Initial import of rayon-1.5.0. am: 041839ceab am: d836dd6404 am: 7522a9ba00

Original change: https://android-review.googlesource.com/c/platform/external/rust/crates/rayon/+/1622436

Change-Id: I94b0e06d9da131d6f98db436ad1a178dfff2ec90

1 files changed, 3121 insertions, 0 deletions

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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]: http://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 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 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},
+    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},
+    take::Take,
+    try_fold::{TryFold, TryFoldWith},
+    update::Update,
+    while_some::WhileSome,
+    zip::Zip,
+    zip_eq::ZipEq,
+};
+
+mod step_by;
+#[cfg(step_by)]
+pub use self::step_by::StepBy;
+
+/// `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<Ok = ()> + Send,
+    {
+        fn ok<R: Try<Ok = ()>>(_: (), _: ()) -> R {
+            R::from_ok(())
+        }
+
+        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<Ok = ()> + Send,
+    {
+        fn ok<R: Try<Ok = ()>>(_: (), _: ()) -> R {
+            R::from_ok(())
+        }
+
+        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<Ok = ()> + Send,
+    {
+        fn ok<R: Try<Ok = ()>>(_: (), _: ()) -> R {
+            R::from_ok(())
+        }
+
+        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 analagous 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<Ok = 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<Ok = 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 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<Ok = 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<Ok = 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);
+    /// ```
+    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 inferrence 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]: 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
+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());
+    /// ```
+    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());
+        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)
+    }
+
+    /// 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])
+    /// ```
+    ///
+    /// # Compatibility
+    ///
+    /// This method is only available on Rust 1.38 or greater.
+    #[cfg(step_by)]
+    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
+    /// thread.  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
+    /// thread.  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]: 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]: 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 {
+    /// Clone of `std::ops::Try`.
+    ///
+    /// Implementing this trait is not permitted outside of `rayon`.
+    pub trait Try {
+        private_decl! {}
+
+        type Ok;
+        type Error;
+        fn into_result(self) -> Result<Self::Ok, Self::Error>;
+        fn from_ok(v: Self::Ok) -> Self;
+        fn from_error(v: Self::Error) -> Self;
+    }
+
+    impl<T> Try for Option<T> {
+        private_impl! {}
+
+        type Ok = T;
+        type Error = ();
+
+        fn into_result(self) -> Result<T, ()> {
+            self.ok_or(())
+        }
+        fn from_ok(v: T) -> Self {
+            Some(v)
+        }
+        fn from_error(_: ()) -> Self {
+            None
+        }
+    }
+
+    impl<T, E> Try for Result<T, E> {
+        private_impl! {}
+
+        type Ok = T;
+        type Error = E;
+
+        fn into_result(self) -> Result<T, E> {
+            self
+        }
+        fn from_ok(v: T) -> Self {
+            Ok(v)
+        }
+        fn from_error(v: E) -> Self {
+            Err(v)
+        }
+    }
+}