rust/src/libcore/iter/mod.rs

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// Copyright 2013-2016 The Rust Project Developers. See the COPYRIGHT
// file at the top-level directory of this distribution and at
// http://rust-lang.org/COPYRIGHT.
//
// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
// http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
// <LICENSE-MIT or http://opensource.org/licenses/MIT>, at your
// option. This file may not be copied, modified, or distributed
// except according to those terms.
//! Composable external iteration.
//!
//! If you've found yourself with a collection of some kind, and needed to
//! perform an operation on the elements of said collection, you'll quickly run
//! into 'iterators'. Iterators are heavily used in idiomatic Rust code, so
//! it's worth becoming familiar with them.
//!
//! Before explaining more, let's talk about how this module is structured:
//!
//! # Organization
//!
//! This module is largely organized by type:
//!
//! * [Traits] are the core portion: these traits define what kind of iterators
//! exist and what you can do with them. The methods of these traits are worth
//! putting some extra study time into.
//! * [Functions] provide some helpful ways to create some basic iterators.
//! * [Structs] are often the return types of the various methods on this
//! module's traits. You'll usually want to look at the method that creates
//! the `struct`, rather than the `struct` itself. For more detail about why,
//! see '[Implementing Iterator](#implementing-iterator)'.
//!
//! [Traits]: #traits
//! [Functions]: #functions
//! [Structs]: #structs
//!
//! That's it! Let's dig into iterators.
//!
//! # Iterator
//!
//! The heart and soul of this module is the [`Iterator`] trait. The core of
//! [`Iterator`] looks like this:
//!
//! ```
//! trait Iterator {
//! type Item;
//! fn next(&mut self) -> Option<Self::Item>;
//! }
//! ```
//!
//! An iterator has a method, [`next`], which when called, returns an
//! [`Option`]`<Item>`. [`next`] will return `Some(Item)` as long as there
//! are elements, and once they've all been exhausted, will return `None` to
//! indicate that iteration is finished. Individual iterators may choose to
//! resume iteration, and so calling [`next`] again may or may not eventually
//! start returning `Some(Item)` again at some point.
//!
//! [`Iterator`]'s full definition includes a number of other methods as well,
//! but they are default methods, built on top of [`next`], and so you get
//! them for free.
//!
//! Iterators are also composable, and it's common to chain them together to do
//! more complex forms of processing. See the [Adapters](#adapters) section
//! below for more details.
//!
//! [`Iterator`]: trait.Iterator.html
//! [`next`]: trait.Iterator.html#tymethod.next
//! [`Option`]: ../../std/option/enum.Option.html
//!
//! # The three forms of iteration
//!
//! There are three common methods which can create iterators from a collection:
//!
//! * `iter()`, which iterates over `&T`.
//! * `iter_mut()`, which iterates over `&mut T`.
//! * `into_iter()`, which iterates over `T`.
//!
//! Various things in the standard library may implement one or more of the
//! three, where appropriate.
//!
//! # Implementing Iterator
//!
//! Creating an iterator of your own involves two steps: creating a `struct` to
//! hold the iterator's state, and then `impl`ementing [`Iterator`] for that
//! `struct`. This is why there are so many `struct`s in this module: there is
//! one for each iterator and iterator adapter.
//!
//! Let's make an iterator named `Counter` which counts from `1` to `5`:
//!
//! ```
//! // First, the struct:
//!
//! /// An iterator which counts from one to five
//! struct Counter {
//! count: usize,
//! }
//!
//! // we want our count to start at one, so let's add a new() method to help.
//! // This isn't strictly necessary, but is convenient. Note that we start
//! // `count` at zero, we'll see why in `next()`'s implementation below.
//! impl Counter {
//! fn new() -> Counter {
//! Counter { count: 0 }
//! }
//! }
//!
//! // Then, we implement `Iterator` for our `Counter`:
//!
//! impl Iterator for Counter {
//! // we will be counting with usize
//! type Item = usize;
//!
//! // next() is the only required method
//! fn next(&mut self) -> Option<usize> {
//! // increment our count. This is why we started at zero.
//! self.count += 1;
//!
//! // check to see if we've finished counting or not.
//! if self.count < 6 {
//! Some(self.count)
//! } else {
//! None
//! }
//! }
//! }
//!
//! // And now we can use it!
//!
//! let mut counter = Counter::new();
//!
//! let x = counter.next().unwrap();
//! println!("{}", x);
//!
//! let x = counter.next().unwrap();
//! println!("{}", x);
//!
//! let x = counter.next().unwrap();
//! println!("{}", x);
//!
//! let x = counter.next().unwrap();
//! println!("{}", x);
//!
//! let x = counter.next().unwrap();
//! println!("{}", x);
//! ```
//!
//! This will print `1` through `5`, each on their own line.
//!
//! Calling `next()` this way gets repetitive. Rust has a construct which can
//! call `next()` on your iterator, until it reaches `None`. Let's go over that
//! next.
//!
//! # for Loops and IntoIterator
//!
//! Rust's `for` loop syntax is actually sugar for iterators. Here's a basic
//! example of `for`:
//!
//! ```
//! let values = vec![1, 2, 3, 4, 5];
//!
//! for x in values {
//! println!("{}", x);
//! }
//! ```
//!
//! This will print the numbers one through five, each on their own line. But
//! you'll notice something here: we never called anything on our vector to
//! produce an iterator. What gives?
//!
//! There's a trait in the standard library for converting something into an
//! iterator: [`IntoIterator`]. This trait has one method, [`into_iter`],
//! which converts the thing implementing [`IntoIterator`] into an iterator.
//! Let's take a look at that `for` loop again, and what the compiler converts
//! it into:
//!
//! [`IntoIterator`]: trait.IntoIterator.html
//! [`into_iter`]: trait.IntoIterator.html#tymethod.into_iter
//!
//! ```
//! let values = vec![1, 2, 3, 4, 5];
//!
//! for x in values {
//! println!("{}", x);
//! }
//! ```
//!
//! Rust de-sugars this into:
//!
//! ```
//! let values = vec![1, 2, 3, 4, 5];
//! {
//! let result = match IntoIterator::into_iter(values) {
//! mut iter => loop {
//! let next;
//! match iter.next() {
//! Some(val) => next = val,
//! None => break,
//! };
//! let x = next;
//! let () = { println!("{}", x); };
//! },
//! };
//! result
//! }
//! ```
//!
//! First, we call `into_iter()` on the value. Then, we match on the iterator
//! that returns, calling [`next`] over and over until we see a `None`. At
//! that point, we `break` out of the loop, and we're done iterating.
//!
//! There's one more subtle bit here: the standard library contains an
//! interesting implementation of [`IntoIterator`]:
//!
//! ```ignore (only-for-syntax-highlight)
//! impl<I: Iterator> IntoIterator for I
//! ```
//!
//! In other words, all [`Iterator`]s implement [`IntoIterator`], by just
//! returning themselves. This means two things:
//!
//! 1. If you're writing an [`Iterator`], you can use it with a `for` loop.
//! 2. If you're creating a collection, implementing [`IntoIterator`] for it
//! will allow your collection to be used with the `for` loop.
//!
//! # Adapters
//!
//! Functions which take an [`Iterator`] and return another [`Iterator`] are
//! often called 'iterator adapters', as they're a form of the 'adapter
//! pattern'.
//!
//! Common iterator adapters include [`map`], [`take`], and [`filter`].
//! For more, see their documentation.
//!
//! [`map`]: trait.Iterator.html#method.map
//! [`take`]: trait.Iterator.html#method.take
//! [`filter`]: trait.Iterator.html#method.filter
//!
//! # Laziness
//!
//! Iterators (and iterator [adapters](#adapters)) are *lazy*. This means that
//! just creating an iterator doesn't _do_ a whole lot. Nothing really happens
//! until you call [`next`]. This is sometimes a source of confusion when
//! creating an iterator solely for its side effects. For example, the [`map`]
//! method calls a closure on each element it iterates over:
//!
