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authorDaniel Baumann <daniel.baumann@progress-linux.org>2024-04-19 00:47:55 +0000
committerDaniel Baumann <daniel.baumann@progress-linux.org>2024-04-19 00:47:55 +0000
commit26a029d407be480d791972afb5975cf62c9360a6 (patch)
treef435a8308119effd964b339f76abb83a57c29483 /third_party/rust/rayon/src/iter/mod.rs
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Adding upstream version 124.0.1.upstream/124.0.1
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
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+//! 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 splitter;
+mod step_by;
+mod sum;
+mod take;
+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,
+ splitter::{split, Split},
+ step_by::StepBy,
+ take::Take,
+ 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(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().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)
+ }
+
+ /// 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 truncated 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 truncated
+ /// 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 truncated 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 truncated
+ /// 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]]);
+ /// ```
+ 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)),
+ }
+ }
+ }
+}