + /// let found_number = c.par_iter().find_map_any(|s| s.parse().ok()); + /// + /// assert_eq!(found_number, Some(5)); + /// ``` + fn find_map_any<P, R>(self, predicate: P) -> Option<R> + where + P: Fn(Self::Item) -> Option<R> + Sync + Send, + R: Send, + { + fn yes<T>(_: &T) -> bool { + true + } + self.filter_map(predicate).find_any(yes) + } + + /// Applies the given predicate to the items in the parallel iterator and + /// returns the sequentially **first** non-None result of the map operation. + /// + /// Once a non-None value is produced from the map operation, all attempts + /// to the right of the match will be stopped, while attempts to the left + /// must continue in case an earlier match is found. + /// + /// Note that not all parallel iterators have a useful order, much like + /// sequential `HashMap` iteration, so "first" may be nebulous. If you + /// just want the first non-None value discovered anywhere in the iterator, + /// `find_map_any` is a better choice. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let c = ["lol", "NaN", "2", "5"]; + /// + /// let first_number = c.par_iter().find_map_first(|s| s.parse().ok()); + /// + /// assert_eq!(first_number, Some(2)); + /// ``` + fn find_map_first<P, R>(self, predicate: P) -> Option<R> + where + P: Fn(Self::Item) -> Option<R> + Sync + Send, + R: Send, + { + fn yes<T>(_: &T) -> bool { + true + } + self.filter_map(predicate).find_first(yes) + } + + /// Applies the given predicate to the items in the parallel iterator and + /// returns the sequentially **last** non-None result of the map operation. + /// + /// Once a non-None value is produced from the map operation, all attempts + /// to the left of the match will be stopped, while attempts to the right + /// must continue in case a later match is found. + /// + /// Note that not all parallel iterators have a useful order, much like + /// sequential `HashMap` iteration, so "first" may be nebulous. If you + /// just want the first non-None value discovered anywhere in the iterator, + /// `find_map_any` is a better choice. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let c = ["lol", "NaN", "2", "5"]; + /// + /// let last_number = c.par_iter().find_map_last(|s| s.parse().ok()); + /// + /// assert_eq!(last_number, Some(5)); + /// ``` + fn find_map_last<P, R>(self, predicate: P) -> Option<R> + where + P: Fn(Self::Item) -> Option<R> + Sync + Send, + R: Send, + { + fn yes<T>(_: &T) -> bool { + true + } + self.filter_map(predicate).find_last(yes) + } + + #[doc(hidden)] + #[deprecated(note = "parallel `find` does not search in order -- use `find_any`, \\ + `find_first`, or `find_last`")] + fn find<P>(self, predicate: P) -> Option<Self::Item> + where + P: Fn(&Self::Item) -> bool + Sync + Send, + { + self.find_any(predicate) + } + + /// Searches for **some** item in the parallel iterator that + /// matches the given predicate, and if so returns true. Once + /// a match is found, we'll attempt to stop process the rest + /// of the items. Proving that there's no match, returning false, + /// does require visiting every item. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [0, 12, 3, 4, 0, 23, 0]; + /// + /// let is_valid = a.par_iter().any(|&x| x > 10); + /// + /// assert!(is_valid); + /// ``` + fn any<P>(self, predicate: P) -> bool + where + P: Fn(Self::Item) -> bool + Sync + Send, + { + self.map(predicate).find_any(bool::clone).is_some() + } + + /// Tests that every item in the parallel iterator matches the given + /// predicate, and if so returns true. If a counter-example is found, + /// we'll attempt to stop processing more items, then return false. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [0, 12, 3, 4, 0, 23, 0]; + /// + /// let is_valid = a.par_iter().all(|&x| x > 10); + /// + /// assert!(!is_valid); + /// ``` + fn all<P>(self, predicate: P) -> bool + where + P: Fn(Self::Item) -> bool + Sync + Send, + { + #[inline] + fn is_false(x: &bool) -> bool { + !x + } + + self.map(predicate).find_any(is_false).is_none() + } + + /// Creates an iterator over the `Some` items of this iterator, halting + /// as soon as any `None` is found. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// use std::sync::atomic::{AtomicUsize, Ordering}; + /// + /// let counter = AtomicUsize::new(0); + /// let value = (0_i32..2048) + /// .into_par_iter() + /// .map(|x| { + /// counter.fetch_add(1, Ordering::SeqCst); + /// if x < 1024 { Some(x) } else { None } + /// }) + /// .while_some() + /// .max(); + /// + /// assert!(value < Some(1024)); + /// assert!(counter.load(Ordering::SeqCst) < 2048); // should not have visited every single one + /// ``` + fn while_some<T>(self) -> WhileSome<Self> + where + Self: ParallelIterator<Item = Option<T>>, + T: Send, + { + WhileSome::new(self) + } + + /// Wraps an iterator with a fuse in case of panics, to halt all threads + /// as soon as possible. + /// + /// Panics within parallel iterators are always propagated to the caller, + /// but they don't always halt the rest of the iterator right away, due to + /// the internal semantics of [`join`]. This adaptor makes a greater effort + /// to stop processing other items sooner, with the cost of additional + /// synchronization overhead, which may also inhibit some optimizations. + /// + /// [`join`]: ../fn.join.html#panics + /// + /// # Examples + /// + /// If this code didn't use `panic_fuse()`, it would continue processing + /// many more items in other threads (with long sleep delays) before the + /// panic is finally propagated. + /// + /// ```should_panic + /// use rayon::prelude::*; + /// use std::{thread, time}; + /// + /// (0..1_000_000) + /// .into_par_iter() + /// .panic_fuse() + /// .for_each(|i| { + /// // simulate some work + /// thread::sleep(time::Duration::from_secs(1)); + /// assert!(i > 0); // oops! + /// }); + /// ``` + fn panic_fuse(self) -> PanicFuse<Self> { + PanicFuse::new(self) + } + + /// Creates a fresh collection containing all the elements produced + /// by this parallel iterator. + /// + /// You may prefer [`collect_into_vec()`] implemented on + /// [`IndexedParallelIterator`], if your underlying iterator also implements + /// it. [`collect_into_vec()`] allocates efficiently with precise knowledge + /// of how many elements the iterator contains, and even allows you to reuse + /// an existing vector's backing store rather than allocating a fresh vector. + /// + /// [`IndexedParallelIterator`]: trait.IndexedParallelIterator.html + /// [`collect_into_vec()`]: + /// trait.IndexedParallelIterator.html#method.collect_into_vec + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let sync_vec: Vec<_> = (0..100).into_iter().collect(); + /// + /// let async_vec: Vec<_> = (0..100).into_par_iter().collect(); + /// + /// assert_eq!