//! ```
//! # #![allow(unused_must_use)]
//! let v = vec![1, 2, 3, 4, 5];
//! v.iter().map(|x| println!("{}", x));
//! ```
//!
//! This will not print any values, as we only created an iterator, rather than
//! using it. The compiler will warn us about this kind of behavior:
//!
//! ```text
//! warning: unused result which must be used: iterator adaptors are lazy and
//! do nothing unless consumed
//! ```
//!
//! The idiomatic way to write a [`map`] for its side effects is to use a
//! `for` loop instead:
//!
//! ```
//! let v = vec![1, 2, 3, 4, 5];
//!
//! for x in &v {
//! println!("{}", x);
//! }
//! ```
//!
//! [`map`]: trait.Iterator.html#method.map
//!
//! The two most common ways to evaluate an iterator are to use a `for` loop
//! like this, or using the [`collect`] method to produce a new collection.
//!
//! [`collect`]: trait.Iterator.html#method.collect
//!
//! # Infinity
//!
//! Iterators do not have to be finite. As an example, an open-ended range is
//! an infinite iterator:
//!
//! ```
//! let numbers = 0..;
//! ```
//!
//! It is common to use the [`take`] iterator adapter to turn an infinite
//! iterator into a finite one:
//!
//! ```
//! let numbers = 0..;
//! let five_numbers = numbers.take(5);
//!
//! for number in five_numbers {
//! println!("{}", number);
//! }
//! ```
//!
//! This will print the numbers `0` through `4`, each on their own line.
//!
//! [`take`]: trait.Iterator.html#method.take
#![stable(feature = "rust1", since = "1.0.0")]
use cmp;
use fmt;
use iter_private::TrustedRandomAccess;
use ops::Try;
use usize;
#[stable(feature = "rust1", since = "1.0.0")]
pub use self::iterator::Iterator;
#[unstable(feature = "step_trait",
reason = "likely to be replaced by finer-grained traits",
issue = "42168")]
pub use self::range::Step;
#[stable(feature = "rust1", since = "1.0.0")]
pub use self::sources::{Repeat, repeat};
#[stable(feature = "iter_empty", since = "1.2.0")]
pub use self::sources::{Empty, empty};
#[stable(feature = "iter_once", since = "1.2.0")]
pub use self::sources::{Once, once};
#[stable(feature = "rust1", since = "1.0.0")]
pub use self::traits::{FromIterator, IntoIterator, DoubleEndedIterator, Extend};
#[stable(feature = "rust1", since = "1.0.0")]
pub use self::traits::{ExactSizeIterator, Sum, Product};
#[unstable(feature = "fused", issue = "35602")]
pub use self::traits::FusedIterator;
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#[unstable(feature = "trusted_len", issue = "37572")]
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pub use self::traits::TrustedLen;
mod iterator;
mod range;
mod sources;
mod traits;
/// Transparent newtype used to implement foo methods in terms of try_foo.
/// Important until #43278 is fixed; might be better as `Result<T, !>` later.
struct AlwaysOk<T>(pub T);
impl<T> Try for AlwaysOk<T> {
type Ok = T;
type Error = !;
#[inline]
fn into_result(self) -> Result<Self::Ok, Self::Error> { Ok(self.0) }
#[inline]
fn from_error(v: Self::Error) -> Self { v }
#[inline]
fn from_ok(v: Self::Ok) -> Self { AlwaysOk(v) }
}
/// Used to make try_fold closures more like normal loops
#[derive(PartialEq)]
enum LoopState<C, B> {
Continue(C),
Break(B),
}
impl<C, B> Try for LoopState<C, B> {
type Ok = C;
type Error = B;
#[inline]
fn into_result(self) -> Result<Self::Ok, Self::Error> {
match self {
LoopState::Continue(y) => Ok(y),
LoopState::Break(x) => Err(x),
}
}
#[inline]
fn from_error(v: Self::Error) -> Self { LoopState::Break(v) }
#[inline]
fn from_ok(v: Self::Ok) -> Self { LoopState::Continue(v) }
}
impl<C, B> LoopState<C, B> {
#[inline]
fn break_value(self) -> Option<B> {
match self {
LoopState::Continue(..) => None,
LoopState::Break(x) => Some(x),
}
}
}
impl<R: Try> LoopState<R::Ok, R> {
#[inline]
fn from_try(r: R) -> Self {
match Try::into_result(r) {
Ok(v) => LoopState::Continue(v),
Err(v) => LoopState::Break(Try::from_error(v)),
}
}
#[inline]
fn into_try(self) -> R {
match self {
LoopState::Continue(v) => Try::from_ok(v),
LoopState::Break(v) => v,
}
}
}
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/// A double-ended iterator with the direction inverted.
///
/// This `struct` is created by the [`rev`] method on [`Iterator`]. See its
/// documentation for more.
///
/// [`rev`]: trait.Iterator.html#method.rev
/// [`Iterator`]: trait.Iterator.html
#[derive(Clone, Debug)]
#[must_use = "iterator adaptors are lazy and do nothing unless consumed"]
#[stable(feature = "rust1", since = "1.0.0")]
pub struct Rev<T> {
iter: T
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I> Iterator for Rev<I> where I: DoubleEndedIterator {
type Item = <I as Iterator>::Item;
#[inline]
fn next(&mut self) -> Option<<I as Iterator>::Item> { self.iter.next_back() }
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) { self.iter.size_hint() }
fn try_fold<B, F, R>(&mut self, init: B, f: F) -> R where
Self: Sized, F: FnMut(B, Self::Item) -> R, R: Try<Ok=B>
{
self.iter.try_rfold(init, f)
}
fn fold<Acc, F>(self, init: Acc, f: F) -> Acc
where F: FnMut(Acc, Self::Item) -> Acc,
{
self.iter.rfold(init, f)
}
#[inline]
fn find<P>(&mut self, predicate: P) -> Option<Self::Item>
where P: FnMut(&Self::Item) -> bool
{
self.iter.rfind(predicate)
}
#[inline]
fn rposition<P>(&mut self, predicate: P) -> Option<usize> where
P: FnMut(Self::Item) -> bool
{
self.iter.position(predicate)
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I> DoubleEndedIterator for Rev<I> where I: DoubleEndedIterator {
#[inline]
fn next_back(&mut self) -> Option<<I as Iterator>::Item> { self.iter.next() }
fn try_rfold<B, F, R>(&mut self, init: B, f: F) -> R where
Self: Sized, F: FnMut(B, Self::Item) -> R, R: Try<Ok=B>
{
self.iter.try_fold(init, f)
}
fn rfold<Acc, F>(self, init: Acc, f: F) -> Acc
where F: FnMut(Acc, Self::Item) -> Acc,
{
self.iter.fold(init, f)
}
fn rfind<P>(&mut self, predicate: P) -> Option<Self::Item>
where P: FnMut(&Self::Item) -> bool
{
self.iter.find(predicate)
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I> ExactSizeIterator for Rev<I>
where I: ExactSizeIterator + DoubleEndedIterator
{
fn len(&self) -> usize {
self.iter.len()
}
fn is_empty(&self) -> bool {
self.iter.is_empty()
}
}
#[unstable(feature = "fused", issue = "35602")]
impl<I> FusedIterator for Rev<I>
where I: FusedIterator + DoubleEndedIterator {}
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#[unstable(feature = "trusted_len", issue = "37572")]
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unsafe impl<I> TrustedLen for Rev<I>
where I: TrustedLen + DoubleEndedIterator {}
/// An iterator that clones the elements of an underlying iterator.
///
/// This `struct` is created by the [`cloned`] method on [`Iterator`]. See its
/// documentation for more.
///
/// [`cloned`]: trait.Iterator.html#method.cloned
/// [`Iterator`]: trait.Iterator.html
#[stable(feature = "iter_cloned", since = "1.1.0")]
#[must_use = "iterator adaptors are lazy and do nothing unless consumed"]
#[derive(Clone, Debug)]
pub struct Cloned<I> {
it: I,
}
#[stable(feature = "iter_cloned", since = "1.1.0")]
impl<'a, I, T: 'a> Iterator for Cloned<I>
where I: Iterator<Item=&'a T>, T: Clone
{
type Item = T;
fn next(&mut self) -> Option<T> {
self.it.next().cloned()
}
fn size_hint(&self) -> (usize, Option<usize>) {
self.it.size_hint()
}
fn try_fold<B, F, R>(&mut self, init: B, mut f: F) -> R where
Self: Sized, F: FnMut(B, Self::Item) -> R, R: Try<Ok=B>
{
self.it.try_fold(init, move |acc, elt| f(acc, elt.clone()))
}
fn fold<Acc, F>(self, init: Acc, mut f: F) -> Acc
where F: FnMut(Acc, Self::Item) -> Acc,
{
self.it.fold(init, move |acc, elt| f(acc, elt.clone()))
}
}
#[stable(feature = "iter_cloned", since = "1.1.0")]
impl<'a, I, T: 'a> DoubleEndedIterator for Cloned<I>
where I: DoubleEndedIterator<Item=&'a T>, T: Clone
{
fn next_back(&mut self) -> Option<T> {
self.it.next_back().cloned()
}
fn try_rfold<B, F, R>(&mut self, init: B, mut f: F) -> R where
Self: Sized, F: FnMut(B, Self::Item) -> R, R: Try<Ok=B>
{
self.it.try_rfold(init, move |acc, elt| f(acc, elt.clone()))
}
fn rfold<Acc, F>(self, init: Acc, mut f: F) -> Acc
where F: FnMut(Acc, Self::Item) -> Acc,
{
self.it.rfold(init, move |acc, elt| f(acc, elt.clone()))
}
}
#[stable(feature = "iter_cloned", since = "1.1.0")]
impl<'a, I, T: 'a> ExactSizeIterator for Cloned<I>
where I: ExactSizeIterator<Item=&'a T>, T: Clone
{
fn len(&self) -> usize {
self.it.len()
}
fn is_empty(&self) -> bool {
self.it.is_empty()
}
}
#[unstable(feature = "fused", issue = "35602")]
impl<'a, I, T: 'a> FusedIterator for Cloned<I>
where I: FusedIterator<Item=&'a T>, T: Clone
{}
#[doc(hidden)]
default unsafe impl<'a, I, T: 'a> TrustedRandomAccess for Cloned<I>
where I: TrustedRandomAccess<Item=&'a T>, T: Clone
{
unsafe fn get_unchecked(&mut self, i: usize) -> Self::Item {
self.it.get_unchecked(i).clone()
}
#[inline]
fn may_have_side_effect() -> bool { true }
}
#[doc(hidden)]
unsafe impl<'a, I, T: 'a> TrustedRandomAccess for Cloned<I>
where I: TrustedRandomAccess<Item=&'a T>, T: Copy
{
unsafe fn get_unchecked(&mut self, i: usize) -> Self::Item {
*self.it.get_unchecked(i)
}
#[inline]
fn may_have_side_effect() -> bool { false }
}
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#[unstable(feature = "trusted_len", issue = "37572")]
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unsafe impl<'a, I, T: 'a> TrustedLen for Cloned<I>
where I: TrustedLen<Item=&'a T>,
T: Clone
{}
/// An iterator that repeats endlessly.
///
/// This `struct` is created by the [`cycle`] method on [`Iterator`]. See its
/// documentation for more.
///
/// [`cycle`]: trait.Iterator.html#method.cycle
/// [`Iterator`]: trait.Iterator.html
#[derive(Clone, Debug)]
#[must_use = "iterator adaptors are lazy and do nothing unless consumed"]
#[stable(feature = "rust1", since = "1.0.0")]
pub struct Cycle<I> {
orig: I,
iter: I,
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I> Iterator for Cycle<I> where I: Clone + Iterator {
type Item = <I as Iterator>::Item;
#[inline]
fn next(&mut self) -> Option<<I as Iterator>::Item> {
match self.iter.next() {
None => { self.iter = self.orig.clone(); self.iter.next() }
y => y
}
}
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
// the cycle iterator is either empty or infinite
match self.orig.size_hint() {
sz @ (0, Some(0)) => sz,
(0, _) => (0, None),
_ => (usize::MAX, None)
}
}
}
#[unstable(feature = "fused", issue = "35602")]
impl<I> FusedIterator for Cycle<I> where I: Clone + Iterator {}
/// An iterator for stepping iterators by a custom amount.
///
/// This `struct` is created by the [`step_by`] method on [`Iterator`]. See
/// its documentation for more.
///
/// [`step_by`]: trait.Iterator.html#method.step_by
/// [`Iterator`]: trait.Iterator.html
#[must_use = "iterator adaptors are lazy and do nothing unless consumed"]
#[unstable(feature = "iterator_step_by",
reason = "unstable replacement of Range::step_by",
issue = "27741")]
#[derive(Clone, Debug)]
pub struct StepBy<I> {
iter: I,
step: usize,
first_take: bool,
}
#[unstable(feature = "iterator_step_by",
reason = "unstable replacement of Range::step_by",
issue = "27741")]
impl<I> Iterator for StepBy<I> where I: Iterator {
type Item = I::Item;
#[inline]
fn next(&mut self) -> Option<Self::Item> {
if self.first_take {
self.first_take = false;
self.iter.next()
} else {
self.iter.nth(self.step)
}
}
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
let inner_hint = self.iter.size_hint();
if self.first_take {
let f = |n| if n == 0 { 0 } else { 1 + (n-1)/(self.step+1) };
(f(inner_hint.0), inner_hint.1.map(f))
} else {
let f = |n| n / (self.step+1);
(f(inner_hint.0), inner_hint.1.map(f))
}
}
}
// StepBy can only make the iterator shorter, so the len will still fit.
#[unstable(feature = "iterator_step_by",
reason = "unstable replacement of Range::step_by",
issue = "27741")]
impl<I> ExactSizeIterator for StepBy<I> where I: ExactSizeIterator {}
/// An iterator that strings two iterators together.
///
/// This `struct` is created by the [`chain`] method on [`Iterator`]. See its
/// documentation for more.
///
/// [`chain`]: trait.Iterator.html#method.chain
/// [`Iterator`]: trait.Iterator.html
#[derive(Clone, Debug)]
#[must_use = "iterator adaptors are lazy and do nothing unless consumed"]
#[stable(feature = "rust1", since = "1.0.0")]
pub struct Chain<A, B> {
a: A,
b: B,
state: ChainState,
}
// The iterator protocol specifies that iteration ends with the return value
// `None` from `.next()` (or `.next_back()`) and it is unspecified what
// further calls return. The chain adaptor must account for this since it uses
// two subiterators.
//
// It uses three states:
//
// - Both: `a` and `b` are remaining
// - Front: `a` remaining
// - Back: `b` remaining
//
// The fourth state (neither iterator is remaining) only occurs after Chain has
// returned None once, so we don't need to store this state.