(sync_vec, async_vec); + /// ``` + /// + /// You can collect a pair of collections like [`unzip`](#method.unzip) + /// for paired items: + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [(0, 1), (1, 2), (2, 3), (3, 4)]; + /// let (first, second): (Vec<_>, Vec<_>) = a.into_par_iter().collect(); + /// + /// assert_eq!(first, [0, 1, 2, 3]); + /// assert_eq!(second, [1, 2, 3, 4]); + /// ``` + /// + /// Or like [`partition_map`](#method.partition_map) for `Either` items: + /// + /// ``` + /// use rayon::prelude::*; + /// use rayon::iter::Either; + /// + /// let (left, right): (Vec<_>, Vec<_>) = (0..8).into_par_iter().map(|x| { + /// if x % 2 == 0 { + /// Either::Left(x * 4) + /// } else { + /// Either::Right(x * 3) + /// } + /// }).collect(); + /// + /// assert_eq!(left, [0, 8, 16, 24]); + /// assert_eq!(right, [3, 9, 15, 21]); + /// ``` + /// + /// You can even collect an arbitrarily-nested combination of pairs and `Either`: + /// + /// ``` + /// use rayon::prelude::*; + /// use rayon::iter::Either; + /// + /// let (first, (left, right)): (Vec<_>, (Vec<_>, Vec<_>)) + /// = (0..8).into_par_iter().map(|x| { + /// if x % 2 == 0 { + /// (x, Either::Left(x * 4)) + /// } else { + /// (-x, Either::Right(x * 3)) + /// } + /// }).collect(); + /// + /// assert_eq!(first, [0, -1, 2, -3, 4, -5, 6, -7]); + /// assert_eq!(left, [0, 8, 16, 24]); + /// assert_eq!(right, [3, 9, 15, 21]); + /// ``` + /// + /// All of that can _also_ be combined with short-circuiting collection of + /// `Result` or `Option` types: + /// + /// ``` + /// use rayon::prelude::*; + /// use rayon::iter::Either; + /// + /// let result: Result<(Vec<_>, (Vec<_>, Vec<_>)), _> + /// = (0..8).into_par_iter().map(|x| { + /// if x > 5 { + /// Err(x) + /// } else if x % 2 == 0 { + /// Ok((x, Either::Left(x * 4))) + /// } else { + /// Ok((-x, Either::Right(x * 3))) + /// } + /// }).collect(); + /// + /// let error = result.unwrap_err(); + /// assert!(error == 6 || error == 7); + /// ``` + fn collect<C>(self) -> C + where + C: FromParallelIterator<Self::Item>, + { + C::from_par_iter(self) + } + + /// Unzips the items of a parallel iterator into a pair of arbitrary + /// `ParallelExtend` containers. + /// + /// You may prefer to use `unzip_into_vecs()`, which allocates more + /// efficiently with precise knowledge of how many elements the + /// iterator contains, and even allows you to reuse existing + /// vectors' backing stores rather than allocating fresh vectors. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [(0, 1), (1, 2), (2, 3), (3, 4)]; + /// + /// let (left, right): (Vec<_>, Vec<_>) = a.par_iter().cloned().unzip(); + /// + /// assert_eq!(left, [0, 1, 2, 3]); + /// assert_eq!(right, [1, 2, 3, 4]); + /// ``` + /// + /// Nested pairs can be unzipped too. + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let (values, (squares, cubes)): (Vec<_>, (Vec<_>, Vec<_>)) = (0..4).into_par_iter() + /// .map(|i| (i, (i * i, i * i * i))) + /// .unzip(); + /// + /// assert_eq!(values, [0, 1, 2, 3]); + /// assert_eq!(squares, [0, 1, 4, 9]); + /// assert_eq!(cubes, [0, 1, 8, 27]); + /// ``` + fn unzip<A, B, FromA, FromB>(self) -> (FromA, FromB) + where + Self: ParallelIterator<Item = (A, B)>, + FromA: Default + Send + ParallelExtend<A>, + FromB: Default + Send + ParallelExtend<B>, + A: Send, + B: Send, + { + unzip::unzip(self) + } + + /// Partitions the items of a parallel iterator into a pair of arbitrary + /// `ParallelExtend` containers. Items for which the `predicate` returns + /// true go into the first container, and the rest go into the second. + /// + /// Note: unlike the standard `Iterator::partition`, this allows distinct + /// collection types for the left and right items. This is more flexible, + /// but may require new type annotations when converting sequential code + /// that used type inference assuming the two were the same. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let (left, right): (Vec<_>, Vec<_>) = (0..8).into_par_iter().partition(|x| x % 2 == 0); + /// + /// assert_eq!(left, [0, 2, 4, 6]); + /// assert_eq!(right, [1, 3, 5, 7]); + /// ``` + fn partition<A, B, P>(self, predicate: P) -> (A, B) + where + A: Default + Send + ParallelExtend<Self::Item>, + B: Default + Send + ParallelExtend<Self::Item>, + P: Fn(&Self::Item) -> bool + Sync + Send, + { + unzip::partition(self, predicate) + } + + /// Partitions and maps the items of a parallel iterator into a pair of + /// arbitrary `ParallelExtend` containers. `Either::Left` items go into + /// the first container, and `Either::Right` items go into the second. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// use rayon::iter::Either; + /// + /// let (left, right): (Vec<_>, Vec<_>) = (0..8).into_par_iter() + /// .partition_map(|x| { + /// if x % 2 == 0 { + /// Either::Left(x * 4) + /// } else { + /// Either::Right(x * 3) + /// } + /// }); + /// + /// assert_eq!(left, [0, 8, 16, 24]); + /// assert_eq!(right, [3, 9, 15, 21]); + /// ``` + /// + /// Nested `Either` enums can be split as well. + /// + /// ``` + /// use rayon::prelude::*; + /// use rayon::iter::Either::*; + /// + /// let ((fizzbuzz, fizz), (buzz, other)): ((Vec<_>, Vec<_>), (Vec<_>, Vec<_>)) = (1..20) + /// .into_par_iter() + /// .partition_map(|x| match (x % 3, x % 5) { + /// (0, 0) => Left(Left(x)), + /// (0, _) => Left(Right(x)), + /// (_, 0) => Right(Left(x)), + /// (_, _) => Right(Right(x)), + /// }); + /// + /// assert_eq!(fizzbuzz, [15]); + /// assert_eq!(fizz, [3, 6, 9, 12, 18]); + /// assert_eq!(buzz, [5, 10]); + /// assert_eq!(other, [1, 2, 4, 7, 8, 11, 13, 14, 16, 17, 19]); + /// ``` + fn partition_map<A, B, P, L, R>(self, predicate: P) -> (A, B) + where + A: Default + Send + ParallelExtend<L>, + B: Default + Send + ParallelExtend<R>, + P: Fn(Self::Item) -> Either<L, R> + Sync + Send, + L: Send, + R: Send, + { + unzip::partition_map(self, predicate) + } + + /// Intersperses clones of an element between items of this iterator. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let x = vec![1, 2, 3]; + /// let r: Vec<_> = x.into_par_iter().intersperse(-1).collect(); + /// + /// assert_eq!