#[derive(Clone, Debug)]
enum ChainState {
// both front and back iterator are remaining
Both,
// only front is remaining
Front,
// only back is remaining
Back,
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<A, B> Iterator for Chain<A, B> where
A: Iterator,
B: Iterator<Item = A::Item>
{
type Item = A::Item;
#[inline]
fn next(&mut self) -> Option<A::Item> {
match self.state {
ChainState::Both => match self.a.next() {
elt @ Some(..) => elt,
None => {
self.state = ChainState::Back;
self.b.next()
}
},
ChainState::Front => self.a.next(),
ChainState::Back => self.b.next(),
}
}
#[inline]
#[rustc_inherit_overflow_checks]
fn count(self) -> usize {
match self.state {
ChainState::Both => self.a.count() + self.b.count(),
ChainState::Front => self.a.count(),
ChainState::Back => self.b.count(),
}
}
fn try_fold<Acc, F, R>(&mut self, init: Acc, mut f: F) -> R where
Self: Sized, F: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
let mut accum = init;
match self.state {
ChainState::Both | ChainState::Front => {
accum = self.a.try_fold(accum, &mut f)?;
if let ChainState::Both = self.state {
self.state = ChainState::Back;
}
}
_ => { }
}
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if let ChainState::Back = self.state {
accum = self.b.try_fold(accum, &mut f)?;
}
Try::from_ok(accum)
}
fn fold<Acc, F>(self, init: Acc, mut f: F) -> Acc
where F: FnMut(Acc, Self::Item) -> Acc,
{
let mut accum = init;
match self.state {
ChainState::Both | ChainState::Front => {
accum = self.a.fold(accum, &mut f);
}
_ => { }
}
match self.state {
ChainState::Both | ChainState::Back => {
accum = self.b.fold(accum, &mut f);
}
_ => { }
}
accum
}
#[inline]
fn nth(&mut self, mut n: usize) -> Option<A::Item> {
match self.state {
ChainState::Both | ChainState::Front => {
for x in self.a.by_ref() {
if n == 0 {
return Some(x)
}
n -= 1;
}
if let ChainState::Both = self.state {
self.state = ChainState::Back;
}
}
ChainState::Back => {}
}
if let ChainState::Back = self.state {
self.b.nth(n)
} else {
None
}
}
#[inline]
fn find<P>(&mut self, mut predicate: P) -> Option<Self::Item> where
P: FnMut(&Self::Item) -> bool,
{
match self.state {
ChainState::Both => match self.a.find(&mut predicate) {
None => {
self.state = ChainState::Back;
self.b.find(predicate)
}
v => v
},
ChainState::Front => self.a.find(predicate),
ChainState::Back => self.b.find(predicate),
}
}
#[inline]
fn last(self) -> Option<A::Item> {
match self.state {
ChainState::Both => {
// Must exhaust a before b.
let a_last = self.a.last();
let b_last = self.b.last();
b_last.or(a_last)
},
ChainState::Front => self.a.last(),
ChainState::Back => self.b.last()
}
}
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
let (a_lower, a_upper) = self.a.size_hint();
let (b_lower, b_upper) = self.b.size_hint();
let lower = a_lower.saturating_add(b_lower);
let upper = match (a_upper, b_upper) {
(Some(x), Some(y)) => x.checked_add(y),
_ => None
};
(lower, upper)
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<A, B> DoubleEndedIterator for Chain<A, B> where
A: DoubleEndedIterator,
B: DoubleEndedIterator<Item=A::Item>,
{
#[inline]
fn next_back(&mut self) -> Option<A::Item> {
match self.state {
ChainState::Both => match self.b.next_back() {
elt @ Some(..) => elt,
None => {
self.state = ChainState::Front;
self.a.next_back()
}
},
ChainState::Front => self.a.next_back(),
ChainState::Back => self.b.next_back(),
}
}
fn try_rfold<Acc, F, R>(&mut self, init: Acc, mut f: F) -> R where
Self: Sized, F: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
let mut accum = init;
match self.state {
ChainState::Both | ChainState::Back => {
accum = self.b.try_rfold(accum, &mut f)?;
if let ChainState::Both = self.state {
self.state = ChainState::Front;
}
}
_ => { }
}
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if let ChainState::Front = self.state {
accum = self.a.try_rfold(accum, &mut f)?;
}
Try::from_ok(accum)
}
fn rfold<Acc, F>(self, init: Acc, mut f: F) -> Acc
where F: FnMut(Acc, Self::Item) -> Acc,
{
let mut accum = init;
match self.state {
ChainState::Both | ChainState::Back => {
accum = self.b.rfold(accum, &mut f);
}
_ => { }
}
match self.state {
ChainState::Both | ChainState::Front => {
accum = self.a.rfold(accum, &mut f);
}
_ => { }
}
accum
}
}
// Note: *both* must be fused to handle double-ended iterators.
#[unstable(feature = "fused", issue = "35602")]
impl<A, B> FusedIterator for Chain<A, B>
where A: FusedIterator,
B: FusedIterator<Item=A::Item>,
{}
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#[unstable(feature = "trusted_len", issue = "37572")]
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unsafe impl<A, B> TrustedLen for Chain<A, B>
where A: TrustedLen, B: TrustedLen<Item=A::Item>,
{}
/// An iterator that iterates two other iterators simultaneously.
///
/// This `struct` is created by the [`zip`] method on [`Iterator`]. See its
/// documentation for more.
///
/// [`zip`]: trait.Iterator.html#method.zip
/// [`Iterator`]: trait.Iterator.html
#[derive(Clone, Debug)]
#[must_use = "iterator adaptors are lazy and do nothing unless consumed"]
#[stable(feature = "rust1", since = "1.0.0")]
pub struct Zip<A, B> {
a: A,
b: B,
// index and len are only used by the specialized version of zip
index: usize,
len: usize,
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<A, B> Iterator for Zip<A, B> where A: Iterator, B: Iterator
{
type Item = (A::Item, B::Item);
#[inline]
fn next(&mut self) -> Option<Self::Item> {
ZipImpl::next(self)
}
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
ZipImpl::size_hint(self)
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<A, B> DoubleEndedIterator for Zip<A, B> where
A: DoubleEndedIterator + ExactSizeIterator,
B: DoubleEndedIterator + ExactSizeIterator,
{
#[inline]
fn next_back(&mut self) -> Option<(A::Item, B::Item)> {
ZipImpl::next_back(self)
}
}
// Zip specialization trait
#[doc(hidden)]
trait ZipImpl<A, B> {
type Item;
fn new(a: A, b: B) -> Self;
fn next(&mut self) -> Option<Self::Item>;
fn size_hint(&self) -> (usize, Option<usize>);
fn next_back(&mut self) -> Option<Self::Item>
where A: DoubleEndedIterator + ExactSizeIterator,
B: DoubleEndedIterator + ExactSizeIterator;
}
// General Zip impl
#[doc(hidden)]
impl<A, B> ZipImpl<A, B> for Zip<A, B>
where A: Iterator, B: Iterator
{
type Item = (A::Item, B::Item);
default fn new(a: A, b: B) -> Self {
Zip {
a,
b,
index: 0, // unused
len: 0, // unused
}
}
#[inline]
default fn next(&mut self) -> Option<(A::Item, B::Item)> {
self.a.next().and_then(|x| {
self.b.next().and_then(|y| {
Some((x, y))
})
})
}
#[inline]
default fn next_back(&mut self) -> Option<(A::Item, B::Item)>
where A: DoubleEndedIterator + ExactSizeIterator,
B: DoubleEndedIterator + ExactSizeIterator
{
let a_sz = self.a.len();
let b_sz = self.b.len();
if a_sz != b_sz {
// Adjust a, b to equal length
if a_sz > b_sz {
for _ in 0..a_sz - b_sz { self.a.next_back(); }
} else {
for _ in 0..b_sz - a_sz { self.b.next_back(); }
}
}
match (self.a.next_back(), self.b.next_back()) {
(Some(x), Some(y)) => Some((x, y)),
(None, None) => None,
_ => unreachable!(),
}
}
#[inline]
default fn size_hint(&self) -> (usize, Option<usize>) {
let (a_lower, a_upper) = self.a.size_hint();
let (b_lower, b_upper) = self.b.size_hint();
let lower = cmp::min(a_lower, b_lower);
let upper = match (a_upper, b_upper) {
(Some(x), Some(y)) => Some(cmp::min(x,y)),
(Some(x), None) => Some(x),
(None, Some(y)) => Some(y),
(None, None) => None
};
(lower, upper)
}
}
#[doc(hidden)]
impl<A, B> ZipImpl<A, B> for Zip<A, B>
where A: TrustedRandomAccess, B: TrustedRandomAccess
{
fn new(a: A, b: B) -> Self {
let len = cmp::min(a.len(), b.len());
Zip {
a,
b,
index: 0,
len,
}
}
#[inline]
fn next(&mut self) -> Option<(A::Item, B::Item)> {
if self.index < self.len {
let i = self.index;
self.index += 1;
unsafe {
Some((self.a.get_unchecked(i), self.b.get_unchecked(i)))
}
} else if A::may_have_side_effect() && self.index < self.a.len() {
// match the base implementation's potential side effects
unsafe {
self.a.get_unchecked(self.index);
}
self.index += 1;
None
} else {
None
}
}
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
let len = self.len - self.index;
(len, Some(len))
}
#[inline]
fn next_back(&mut self) -> Option<(A::Item, B::Item)>
where A: DoubleEndedIterator + ExactSizeIterator,
B: DoubleEndedIterator + ExactSizeIterator
{
// Adjust a, b to equal length
if A::may_have_side_effect() {
let sz = self.a.len();
if sz > self.len {
for _ in 0..sz - cmp::max(self.len, self.index) {
self.a.next_back();
}
}
}
if B::may_have_side_effect() {
let sz = self.b.len();
if sz > self.len {
for _ in 0..sz - self.len {
self.b.next_back();
}
}
}
if self.index < self.len {
self.len -= 1;
let i = self.len;
unsafe {
Some((self.a.get_unchecked(i), self.b.get_unchecked(i)))
}
} else {
None
}
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<A, B> ExactSizeIterator for Zip<A, B>
where A: ExactSizeIterator, B: ExactSizeIterator {}
#[doc(hidden)]
unsafe impl<A, B> TrustedRandomAccess for Zip<A, B>
where A: TrustedRandomAccess,
B: TrustedRandomAccess,
{
unsafe fn get_unchecked(&mut self, i: usize) -> (A::Item, B::Item) {
(self.a.get_unchecked(i), self.b.get_unchecked(i))
}
fn may_have_side_effect() -> bool {
A::may_have_side_effect() || B::may_have_side_effect()
}
}
#[unstable(feature = "fused", issue = "35602")]
impl<A, B> FusedIterator for Zip<A, B>
where A: FusedIterator, B: FusedIterator, {}
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#[unstable(feature = "trusted_len", issue = "37572")]
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unsafe impl<A, B> TrustedLen for Zip<A, B>
where A: TrustedLen, B: TrustedLen,
{}
/// An iterator that maps the values of `iter` with `f`.