(r, vec![1, -1, 2, -1, 3]); + /// ``` + fn intersperse(self, element: Self::Item) -> Intersperse<Self> + where + Self::Item: Clone, + { + Intersperse::new(self, element) + } + + /// Creates an iterator that yields `n` elements from *anywhere* in the original iterator. + /// + /// This is similar to [`IndexedParallelIterator::take`] without being + /// constrained to the "first" `n` of the original iterator order. The + /// taken items will still maintain their relative order where that is + /// visible in `collect`, `reduce`, and similar outputs. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let result: Vec<_> = (0..100) + /// .into_par_iter() + /// .filter(|&x| x % 2 == 0) + /// .take_any(5) + /// .collect(); + /// + /// assert_eq!(result.len(), 5); + /// assert!(result.windows(2).all(|w| w[0] < w[1])); + /// ``` + fn take_any(self, n: usize) -> TakeAny<Self> { + TakeAny::new(self, n) + } + + /// Creates an iterator that skips `n` elements from *anywhere* in the original iterator. + /// + /// This is similar to [`IndexedParallelIterator::skip`] without being + /// constrained to the "first" `n` of the original iterator order. The + /// remaining items will still maintain their relative order where that is + /// visible in `collect`, `reduce`, and similar outputs. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let result: Vec<_> = (0..100) + /// .into_par_iter() + /// .filter(|&x| x % 2 == 0) + /// .skip_any(5) + /// .collect(); + /// + /// assert_eq!(result.len(), 45); + /// assert!(result.windows(2).all(|w| w[0] < w[1])); + /// ``` + fn skip_any(self, n: usize) -> SkipAny<Self> { + SkipAny::new(self, n) + } + + /// Creates an iterator that takes elements from *anywhere* in the original iterator + /// until the given `predicate` returns `false`. + /// + /// The `predicate` may be anything -- e.g. it could be checking a fact about the item, a + /// global condition unrelated to the item itself, or some combination thereof. + /// + /// If parallel calls to the `predicate` race and give different results, then the + /// `true` results will still take those particular items, while respecting the `false` + /// result from elsewhere to skip any further items. + /// + /// This is similar to [`Iterator::take_while`] without being constrained to the original + /// iterator order. The taken items will still maintain their relative order where that is + /// visible in `collect`, `reduce`, and similar outputs. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let result: Vec<_> = (0..100) + /// .into_par_iter() + /// .take_any_while(|x| *x < 50) + /// .collect(); + /// + /// assert!(result.len() <= 50); + /// assert!(result.windows(2).all(|w| w[0] < w[1])); + /// ``` + /// + /// ``` + /// use rayon::prelude::*; + /// use std::sync::atomic::AtomicUsize; + /// use std::sync::atomic::Ordering::Relaxed; + /// + /// // Collect any group of items that sum <= 1000 + /// let quota = AtomicUsize::new(1000); + /// let result: Vec<_> = (0_usize..100) + /// .into_par_iter() + /// .take_any_while(|&x| { + /// quota.fetch_update(Relaxed, Relaxed, |q| q.checked_sub(x)) + /// .is_ok() + /// }) + /// .collect(); + /// + /// let sum = result.iter().sum::<usize>(); + /// assert!(matches!(sum, 902..=1000)); + /// ``` + fn take_any_while<P>(self, predicate: P) -> TakeAnyWhile<Self, P> + where + P: Fn(&Self::Item) -> bool + Sync + Send, + { + TakeAnyWhile::new(self, predicate) + } + + /// Creates an iterator that skips elements from *anywhere* in the original iterator + /// until the given `predicate` returns `false`. + /// + /// The `predicate` may be anything -- e.g. it could be checking a fact about the item, a + /// global condition unrelated to the item itself, or some combination thereof. + /// + /// If parallel calls to the `predicate` race and give different results, then the + /// `true` results will still skip those particular items, while respecting the `false` + /// result from elsewhere to skip any further items. + /// + /// This is similar to [`Iterator::skip_while`] without being constrained to the original + /// iterator order. The remaining items will still maintain their relative order where that is + /// visible in `collect`, `reduce`, and similar outputs. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let result: Vec<_> = (0..100) + /// .into_par_iter() + /// .skip_any_while(|x| *x < 50) + /// .collect(); + /// + /// assert!(result.len() >= 50); + /// assert!(result.windows(2).all(|w| w[0] < w[1])); + /// ``` + fn skip_any_while<P>(self, predicate: P) -> SkipAnyWhile<Self, P> + where + P: Fn(&Self::Item) -> bool + Sync + Send, + { + SkipAnyWhile::new(self, predicate) + } + + /// Internal method used to define the behavior of this parallel + /// iterator. You should not need to call this directly. + /// + /// This method causes the iterator `self` to start producing + /// items and to feed them to the consumer `consumer` one by one. + /// It may split the consumer before doing so to create the + /// opportunity to produce in parallel. + /// + /// See the [README] for more details on the internals of parallel + /// iterators. + /// + /// [README]: https://github.com/rayon-rs/rayon/blob/master/src/iter/plumbing/README.md + fn drive_unindexed<C>(self, consumer: C) -> C::Result + where + C: UnindexedConsumer<Self::Item>; + + /// Internal method used to define the behavior of this parallel + /// iterator. You should not need to call this directly. + /// + /// Returns the number of items produced by this iterator, if known + /// statically. This can be used by consumers to trigger special fast + /// paths. Therefore, if `Some(_)` is returned, this iterator must only + /// use the (indexed) `Consumer` methods when driving a consumer, such + /// as `split_at()`. Calling `UnindexedConsumer::split_off_left()` or + /// other `UnindexedConsumer` methods -- or returning an inaccurate + /// value -- may result in panics. + /// + /// This method is currently used to optimize `collect` for want + /// of true Rust specialization; it may be removed when + /// specialization is stable. + fn opt_len(&self) -> Option<usize> { + None + } +} + +impl<T: ParallelIterator> IntoParallelIterator for T { + type Iter = T; + type Item = T::Item; + + fn into_par_iter(self) -> T { + self + } +} + +/// An iterator that supports "random access" to its data, meaning +/// that you can split it at arbitrary indices and draw data from +/// those points. +/// +/// **Note:** Not implemented for `u64`, `i64`, `u128`, or `i128` ranges +// Waiting for `ExactSizeIterator::is_empty` to be stabilized. See rust-lang/rust#35428 +#[allow(clippy::len_without_is_empty)] +pub trait IndexedParallelIterator: ParallelIterator { + /// Collects the results of the iterator into the specified + /// vector. The vector is always cleared before execution + /// begins. If possible, reusing the vector across calls can lead + /// to better performance since it reuses the same backing buffer. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// // any prior data will be cleared + /// let mut vec = vec![-1, -2, -3]; + /// + /// (0..5).into_par_iter() + /// .collect_into_vec(&mut vec); + /// + /// assert_eq!(vec, [0, 1, 2, 3, 4]); + /// ``` + fn collect_into_vec(self, target: &mut Vec<Self::Item>) { + collect::collect_into_vec(self, target); + } + + /// Unzips the results of the iterator into the specified + /// vectors. The vectors are always cleared before execution + /// begins. If possible, reusing the vectors across calls can lead + /// to better performance since they reuse the same backing buffer. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// // any prior data will be cleared + /// let mut left = vec![42; 10]; + /// let mut right = vec![-1; 10]; + /// + /// (10..15).into_par_iter() + /// .enumerate() + /// .unzip_into_vecs(&mut left, &mut right); + /// + /// assert_eq!(left, [0, 1, 2, 3, 4]); + /// assert_eq!(right, [10, 11, 12, 13, 14]); + /// ``` + fn unzip_into_vecs<A, B>(self, left: &mut Vec<A>, right: &mut Vec<B>) + where + Self: IndexedParallelIterator<Item = (A, B)>, + A: Send, + B: Send, + { + collect::unzip_into_vecs(self, left, right); + } + + /// Iterates over tuples `(A, B)`, where the items `A` are from + /// this iterator and `B` are from the iterator given as argument. + /// Like the `zip` method on ordinary iterators, if the two + /// iterators are of unequal length, you only get the items they + /// have in common. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let result: Vec<_> = (1..4) + /// .into_par_iter() + /// .zip(vec!['a', 'b', 'c']) + /// .collect(); + /// + /// assert_eq!(result, [(1, 'a'), (2, 'b'), (3, 'c')]); + /// ``` + fn zip<Z>(self, zip_op: Z) -> Zip<Self, Z::Iter> + where + Z: IntoParallelIterator, + Z::Iter: IndexedParallelIterator, + { + Zip::new(self, zip_op.into_par_iter()) + } + + /// The same as `Zip`, but requires that both iterators have the same length. + /// + /// # Panics + /// Will panic if `self` and `zip_op` are not the same length. + /// + /// ```should_panic + /// use rayon::prelude::*; + /// + /// let one = [1u8]; + /// let two = [2u8, 2]; + /// let one_iter = one.par_iter(); + /// let two_iter = two.par_iter(); + /// + /// // this will panic + /// let zipped: Vec<(&u8, &u8)> = one_iter.zip_eq(two_iter).collect(); + /// + /// // we should never get here + /// assert_eq!(1, zipped.len()); + /// ``` + #[track_caller] + fn zip_eq<Z>(self, zip_op: Z) -> ZipEq<Self, Z::Iter> + where + Z: IntoParallelIterator, + Z::Iter: IndexedParallelIterator, + { + let zip_op_iter = zip_op.into_par_iter(); + assert_eq!( + self.len(), + zip_op_iter.len(), + "iterators must have the same length" + ); + ZipEq::new(self, zip_op_iter) + } + + /// Interleaves elements of this iterator and the other given + /// iterator. Alternately yields elements from this iterator and + /// the given iterator, until both are exhausted. If one iterator + /// is exhausted before the other, the last elements are provided + /// from the other. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// let (x, y) = (vec![1, 2], vec![3, 4, 5, 6]); + /// let r: Vec<i32> = x.into_par_iter().interleave(y).collect(); + /// assert_eq!(r, vec![1, 3, 2, 4, 5, 6]); + /// ``` + fn interleave<I>(self, other: I) -> Interleave<Self, I::Iter> + where + I: IntoParallelIterator<Item = Self::Item>, + I::Iter: IndexedParallelIterator<Item = Self::Item>, + { + Interleave::new(self, other.into_par_iter()) + } + + /// Interleaves elements of this iterator and the other given + /// iterator, until one is exhausted. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// let (x, y) = (vec![1, 2, 3, 4], vec![5, 6]); + /// let r: Vec<i32> = x.into_par_iter().interleave_shortest(y).collect(); + /// assert_eq!(r, vec![1, 5, 2, 6, 3]); + /// ``` + fn interleave_shortest<I>(self, other: I) -> InterleaveShortest<Self, I::Iter> + where + I: IntoParallelIterator<Item = Self::Item>, + I::Iter: IndexedParallelIterator<Item = Self::Item>, + { + InterleaveShortest::new(self, other.into_par_iter()) + } + + /// Splits an iterator up into fixed-size chunks. + /// + /// Returns an iterator that returns `Vec`s of the given number of elements. + /// If the number of elements in the iterator is not divisible by `chunk_size`, + /// the last chunk may be shorter than `chunk_size`. + /// + /// See also [`par_chunks()`] and [`par_chunks_mut()`] for similar behavior on + /// slices, without having to allocate intermediate `Vec`s for the chunks. + /// + /// [`par_chunks()`]: ../slice/trait.ParallelSlice.html#method.par_chunks + /// [`par_chunks_mut()`]: ../slice/trait.ParallelSliceMut.html#method.par_chunks_mut + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// let a = vec![1, 2, 3, 4, 5, 6, 7, 8, 9, 10]; + /// let r: Vec<Vec<i32>> = a.into_par_iter().chunks(3).collect(); + /// assert_eq!(r, vec![vec![1,2,3], vec![4,5,6], vec![7,8,9], vec![10]]); + /// ``` + #[track_caller] + fn chunks(self, chunk_size: usize) -> Chunks<Self> { + assert!(chunk_size != 0, "chunk_size must not be zero"); + Chunks::new(self, chunk_size) + } + + /// Splits an iterator into fixed-size chunks, performing a sequential [`fold()`] on + /// each chunk. + /// + /// Returns an iterator that produces a folded result for each chunk of items + /// produced by this iterator. + /// + /// This works essentially like: + /// + /// ```text + /// iter.chunks(chunk_size) + /// .map(|chunk| + /// chunk.into_iter() + /// .fold(identity, fold_op) + /// ) + /// ``` + /// + /// except there is no per-chunk allocation overhead. + /// + /// [`fold()`]: std::iter::Iterator#method.fold + /// + /// **Panics** if `chunk_size` is 0. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// let nums = vec![1, 2, 3, 4, 5, 6, 7, 8, 9, 10]; + /// let chunk_sums = nums.into_par_iter().fold_chunks(2, || 0, |a, n| a + n).collect::<Vec<_>>(); + /// assert_eq!(chunk_sums, vec![3, 7, 11, 15, 19]); + /// ``` + #[track_caller] + fn fold_chunks<T, ID, F>( + self, + chunk_size: usize, + identity: ID, + fold_op: F, + ) -> FoldChunks<Self, ID, F> + where + ID: Fn() -> T + Send + Sync, + F: Fn(T, Self::Item) -> T + Send + Sync, + T: Send, + { + assert!