///
/// This `struct` is created by the [`map`] method on [`Iterator`]. See its
/// documentation for more.
///
/// [`map`]: trait.Iterator.html#method.map
/// [`Iterator`]: trait.Iterator.html
///
/// # Notes about side effects
///
/// The [`map`] iterator implements [`DoubleEndedIterator`], meaning that
/// you can also [`map`] backwards:
///
/// ```rust
/// let v: Vec<i32> = vec![1, 2, 3].into_iter().map(|x| x + 1).rev().collect();
///
/// assert_eq!(v, [4, 3, 2]);
/// ```
///
/// [`DoubleEndedIterator`]: trait.DoubleEndedIterator.html
///
/// But if your closure has state, iterating backwards may act in a way you do
/// not expect. Let's go through an example. First, in the forward direction:
///
/// ```rust
/// let mut c = 0;
///
/// for pair in vec!['a', 'b', 'c'].into_iter()
/// .map(|letter| { c += 1; (letter, c) }) {
/// println!("{:?}", pair);
/// }
/// ```
///
/// This will print "('a', 1), ('b', 2), ('c', 3)".
///
/// Now consider this twist where we add a call to `rev`. This version will
/// print `('c', 1), ('b', 2), ('a', 3)`. Note that the letters are reversed,
/// but the values of the counter still go in order. This is because `map()` is
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/// still being called lazily on each item, but we are popping items off the
/// back of the vector now, instead of shifting them from the front.
///
/// ```rust
/// let mut c = 0;
///
/// for pair in vec!['a', 'b', 'c'].into_iter()
/// .map(|letter| { c += 1; (letter, c) })
/// .rev() {
/// println!("{:?}", pair);
/// }
/// ```
#[must_use = "iterator adaptors are lazy and do nothing unless consumed"]
#[stable(feature = "rust1", since = "1.0.0")]
#[derive(Clone)]
pub struct Map<I, F> {
iter: I,
f: F,
}
#[stable(feature = "core_impl_debug", since = "1.9.0")]
impl<I: fmt::Debug, F> fmt::Debug for Map<I, F> {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
f.debug_struct("Map")
.field("iter", &self.iter)
.finish()
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<B, I: Iterator, F> Iterator for Map<I, F> where F: FnMut(I::Item) -> B {
type Item = B;
#[inline]
fn next(&mut self) -> Option<B> {
self.iter.next().map(&mut self.f)
}
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
self.iter.size_hint()
}
fn try_fold<Acc, G, R>(&mut self, init: Acc, mut g: G) -> R where
Self: Sized, G: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
let f = &mut self.f;
self.iter.try_fold(init, move |acc, elt| g(acc, f(elt)))
}
fn fold<Acc, G>(self, init: Acc, mut g: G) -> Acc
where G: FnMut(Acc, Self::Item) -> Acc,
{
let mut f = self.f;
self.iter.fold(init, move |acc, elt| g(acc, f(elt)))
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<B, I: DoubleEndedIterator, F> DoubleEndedIterator for Map<I, F> where
F: FnMut(I::Item) -> B,
{
#[inline]
fn next_back(&mut self) -> Option<B> {
self.iter.next_back().map(&mut self.f)
}
fn try_rfold<Acc, G, R>(&mut self, init: Acc, mut g: G) -> R where
Self: Sized, G: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
let f = &mut self.f;
self.iter.try_rfold(init, move |acc, elt| g(acc, f(elt)))
}
fn rfold<Acc, G>(self, init: Acc, mut g: G) -> Acc
where G: FnMut(Acc, Self::Item) -> Acc,
{
let mut f = self.f;
self.iter.rfold(init, move |acc, elt| g(acc, f(elt)))
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<B, I: ExactSizeIterator, F> ExactSizeIterator for Map<I, F>
where F: FnMut(I::Item) -> B
{
fn len(&self) -> usize {
self.iter.len()
}
fn is_empty(&self) -> bool {
self.iter.is_empty()
}
}
#[unstable(feature = "fused", issue = "35602")]
impl<B, I: FusedIterator, F> FusedIterator for Map<I, F>
where F: FnMut(I::Item) -> B {}
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#[unstable(feature = "trusted_len", issue = "37572")]
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unsafe impl<B, I, F> TrustedLen for Map<I, F>
where I: TrustedLen,
F: FnMut(I::Item) -> B {}
#[doc(hidden)]
unsafe impl<B, I, F> TrustedRandomAccess for Map<I, F>
where I: TrustedRandomAccess,
F: FnMut(I::Item) -> B,
{
unsafe fn get_unchecked(&mut self, i: usize) -> Self::Item {
(self.f)(self.iter.get_unchecked(i))
}
#[inline]
fn may_have_side_effect() -> bool { true }
}
/// An iterator that filters the elements of `iter` with `predicate`.
///
/// This `struct` is created by the [`filter`] method on [`Iterator`]. See its
/// documentation for more.
///
/// [`filter`]: trait.Iterator.html#method.filter
/// [`Iterator`]: trait.Iterator.html
#[must_use = "iterator adaptors are lazy and do nothing unless consumed"]
#[stable(feature = "rust1", since = "1.0.0")]
#[derive(Clone)]
pub struct Filter<I, P> {
iter: I,
predicate: P,
}
#[stable(feature = "core_impl_debug", since = "1.9.0")]
impl<I: fmt::Debug, P> fmt::Debug for Filter<I, P> {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
f.debug_struct("Filter")
.field("iter", &self.iter)
.finish()
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I: Iterator, P> Iterator for Filter<I, P> where P: FnMut(&I::Item) -> bool {
type Item = I::Item;
#[inline]
fn next(&mut self) -> Option<I::Item> {
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for x in &mut self.iter {
if (self.predicate)(&x) {
return Some(x);
}
}
None
}
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
let (_, upper) = self.iter.size_hint();
(0, upper) // can't know a lower bound, due to the predicate
}
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// this special case allows the compiler to make `.filter(_).count()`
// branchless. Barring perfect branch prediction (which is unattainable in
// the general case), this will be much faster in >90% of cases (containing
// virtually all real workloads) and only a tiny bit slower in the rest.
//
// Having this specialization thus allows us to write `.filter(p).count()`
// where we would otherwise write `.map(|x| p(x) as usize).sum()`, which is
// less readable and also less backwards-compatible to Rust before 1.10.
//
// Using the branchless version will also simplify the LLVM byte code, thus
// leaving more budget for LLVM optimizations.
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#[inline]
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fn count(mut self) -> usize {
let mut count = 0;
for x in &mut self.iter {
count += (self.predicate)(&x) as usize;
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}
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count
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}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
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#[inline]
fn try_fold<Acc, Fold, R>(&mut self, init: Acc, mut fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
let predicate = &mut self.predicate;
self.iter.try_fold(init, move |acc, item| if predicate(&item) {
fold(acc, item)
} else {
Try::from_ok(acc)
})
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn fold<Acc, Fold>(self, init: Acc, mut fold: Fold) -> Acc
where Fold: FnMut(Acc, Self::Item) -> Acc,
{
let mut predicate = self.predicate;
self.iter.fold(init, move |acc, item| if predicate(&item) {
fold(acc, item)
} else {
acc
})
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I: DoubleEndedIterator, P> DoubleEndedIterator for Filter<I, P>
where P: FnMut(&I::Item) -> bool,
{
#[inline]
fn next_back(&mut self) -> Option<I::Item> {
for x in self.iter.by_ref().rev() {
if (self.predicate)(&x) {
return Some(x);
}
}
None
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn try_rfold<Acc, Fold, R>(&mut self, init: Acc, mut fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
let predicate = &mut self.predicate;
self.iter.try_rfold(init, move |acc, item| if predicate(&item) {
fold(acc, item)
} else {
Try::from_ok(acc)
})
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn rfold<Acc, Fold>(self, init: Acc, mut fold: Fold) -> Acc
where Fold: FnMut(Acc, Self::Item) -> Acc,
{
let mut predicate = self.predicate;
self.iter.rfold(init, move |acc, item| if predicate(&item) {
fold(acc, item)
} else {
acc
})
}
}
#[unstable(feature = "fused", issue = "35602")]
impl<I: FusedIterator, P> FusedIterator for Filter<I, P>
where P: FnMut(&I::Item) -> bool {}
/// An iterator that uses `f` to both filter and map elements from `iter`.
///
/// This `struct` is created by the [`filter_map`] method on [`Iterator`]. See its
/// documentation for more.
///
/// [`filter_map`]: trait.Iterator.html#method.filter_map
/// [`Iterator`]: trait.Iterator.html
#[must_use = "iterator adaptors are lazy and do nothing unless consumed"]
#[stable(feature = "rust1", since = "1.0.0")]
#[derive(Clone)]
pub struct FilterMap<I, F> {
iter: I,
f: F,
}
#[stable(feature = "core_impl_debug", since = "1.9.0")]
impl<I: fmt::Debug, F> fmt::Debug for FilterMap<I, F> {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
f.debug_struct("FilterMap")
.field("iter", &self.iter)
.finish()
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<B, I: Iterator, F> Iterator for FilterMap<I, F>
where F: FnMut(I::Item) -> Option<B>,
{
type Item = B;
#[inline]
fn next(&mut self) -> Option<B> {
for x in self.iter.by_ref() {
if let Some(y) = (self.f)(x) {
return Some(y);
}
}
None
}
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
let (_, upper) = self.iter.size_hint();
(0, upper) // can't know a lower bound, due to the predicate
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn try_fold<Acc, Fold, R>(&mut self, init: Acc, mut fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
let f = &mut self.f;
self.iter.try_fold(init, move |acc, item| match f(item) {
Some(x) => fold(acc, x),
None => Try::from_ok(acc),
})
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn fold<Acc, Fold>(self, init: Acc, mut fold: Fold) -> Acc
where Fold: FnMut(Acc, Self::Item) -> Acc,
{
let mut f = self.f;
self.iter.fold(init, move |acc, item| match f(item) {
Some(x) => fold(acc, x),
None => acc,
})
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<B, I: DoubleEndedIterator, F> DoubleEndedIterator for FilterMap<I, F>
where F: FnMut(I::Item) -> Option<B>,
{
#[inline]
fn next_back(&mut self) -> Option<B> {
for x in self.iter.by_ref().rev() {
if let Some(y) = (self.f)(x) {
return Some(y);
}
}
None
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn try_rfold<Acc, Fold, R>(&mut self, init: Acc, mut fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
let f = &mut self.f;
self.iter.try_rfold(init, move |acc, item| match f(item) {
Some(x) => fold(acc, x),
None => Try::from_ok(acc),
})
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn rfold<Acc, Fold>(self, init: Acc, mut fold: Fold) -> Acc
where Fold: FnMut(Acc, Self::Item) -> Acc,
{
let mut f = self.f;
self.iter.rfold(init, move |acc, item| match f(item) {
Some(x) => fold(acc, x),
None => acc,
})
}
}
#[unstable(feature = "fused", issue = "35602")]
impl<B, I: FusedIterator, F> FusedIterator for FilterMap<I, F>
where F: FnMut(I::Item) -> Option<B> {}
/// An iterator that yields the current count and the element during iteration.
///
/// This `struct` is created by the [`enumerate`] method on [`Iterator`]. See its
/// documentation for more.
///
/// [`enumerate`]: trait.Iterator.html#method.enumerate
/// [`Iterator`]: trait.Iterator.html
#[derive(Clone, Debug)]
#[must_use = "iterator adaptors are lazy and do nothing unless consumed"]
#[stable(feature = "rust1", since = "1.0.0")]
pub struct Enumerate<I> {
iter: I,
count: usize,
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I> Iterator for Enumerate<I> where I: Iterator {
type Item = (usize, <I as Iterator>::Item);
/// # Overflow Behavior
///
/// The method does no guarding against overflows, so enumerating more than
/// `usize::MAX` elements either produces the wrong result or panics. If
/// debug assertions are enabled, a panic is guaranteed.
///
/// # Panics
///
/// Might panic if the index of the element overflows a `usize`.
#[inline]
#[rustc_inherit_overflow_checks]
fn next(&mut self) -> Option<(usize, <I as Iterator>::Item)> {
self.iter.next().map(|a| {
let ret = (self.count, a);
// Possible undefined overflow.
self.count += 1;
ret
})
}
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
self.iter.size_hint()
}
#[inline]
#[rustc_inherit_overflow_checks]
fn nth(&mut self, n: usize) -> Option<(usize, I::Item)> {
self.iter.nth(n).map(|a| {
let i = self.count + n;
self.count = i + 1;
(i, a)
})
}
#[inline]
fn count(self) -> usize {
self.iter.count()
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
#[rustc_inherit_overflow_checks]
fn try_fold<Acc, Fold, R>(&mut self, init: Acc, mut fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
let count = &mut self.count;
self.iter.try_fold(init, move |acc, item| {
let acc = fold(acc, (*count, item));
*count += 1;
acc
})
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
#[rustc_inherit_overflow_checks]
fn fold<Acc, Fold>(self, init: Acc, mut fold: Fold) -> Acc
where Fold: FnMut(Acc, Self::Item) -> Acc,
{
let mut count = self.count;
self.iter.fold(init, move |acc, item| {
let acc = fold(acc, (count, item));
count += 1;
acc
})
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I> DoubleEndedIterator for Enumerate<I> where
I: ExactSizeIterator + DoubleEndedIterator
{
#[inline]
fn next_back(&mut self) -> Option<(usize, <I as Iterator>::Item)> {
self.iter.next_back().map(|a| {
let len = self.iter.len();
// Can safely add, `ExactSizeIterator` promises that the number of
// elements fits into a `usize`.