(chunk_size != 0, "chunk_size must not be zero"); + FoldChunks::new(self, chunk_size, identity, fold_op) + } + + /// Splits an iterator into fixed-size chunks, performing a sequential [`fold()`] on + /// each chunk. + /// + /// Returns an iterator that produces a folded result for each chunk of items + /// produced by this iterator. + /// + /// This works essentially like `fold_chunks(chunk_size, || init.clone(), fold_op)`, + /// except it doesn't require the `init` type to be `Sync`, nor any other form of + /// added synchronization. + /// + /// [`fold()`]: std::iter::Iterator#method.fold + /// + /// **Panics** if `chunk_size` is 0. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// let nums = vec![1, 2, 3, 4, 5, 6, 7, 8, 9, 10]; + /// let chunk_sums = nums.into_par_iter().fold_chunks_with(2, 0, |a, n| a + n).collect::<Vec<_>>(); + /// assert_eq!(chunk_sums, vec![3, 7, 11, 15, 19]); + /// ``` + #[track_caller] + fn fold_chunks_with<T, F>( + self, + chunk_size: usize, + init: T, + fold_op: F, + ) -> FoldChunksWith<Self, T, F> + where + T: Send + Clone, + F: Fn(T, Self::Item) -> T + Send + Sync, + { + assert!(chunk_size != 0, "chunk_size must not be zero"); + FoldChunksWith::new(self, chunk_size, init, fold_op) + } + + /// Lexicographically compares the elements of this `ParallelIterator` with those of + /// another. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// use std::cmp::Ordering::*; + /// + /// let x = vec![1, 2, 3]; + /// assert_eq!(x.par_iter().cmp(&vec![1, 3, 0]), Less); + /// assert_eq!(x.par_iter().cmp(&vec![1, 2, 3]), Equal); + /// assert_eq!(x.par_iter().cmp(&vec![1, 2]), Greater); + /// ``` + fn cmp<I>(self, other: I) -> Ordering + where + I: IntoParallelIterator<Item = Self::Item>, + I::Iter: IndexedParallelIterator, + Self::Item: Ord, + { + #[inline] + fn ordering<T: Ord>((x, y): (T, T)) -> Ordering { + Ord::cmp(&x, &y) + } + + #[inline] + fn inequal(&ord: &Ordering) -> bool { + ord != Ordering::Equal + } + + let other = other.into_par_iter(); + let ord_len = self.len().cmp(&other.len()); + self.zip(other) + .map(ordering) + .find_first(inequal) + .unwrap_or(ord_len) + } + + /// Lexicographically compares the elements of this `ParallelIterator` with those of + /// another. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// use std::cmp::Ordering::*; + /// use std::f64::NAN; + /// + /// let x = vec![1.0, 2.0, 3.0]; + /// assert_eq!(x.par_iter().partial_cmp(&vec![1.0, 3.0, 0.0]), Some(Less)); + /// assert_eq!(x.par_iter().partial_cmp(&vec![1.0, 2.0, 3.0]), Some(Equal)); + /// assert_eq!(x.par_iter().partial_cmp(&vec![1.0, 2.0]), Some(Greater)); + /// assert_eq!(x.par_iter().partial_cmp(&vec![1.0, NAN]), None); + /// ``` + fn partial_cmp<I>(self, other: I) -> Option<Ordering> + where + I: IntoParallelIterator, + I::Iter: IndexedParallelIterator, + Self::Item: PartialOrd<I::Item>, + { + #[inline] + fn ordering<T: PartialOrd<U>, U>((x, y): (T, U)) -> Option<Ordering> { + PartialOrd::partial_cmp(&x, &y) + } + + #[inline] + fn inequal(&ord: &Option<Ordering>) -> bool { + ord != Some(Ordering::Equal) + } + + let other = other.into_par_iter(); + let ord_len = self.len().cmp(&other.len()); + self.zip(other) + .map(ordering) + .find_first(inequal) + .unwrap_or(Some(ord_len)) + } + + /// Determines if the elements of this `ParallelIterator` + /// are equal to those of another + fn eq<I>(self, other: I) -> bool + where + I: IntoParallelIterator, + I::Iter: IndexedParallelIterator, + Self::Item: PartialEq<I::Item>, + { + #[inline] + fn eq<T: PartialEq<U>, U>((x, y): (T, U)) -> bool { + PartialEq::eq(&x, &y) + } + + let other = other.into_par_iter(); + self.len() == other.len() && self.zip(other).all(eq) + } + + /// Determines if the elements of this `ParallelIterator` + /// are unequal to those of another + fn ne<I>(self, other: I) -> bool + where + I: IntoParallelIterator, + I::Iter: IndexedParallelIterator, + Self::Item: PartialEq<I::Item>, + { + !self.eq(other) + } + + /// Determines if the elements of this `ParallelIterator` + /// are lexicographically less than those of another. + fn lt<I>(self, other: I) -> bool + where + I: IntoParallelIterator, + I::Iter: IndexedParallelIterator, + Self::Item: PartialOrd<I::Item>, + { + self.partial_cmp(other) == Some(Ordering::Less) + } + + /// Determines if the elements of this `ParallelIterator` + /// are less or equal to those of another. + fn le<I>(self, other: I) -> bool + where + I: IntoParallelIterator, + I::Iter: IndexedParallelIterator, + Self::Item: PartialOrd<I::Item>, + { + let ord = self.partial_cmp(other); + ord == Some(Ordering::Equal) || ord == Some(Ordering::Less) + } + + /// Determines if the elements of this `ParallelIterator` + /// are lexicographically greater than those of another. + fn gt<I>(self, other: I) -> bool + where + I: IntoParallelIterator, + I::Iter: IndexedParallelIterator, + Self::Item: PartialOrd<I::Item>, + { + self.partial_cmp(other) == Some(Ordering::Greater) + } + + /// Determines if the elements of this `ParallelIterator` + /// are less or equal to those of another. + fn ge<I>(self, other: I) -> bool + where + I: IntoParallelIterator, + I::Iter: IndexedParallelIterator, + Self::Item: PartialOrd<I::Item>, + { + let ord = self.partial_cmp(other); + ord == Some(Ordering::Equal) || ord == Some(Ordering::Greater) + } + + /// Yields an index along with each item. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let chars = vec!['a', 'b', 'c']; + /// let result: Vec<_> = chars + /// .into_par_iter() + /// .enumerate() + /// .collect(); + /// + /// assert_eq!(result, [(0, 'a'), (1, 'b'), (2, 'c')]); + /// ``` + fn enumerate(self) -> Enumerate<Self> { + Enumerate::new(self) + } + + /// Creates an iterator that steps by the given amount + /// + /// # Examples + /// + /// ``` + ///use rayon::prelude::*; + /// + /// let range = (3..10); + /// let result: Vec<i32> = range + /// .into_par_iter() + /// .step_by(3) + /// .collect(); + /// + /// assert_eq!(result, [3, 6, 9]) + /// ``` + fn step_by(self, step: usize) -> StepBy<Self> { + StepBy::new(self, step) + } + + /// Creates an iterator that skips the first `n` elements. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let result: Vec<_> = (0..100) + /// .into_par_iter() + /// .skip(95) + /// .collect(); + /// + /// assert_eq!(result, [95, 96, 97, 98, 99]); + /// ``` + fn skip(self, n: usize) -> Skip<Self> { + Skip::new(self, n) + } + + /// Creates an iterator that yields the first `n` elements. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let result: Vec<_> = (0..100) + /// .into_par_iter() + /// .take(5) + /// .collect(); + /// + /// assert_eq!(result, [0, 1, 2, 3, 4]); + /// ``` + fn take(self, n: usize) -> Take<Self> { + Take::new(self, n) + } + + /// Searches for **some** item in the parallel iterator that + /// matches the given predicate, and returns its index. Like + /// `ParallelIterator::find_any`, the parallel search will not + /// necessarily find the **first** match, and once a match is + /// found we'll attempt to stop processing any more. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [1, 2, 3, 3]; + /// + /// let i = a.par_iter().position_any(|&x| x == 3).expect("found"); + /// assert!(i == 2 || i == 3); + /// + /// assert_eq!(a.par_iter().position_any(|&x| x == 100), None); + /// ``` + fn position_any<P>(self, predicate: P) -> Option<usize> + where + P: Fn(Self::Item) -> bool + Sync + Send, + { + #[inline] + fn check(&(_, p): &(usize, bool)) -> bool { + p + } + + let (i, _) = self.map(predicate).enumerate().find_any(check)?; + Some(i) + } + + /// Searches for the sequentially **first** item in the parallel iterator + /// that matches the given predicate, and returns its index. + /// + /// Like `ParallelIterator::find_first`, once a match is found, + /// all attempts to the right of the match will be stopped, while + /// attempts to the left must continue in case an earlier match + /// is found. + /// + /// Note that not all parallel iterators have a useful order, much like + /// sequential `HashMap` iteration, so "first" may be nebulous. If you + /// just want the first match that discovered anywhere in the iterator, + /// `position_any` is a better choice. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [1, 2, 3, 3]; + /// + /// assert_eq!(a.par_iter().position_first(|&x| x == 3), Some(2)); + /// + /// assert_eq!(a.par_iter().position_first(|&x| x == 100), None); + /// ``` + fn position_first<P>(self, predicate: P) -> Option<usize> + where + P: Fn(Self::Item) -> bool + Sync + Send, + { + #[inline] + fn check(&(_, p): &(usize, bool)) -> bool { + p + } + + let (i, _) = self.map(predicate).enumerate().find_first(check)?; + Some(i) + } + + /// Searches for the sequentially **last** item in the parallel iterator + /// that matches the given predicate, and returns its index. + /// + /// Like `ParallelIterator::find_last`, once a match is found, + /// all attempts to the left of the match will be stopped, while + /// attempts to the right must continue in case a later match + /// is found. + /// + /// Note that not all parallel iterators have a useful order, much like + /// sequential `HashMap` iteration, so "last" may be nebulous. When the + /// order doesn't actually matter to you, `position_any` is a better + /// choice. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let a = [1, 2, 3, 3]; + /// + /// assert_eq!(a.par_iter().position_last(|&x| x == 3), Some(3)); + /// + /// assert_eq!(a.par_iter().position_last(|&x| x == 100), None); + /// ``` + fn position_last<P>(self, predicate: P) -> Option<usize> + where + P: Fn(Self::Item) -> bool + Sync + Send, + { + #[inline] + fn check(&(_, p): &(usize, bool)) -> bool { + p + } + + let (i, _) = self.map(predicate).enumerate().find_last(check)?; + Some(i) + } + + #[doc(hidden)] + #[deprecated( + note = "parallel `position` does not search in order -- use `position_any`, \\ + `position_first`, or `position_last`" + )] + fn position<P>(self, predicate: P) -> Option<usize> + where + P: Fn(Self::Item) -> bool + Sync + Send, + { + self.position_any(predicate) + } + + /// Searches for items in the parallel iterator that match the given + /// predicate, and returns their indices. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let primes = vec![2, 3, 5, 7, 11, 13, 17, 19, 23, 29]; + /// + /// // Find the positions of primes congruent to 1 modulo 6 + /// let p1mod6: Vec<_> = primes.par_iter().positions(|&p| p % 6 == 1).collect(); + /// assert_eq!(p1mod6, [3, 5, 7]); // primes 7, 13, and 19 + /// + /// // Find the positions of primes congruent to 5 modulo 6 + /// let p5mod6: Vec<_> = primes.par_iter().positions(|&p| p % 6 == 5).collect(); + /// assert_eq!(p5mod6, [2, 4, 6, 8, 9]); // primes 5, 11, 17, 23, and 29 + /// ``` + fn positions<P>(self, predicate: P) -> Positions<Self, P> + where + P: Fn(Self::Item) -> bool + Sync + Send, + { + Positions::new(self, predicate) + } + + /// Produces a new iterator with the elements of this iterator in + /// reverse order. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let result: Vec<_> = (0..5) + /// .into_par_iter() + /// .rev() + /// .collect(); + /// + /// assert_eq!(result, [4, 3, 2, 1, 0]); + /// ``` + fn rev(self) -> Rev<Self> { + Rev::new(self) + } + + /// Sets the minimum length of iterators desired to process in each + /// rayon job. Rayon will not split any smaller than this length, but + /// of course an iterator could already be smaller to begin with. + /// + /// Producers like `zip` and `interleave` will use greater of the two + /// minimums. + /// Chained iterators and iterators inside `flat_map` may each use + /// their own minimum length. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let min = (0..1_000_000) + /// .into_par_iter() + /// .with_min_len(1234) + /// .fold(|| 0, |acc, _| acc + 1) // count how many are in this segment + /// .min().unwrap(); + /// + /// assert!(min >= 1234); + /// ``` + fn with_min_len(self, min: usize) -> MinLen<Self> { + MinLen::new(self, min) + } + + /// Sets the maximum length of iterators desired to process in each + /// rayon job. Rayon will try to split at least below this length, + /// unless that would put it below the length from `with_min_len()`. + /// For example, given min=10 and max=15, a length of 16 will not be + /// split any further. + /// + /// Producers like `zip` and `interleave` will use lesser of the two + /// maximums. + /// Chained iterators and iterators inside `flat_map` may each use + /// their own maximum length. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let max = (0..1_000_000) + /// .into_par_iter() + /// .with_max_len(1234) + /// .fold(|| 0, |acc, _| acc + 1) // count how many are in this segment + /// .max().unwrap(); + /// + /// assert!