(self.count + len, a)
})
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn try_rfold<Acc, Fold, R>(&mut self, init: Acc, mut fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
// Can safely add and subtract the count, as `ExactSizeIterator` promises
// that the number of elements fits into a `usize`.
let mut count = self.count + self.iter.len();
self.iter.try_rfold(init, move |acc, item| {
count -= 1;
fold(acc, (count, item))
})
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
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#[inline]
fn rfold<Acc, Fold>(self, init: Acc, mut fold: Fold) -> Acc
where Fold: FnMut(Acc, Self::Item) -> Acc,
{
// Can safely add and subtract the count, as `ExactSizeIterator` promises
// that the number of elements fits into a `usize`.
let mut count = self.count + self.iter.len();
self.iter.rfold(init, move |acc, item| {
count -= 1;
fold(acc, (count, item))
})
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I> ExactSizeIterator for Enumerate<I> where I: ExactSizeIterator {
fn len(&self) -> usize {
self.iter.len()
}
fn is_empty(&self) -> bool {
self.iter.is_empty()
}
}
#[doc(hidden)]
unsafe impl<I> TrustedRandomAccess for Enumerate<I>
where I: TrustedRandomAccess
{
unsafe fn get_unchecked(&mut self, i: usize) -> (usize, I::Item) {
(self.count + i, self.iter.get_unchecked(i))
}
fn may_have_side_effect() -> bool {
I::may_have_side_effect()
}
}
#[unstable(feature = "fused", issue = "35602")]
impl<I> FusedIterator for Enumerate<I> where I: FusedIterator {}
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#[unstable(feature = "trusted_len", issue = "37572")]
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unsafe impl<I> TrustedLen for Enumerate<I>
where I: TrustedLen,
{}
/// An iterator with a `peek()` that returns an optional reference to the next
/// element.
///
/// This `struct` is created by the [`peekable`] method on [`Iterator`]. See its
/// documentation for more.
///
/// [`peekable`]: trait.Iterator.html#method.peekable
/// [`Iterator`]: trait.Iterator.html
#[derive(Clone, Debug)]
#[must_use = "iterator adaptors are lazy and do nothing unless consumed"]
#[stable(feature = "rust1", since = "1.0.0")]
pub struct Peekable<I: Iterator> {
iter: I,
/// Remember a peeked value, even if it was None.
peeked: Option<Option<I::Item>>,
}
// Peekable must remember if a None has been seen in the `.peek()` method.
// It ensures that `.peek(); .peek();` or `.peek(); .next();` only advances the
// underlying iterator at most once. This does not by itself make the iterator
// fused.
#[stable(feature = "rust1", since = "1.0.0")]
impl<I: Iterator> Iterator for Peekable<I> {
type Item = I::Item;
#[inline]
fn next(&mut self) -> Option<I::Item> {
match self.peeked.take() {
Some(v) => v,
None => self.iter.next(),
}
}
#[inline]
#[rustc_inherit_overflow_checks]
fn count(mut self) -> usize {
match self.peeked.take() {
Some(None) => 0,
Some(Some(_)) => 1 + self.iter.count(),
None => self.iter.count(),
}
}
#[inline]
fn nth(&mut self, n: usize) -> Option<I::Item> {
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// FIXME(#6393): merge these when borrow-checking gets better.
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if n == 0 {
match self.peeked.take() {
Some(v) => v,
None => self.iter.nth(n),
}
} else {
match self.peeked.take() {
Some(None) => None,
Some(Some(_)) => self.iter.nth(n - 1),
None => self.iter.nth(n),
}
}
}
#[inline]
fn last(mut self) -> Option<I::Item> {
let peek_opt = match self.peeked.take() {
Some(None) => return None,
Some(v) => v,
None => None,
};
self.iter.last().or(peek_opt)
}
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
let peek_len = match self.peeked {
Some(None) => return (0, Some(0)),
Some(Some(_)) => 1,
None => 0,
};
let (lo, hi) = self.iter.size_hint();
let lo = lo.saturating_add(peek_len);
let hi = hi.and_then(|x| x.checked_add(peek_len));
(lo, hi)
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
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#[inline]
fn try_fold<B, F, R>(&mut self, init: B, mut f: F) -> R where
Self: Sized, F: FnMut(B, Self::Item) -> R, R: Try<Ok=B>
{
let acc = match self.peeked.take() {
Some(None) => return Try::from_ok(init),
Some(Some(v)) => f(init, v)?,
None => init,
};
self.iter.try_fold(acc, f)
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn fold<Acc, Fold>(self, init: Acc, mut fold: Fold) -> Acc
where Fold: FnMut(Acc, Self::Item) -> Acc,
{
let acc = match self.peeked {
Some(None) => return init,
Some(Some(v)) => fold(init, v),
None => init,
};
self.iter.fold(acc, fold)
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I: ExactSizeIterator> ExactSizeIterator for Peekable<I> {}
#[unstable(feature = "fused", issue = "35602")]
impl<I: FusedIterator> FusedIterator for Peekable<I> {}
impl<I: Iterator> Peekable<I> {
/// Returns a reference to the next() value without advancing the iterator.
///
/// Like [`next`], if there is a value, it is wrapped in a `Some(T)`.
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/// But if the iteration is over, `None` is returned.
///
/// [`next`]: trait.Iterator.html#tymethod.next
///
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/// Because `peek()` returns a reference, and many iterators iterate over
/// references, there can be a possibly confusing situation where the
/// return value is a double reference. You can see this effect in the
2016-04-28 16:51:42 -05:00
/// examples below.
///
/// # Examples
///
/// Basic usage:
///
/// ```
/// let xs = [1, 2, 3];
///
/// let mut iter = xs.iter().peekable();
///
/// // peek() lets us see into the future
/// assert_eq!(iter.peek(), Some(&&1));
/// assert_eq!(iter.next(), Some(&1));
///
/// assert_eq!(iter.next(), Some(&2));
///
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/// // The iterator does not advance even if we `peek` multiple times
/// assert_eq!(iter.peek(), Some(&&3));
/// assert_eq!(iter.peek(), Some(&&3));
///
/// assert_eq!(iter.next(), Some(&3));
///
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/// // After the iterator is finished, so is `peek()`
/// assert_eq!(iter.peek(), None);
/// assert_eq!(iter.next(), None);
/// ```
#[inline]
#[stable(feature = "rust1", since = "1.0.0")]
pub fn peek(&mut self) -> Option<&I::Item> {
if self.peeked.is_none() {
self.peeked = Some(self.iter.next());
}
match self.peeked {
Some(Some(ref value)) => Some(value),
Some(None) => None,
_ => unreachable!(),
}
}
}
/// An iterator that rejects elements while `predicate` is true.
///
/// This `struct` is created by the [`skip_while`] method on [`Iterator`]. See its
/// documentation for more.
///
/// [`skip_while`]: trait.Iterator.html#method.skip_while
/// [`Iterator`]: trait.Iterator.html
#[must_use = "iterator adaptors are lazy and do nothing unless consumed"]
#[stable(feature = "rust1", since = "1.0.0")]
#[derive(Clone)]
pub struct SkipWhile<I, P> {
iter: I,
flag: bool,
predicate: P,
}
#[stable(feature = "core_impl_debug", since = "1.9.0")]
impl<I: fmt::Debug, P> fmt::Debug for SkipWhile<I, P> {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
f.debug_struct("SkipWhile")
.field("iter", &self.iter)
.field("flag", &self.flag)
.finish()
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I: Iterator, P> Iterator for SkipWhile<I, P>
where P: FnMut(&I::Item) -> bool
{
type Item = I::Item;
#[inline]
fn next(&mut self) -> Option<I::Item> {
let flag = &mut self.flag;
let pred = &mut self.predicate;
self.iter.find(move |x| {
if *flag || !pred(x) {
*flag = true;
true
} else {
false
}
})
}
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
let (_, upper) = self.iter.size_hint();
(0, upper) // can't know a lower bound, due to the predicate
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn try_fold<Acc, Fold, R>(&mut self, mut init: Acc, mut fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
if !self.flag {
match self.next() {
Some(v) => init = fold(init, v)?,
None => return Try::from_ok(init),
}
}
self.iter.try_fold(init, fold)
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn fold<Acc, Fold>(mut self, mut init: Acc, mut fold: Fold) -> Acc
where Fold: FnMut(Acc, Self::Item) -> Acc,
{
if !self.flag {
match self.next() {
Some(v) => init = fold(init, v),
None => return init,
}
}
self.iter.fold(init, fold)
}
}
#[unstable(feature = "fused", issue = "35602")]
impl<I, P> FusedIterator for SkipWhile<I, P>
where I: FusedIterator, P: FnMut(&I::Item) -> bool {}
/// An iterator that only accepts elements while `predicate` is true.