(max <= 1234); + /// ``` + fn with_max_len(self, max: usize) -> MaxLen<Self> { + MaxLen::new(self, max) + } + + /// Produces an exact count of how many items this iterator will + /// produce, presuming no panic occurs. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let par_iter = (0..100).into_par_iter().zip(vec![0; 10]); + /// assert_eq!(par_iter.len(), 10); + /// + /// let vec: Vec<_> = par_iter.collect(); + /// assert_eq!(vec.len(), 10); + /// ``` + fn len(&self) -> usize; + + /// Internal method used to define the behavior of this parallel + /// iterator. You should not need to call this directly. + /// + /// This method causes the iterator `self` to start producing + /// items and to feed them to the consumer `consumer` one by one. + /// It may split the consumer before doing so to create the + /// opportunity to produce in parallel. If a split does happen, it + /// will inform the consumer of the index where the split should + /// occur (unlike `ParallelIterator::drive_unindexed()`). + /// + /// See the [README] for more details on the internals of parallel + /// iterators. + /// + /// [README]: https://github.com/rayon-rs/rayon/blob/master/src/iter/plumbing/README.md + fn drive<C: Consumer<Self::Item>>(self, consumer: C) -> C::Result; + + /// Internal method used to define the behavior of this parallel + /// iterator. You should not need to call this directly. + /// + /// This method converts the iterator into a producer P and then + /// invokes `callback.callback()` with P. Note that the type of + /// this producer is not defined as part of the API, since + /// `callback` must be defined generically for all producers. This + /// allows the producer type to contain references; it also means + /// that parallel iterators can adjust that type without causing a + /// breaking change. + /// + /// See the [README] for more details on the internals of parallel + /// iterators. + /// + /// [README]: https://github.com/rayon-rs/rayon/blob/master/src/iter/plumbing/README.md + fn with_producer<CB: ProducerCallback<Self::Item>>(self, callback: CB) -> CB::Output; +} + +/// `FromParallelIterator` implements the creation of a collection +/// from a [`ParallelIterator`]. By implementing +/// `FromParallelIterator` for a given type, you define how it will be +/// created from an iterator. +/// +/// `FromParallelIterator` is used through [`ParallelIterator`]'s [`collect()`] method. +/// +/// [`ParallelIterator`]: trait.ParallelIterator.html +/// [`collect()`]: trait.ParallelIterator.html#method.collect +/// +/// # Examples +/// +/// Implementing `FromParallelIterator` for your type: +/// +/// ``` +/// use rayon::prelude::*; +/// use std::mem; +/// +/// struct BlackHole { +/// mass: usize, +/// } +/// +/// impl<T: Send> FromParallelIterator<T> for BlackHole { +/// fn from_par_iter<I>(par_iter: I) -> Self +/// where I: IntoParallelIterator<Item = T> +/// { +/// let par_iter = par_iter.into_par_iter(); +/// BlackHole { +/// mass: par_iter.count() * mem::size_of::<T>(), +/// } +/// } +/// } +/// +/// let bh: BlackHole = (0i32..1000).into_par_iter().collect(); +/// assert_eq!(bh.mass, 4000); +/// ``` +pub trait FromParallelIterator<T> +where + T: Send, +{ + /// Creates an instance of the collection from the parallel iterator `par_iter`. + /// + /// If your collection is not naturally parallel, the easiest (and + /// fastest) way to do this is often to collect `par_iter` into a + /// [`LinkedList`] or other intermediate data structure and then + /// sequentially extend your collection. However, a more 'native' + /// technique is to use the [`par_iter.fold`] or + /// [`par_iter.fold_with`] methods to create the collection. + /// Alternatively, if your collection is 'natively' parallel, you + /// can use `par_iter.for_each` to process each element in turn. + /// + /// [`LinkedList`]: https://doc.rust-lang.org/std/collections/struct.LinkedList.html + /// [`par_iter.fold`]: trait.ParallelIterator.html#method.fold + /// [`par_iter.fold_with`]: trait.ParallelIterator.html#method.fold_with + /// [`par_iter.for_each`]: trait.ParallelIterator.html#method.for_each + fn from_par_iter<I>(par_iter: I) -> Self + where + I: IntoParallelIterator<Item = T>; +} + +/// `ParallelExtend` extends an existing collection with items from a [`ParallelIterator`]. +/// +/// [`ParallelIterator`]: trait.ParallelIterator.html +/// +/// # Examples +/// +/// Implementing `ParallelExtend` for your type: +/// +/// ``` +/// use rayon::prelude::*; +/// use std::mem; +/// +/// struct BlackHole { +/// mass: usize, +/// } +/// +/// impl<T: Send> ParallelExtend<T> for BlackHole { +/// fn par_extend<I>(&mut self, par_iter: I) +/// where I: IntoParallelIterator<Item = T> +/// { +/// let par_iter = par_iter.into_par_iter(); +/// self.mass += par_iter.count() * mem::size_of::<T>(); +/// } +/// } +/// +/// let mut bh = BlackHole { mass: 0 }; +/// bh.par_extend(0i32..1000); +/// assert_eq!(bh.mass, 4000); +/// bh.par_extend(0i64..10); +/// assert_eq!(bh.mass, 4080); +/// ``` +pub trait ParallelExtend<T> +where + T: Send, +{ + /// Extends an instance of the collection with the elements drawn + /// from the parallel iterator `par_iter`. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let mut vec = vec![]; + /// vec.par_extend(0..5); + /// vec.par_extend((0..5).into_par_iter().map(|i| i * i)); + /// assert_eq!(vec, [0, 1, 2, 3, 4, 0, 1, 4, 9, 16]); + /// ``` + fn par_extend<I>(&mut self, par_iter: I) + where + I: IntoParallelIterator<Item = T>; +} + +/// `ParallelDrainFull` creates a parallel iterator that moves all items +/// from a collection while retaining the original capacity. +/// +/// Types which are indexable typically implement [`ParallelDrainRange`] +/// instead, where you can drain fully with `par_drain(..)`. +/// +/// [`ParallelDrainRange`]: trait.ParallelDrainRange.html +pub trait ParallelDrainFull { + /// The draining parallel iterator type that will be created. + type Iter: ParallelIterator<Item = Self::Item>; + + /// The type of item that the parallel iterator will produce. + /// This is usually the same as `IntoParallelIterator::Item`. + type Item: Send; + + /// Returns a draining parallel iterator over an entire collection. + /// + /// When the iterator is dropped, all items are removed, even if the + /// iterator was not fully consumed. If the iterator is leaked, for example + /// using `std::mem::forget`, it is unspecified how many items are removed. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// use std::collections::{BinaryHeap, HashSet}; + /// + /// let squares: HashSet<i32> = (0..10).map(|x| x * x).collect(); + /// + /// let mut heap: BinaryHeap<_> = squares.iter().copied().collect(); + /// assert_eq!( + /// // heaps are drained in arbitrary order + /// heap.par_drain() + /// .inspect(|x| assert!(squares.contains(x))) + /// .count(), + /// squares.len(), + /// ); + /// assert!(heap.is_empty()); + /// assert!(heap.capacity() >= squares.len()); + /// ``` + fn par_drain(self) -> Self::Iter; +} + +/// `ParallelDrainRange` creates a parallel iterator that moves a range of items +/// from a collection while retaining the original capacity. +/// +/// Types which are not indexable may implement [`ParallelDrainFull`] instead. +/// +/// [`ParallelDrainFull`]: trait.ParallelDrainFull.html +pub trait ParallelDrainRange<Idx = usize> { + /// The draining parallel iterator type that will be created. + type Iter: ParallelIterator<Item = Self::Item>; + + /// The type of item that the parallel iterator will produce. + /// This is usually the same as `IntoParallelIterator::Item`. + type Item: Send; + + /// Returns a draining parallel iterator over a range of the collection. + /// + /// When the iterator is dropped, all items in the range are removed, even + /// if the iterator was not fully consumed. If the iterator is leaked, for + /// example using `std::mem::forget`, it is unspecified how many items are + /// removed. + /// + /// # Examples + /// + /// ``` + /// use rayon::prelude::*; + /// + /// let squares: Vec<i32> = (0..10).map(|x| x * x).collect(); + /// + /// println!("RangeFull"); + /// let mut vec = squares.clone(); + /// assert!(vec.par_drain(..) + /// .eq(squares.par_iter().copied())); + /// assert!(vec.is_empty()); + /// assert!(vec.capacity() >= squares.len()); + /// + /// println!("RangeFrom"); + /// let mut vec = squares.clone(); + /// assert!(vec.par_drain(5..) + /// .eq(squares[5..].par_iter().copied())); + /// assert_eq!(&vec[..], &squares[..5]); + /// assert!(vec.capacity() >= squares.len()); + /// + /// println!("RangeTo"); + /// let mut vec = squares.clone(); + /// assert!(vec.par_drain(..5) + /// .eq(squares[..5].par_iter().copied())); + /// assert_eq!(&vec[..], &squares[5..]); + /// assert!(vec.capacity() >= squares.len()); + /// + /// println!("RangeToInclusive"); + /// let mut vec = squares.clone(); + /// assert!(vec.par_drain(..=5) + /// .eq(squares[..=5].par_iter().copied())); + /// assert_eq!(&vec[..], &squares[6..]); + /// assert!(vec.capacity() >= squares.len()); + /// + /// println!("Range"); + /// let mut vec = squares.clone(); + /// assert!(vec.par_drain(3..7) + /// .eq(squares[3..7].par_iter().copied())); + /// assert_eq!(&vec[..3], &squares[..3]); + /// assert_eq!(&vec[3..], &squares[7..]); + /// assert!(vec.capacity() >= squares.len()); + /// + /// println!("RangeInclusive"); + /// let mut vec = squares.clone(); + /// assert!(vec.par_drain(3..=7) + /// .eq(squares[3..=7].par_iter().copied())); + /// assert_eq!(&vec[..3], &squares[..3]); + /// assert_eq!(&vec[3..], &squares[8..]); + /// assert!(vec.capacity() >= squares.len()); + /// ``` + fn par_drain<R: RangeBounds<Idx>>(self, range: R) -> Self::Iter; +} + +/// We hide the `Try` trait in a private module, as it's only meant to be a +/// stable clone of the standard library's `Try` trait, as yet unstable. +mod private { + use std::convert::Infallible; + use std::ops::ControlFlow::{self, Break, Continue}; + use std::task::Poll; + + /// Clone of `std::ops::Try`. + /// + /// Implementing this trait is not permitted outside of `rayon`. + pub trait Try { + private_decl! {} + + type Output; + type Residual; + + fn from_output(output: Self::Output) -> Self; + + fn from_residual(residual: Self::Residual) -> Self; + + fn branch(self) -> ControlFlow<Self::Residual, Self::Output>; + } + + impl<B, C> Try for ControlFlow<B, C> { + private_impl! {} + + type Output = C; + type Residual = ControlFlow<B, Infallible>; + + fn from_output(output: Self::Output) -> Self { + Continue(output) + } + + fn from_residual(residual: Self::Residual) -> Self { + match residual { + Break(b) => Break(b), + Continue(_) => unreachable!(), + } + } + + fn branch(self) -> ControlFlow<Self::Residual, Self::Output> { + match self { + Continue(c) => Continue(c), + Break(b) => Break(Break(b)), + } + } + } + + impl<T> Try for Option<T> { + private_impl! {} + + type Output = T; + type Residual = Option<Infallible>; + + fn from_output(output: Self::Output) -> Self { + Some(output) + } + + fn from_residual(residual: Self::Residual) -> Self { + match residual { + None => None, + Some(_) => unreachable!(), + } + } + + fn branch(self) -> ControlFlow<Self::Residual, Self::Output> { + match self { + Some(c) => Continue(c), + None => Break(None), + } + } + } + + impl<T, E> Try for Result<T, E> { + private_impl! {} + + type Output = T; + type Residual = Result<Infallible, E>; + + fn from_output(output: Self::Output) -> Self { + Ok(output) + } + + fn from_residual(residual: Self::Residual) -> Self { + match residual { + Err(e) => Err(e), + Ok(_) => unreachable!(), + } + } + + fn branch(self) -> ControlFlow<Self::Residual, Self::Output> { + match self { + Ok(c) => Continue(c), + Err(e) => Break(Err(e)), + } + } + } + + impl<T, E> Try for Poll<Result<T, E>> { + private_impl! {} + + type Output = Poll<T>; + type Residual = Result<Infallible, E>; + + fn from_output(output: Self::Output) -> Self { + output.map(Ok) + } + + fn from_residual(residual: Self::Residual) -> Self { + match residual { + Err(e) => Poll::Ready(Err(e)), + Ok(_) => unreachable!(), + } + } + + fn branch(self) -> ControlFlow<Self::Residual, Self::Output> { + match self { + Poll::Pending => Continue(Poll::Pending), + Poll::Ready(Ok(c)) => Continue(Poll::Ready(c)), + Poll::Ready(Err(e)) => Break(Err(e)), + } + } + } + + impl<T, E> Try for Poll<Option<Result<T, E>>> { + private_impl! {} + + type Output = Poll<Option<T>>; + type Residual = Result<Infallible, E>; + + fn from_output(output: Self::Output) -> Self { + match output { + Poll::Ready(o) => Poll::Ready(o.map(Ok)), + Poll::Pending => Poll::Pending, + } + } + + fn from_residual(residual: Self::Residual) -> Self { + match residual { + Err(e) => Poll::Ready(Some(Err(e))), + Ok(_) => unreachable!(), + } + } + + fn branch(self) -> ControlFlow<Self::Residual, Self::Output> { + match self { + Poll::Pending => Continue(Poll::Pending), + Poll::Ready(None) => Continue(Poll::Ready(None)), + Poll::Ready(Some(Ok(c))) => Continue(Poll::Ready(Some(c))), + Poll::Ready(Some(Err(e))) => Break(Err(e)), + } + } + } +} |