///
/// This `struct` is created by the [`take_while`] method on [`Iterator`]. See its
/// documentation for more.
///
/// [`take_while`]: trait.Iterator.html#method.take_while
/// [`Iterator`]: trait.Iterator.html
#[must_use = "iterator adaptors are lazy and do nothing unless consumed"]
#[stable(feature = "rust1", since = "1.0.0")]
#[derive(Clone)]
pub struct TakeWhile<I, P> {
iter: I,
flag: bool,
predicate: P,
}
#[stable(feature = "core_impl_debug", since = "1.9.0")]
impl<I: fmt::Debug, P> fmt::Debug for TakeWhile<I, P> {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
f.debug_struct("TakeWhile")
.field("iter", &self.iter)
.field("flag", &self.flag)
.finish()
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I: Iterator, P> Iterator for TakeWhile<I, P>
where P: FnMut(&I::Item) -> bool
{
type Item = I::Item;
#[inline]
fn next(&mut self) -> Option<I::Item> {
if self.flag {
None
} else {
self.iter.next().and_then(|x| {
if (self.predicate)(&x) {
Some(x)
} else {
self.flag = true;
None
}
})
}
}
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
let (_, upper) = self.iter.size_hint();
(0, upper) // can't know a lower bound, due to the predicate
}
#[inline]
fn try_fold<Acc, Fold, R>(&mut self, init: Acc, mut fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
if self.flag {
Try::from_ok(init)
} else {
let flag = &mut self.flag;
let p = &mut self.predicate;
self.iter.try_fold(init, move |acc, x|{
if p(&x) {
LoopState::from_try(fold(acc, x))
} else {
*flag = true;
LoopState::Break(Try::from_ok(acc))
}
}).into_try()
}
}
}
#[unstable(feature = "fused", issue = "35602")]
impl<I, P> FusedIterator for TakeWhile<I, P>
where I: FusedIterator, P: FnMut(&I::Item) -> bool {}
/// An iterator that skips over `n` elements of `iter`.
///
/// This `struct` is created by the [`skip`] method on [`Iterator`]. See its
/// documentation for more.
///
/// [`skip`]: trait.Iterator.html#method.skip
/// [`Iterator`]: trait.Iterator.html
#[derive(Clone, Debug)]
#[must_use = "iterator adaptors are lazy and do nothing unless consumed"]
#[stable(feature = "rust1", since = "1.0.0")]
pub struct Skip<I> {
iter: I,
n: usize
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I> Iterator for Skip<I> where I: Iterator {
type Item = <I as Iterator>::Item;
#[inline]
fn next(&mut self) -> Option<I::Item> {
if self.n == 0 {
self.iter.next()
} else {
let old_n = self.n;
self.n = 0;
self.iter.nth(old_n)
}
}
#[inline]
fn nth(&mut self, n: usize) -> Option<I::Item> {
// Can't just add n + self.n due to overflow.
if self.n == 0 {
self.iter.nth(n)
} else {
let to_skip = self.n;
self.n = 0;
// nth(n) skips n+1
if self.iter.nth(to_skip-1).is_none() {
return None;
}
self.iter.nth(n)
}
}
#[inline]
fn count(self) -> usize {
self.iter.count().saturating_sub(self.n)
}
#[inline]
fn last(mut self) -> Option<I::Item> {
if self.n == 0 {
self.iter.last()
} else {
let next = self.next();
if next.is_some() {
// recurse. n should be 0.
self.last().or(next)
} else {
None
}
}
}
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
let (lower, upper) = self.iter.size_hint();
let lower = lower.saturating_sub(self.n);
let upper = upper.map(|x| x.saturating_sub(self.n));
(lower, upper)
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn try_fold<Acc, Fold, R>(&mut self, init: Acc, fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
let n = self.n;
self.n = 0;
if n > 0 {
// nth(n) skips n+1
if self.iter.nth(n - 1).is_none() {
return Try::from_ok(init);
}
}
self.iter.try_fold(init, fold)
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn fold<Acc, Fold>(mut self, init: Acc, fold: Fold) -> Acc
where Fold: FnMut(Acc, Self::Item) -> Acc,
{
if self.n > 0 {
// nth(n) skips n+1
if self.iter.nth(self.n - 1).is_none() {
return init;
}
}
self.iter.fold(init, fold)
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I> ExactSizeIterator for Skip<I> where I: ExactSizeIterator {}
#[stable(feature = "double_ended_skip_iterator", since = "1.9.0")]
impl<I> DoubleEndedIterator for Skip<I> where I: DoubleEndedIterator + ExactSizeIterator {
fn next_back(&mut self) -> Option<Self::Item> {
if self.len() > 0 {
self.iter.next_back()
} else {
None
}
}
fn try_rfold<Acc, Fold, R>(&mut self, init: Acc, mut fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
let mut n = self.len();
if n == 0 {
Try::from_ok(init)
} else {
self.iter.try_rfold(init, move |acc, x| {
n -= 1;
let r = fold(acc, x);
if n == 0 { LoopState::Break(r) }
else { LoopState::from_try(r) }
}).into_try()
}
}
}
#[unstable(feature = "fused", issue = "35602")]
impl<I> FusedIterator for Skip<I> where I: FusedIterator {}
/// An iterator that only iterates over the first `n` iterations of `iter`.
///
/// This `struct` is created by the [`take`] method on [`Iterator`]. See its
/// documentation for more.
///
/// [`take`]: trait.Iterator.html#method.take
/// [`Iterator`]: trait.Iterator.html
#[derive(Clone, Debug)]
#[must_use = "iterator adaptors are lazy and do nothing unless consumed"]
#[stable(feature = "rust1", since = "1.0.0")]
pub struct Take<I> {
iter: I,
n: usize
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I> Iterator for Take<I> where I: Iterator{
type Item = <I as Iterator>::Item;
#[inline]
fn next(&mut self) -> Option<<I as Iterator>::Item> {
if self.n != 0 {
self.n -= 1;
self.iter.next()
} else {
None
}
}
#[inline]
fn nth(&mut self, n: usize) -> Option<I::Item> {
if self.n > n {
self.n -= n + 1;
self.iter.nth(n)
} else {
if self.n > 0 {
self.iter.nth(self.n - 1);
self.n = 0;
}
None
}
}
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
let (lower, upper) = self.iter.size_hint();
let lower = cmp::min(lower, self.n);
let upper = match upper {
Some(x) if x < self.n => Some(x),
_ => Some(self.n)
};
(lower, upper)
}
#[inline]
fn try_fold<Acc, Fold, R>(&mut self, init: Acc, mut fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
if self.n == 0 {
Try::from_ok(init)
} else {
let n = &mut self.n;
self.iter.try_fold(init, move |acc, x| {
*n -= 1;
let r = fold(acc, x);
if *n == 0 { LoopState::Break(r) }
else { LoopState::from_try(r) }
}).into_try()
}
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I> ExactSizeIterator for Take<I> where I: ExactSizeIterator {}
#[unstable(feature = "fused", issue = "35602")]
impl<I> FusedIterator for Take<I> where I: FusedIterator {}
/// An iterator to maintain state while iterating another iterator.
///
/// This `struct` is created by the [`scan`] method on [`Iterator`]. See its
/// documentation for more.
///
/// [`scan`]: trait.Iterator.html#method.scan
/// [`Iterator`]: trait.Iterator.html
#[must_use = "iterator adaptors are lazy and do nothing unless consumed"]
#[stable(feature = "rust1", since = "1.0.0")]
#[derive(Clone)]
pub struct Scan<I, St, F> {
iter: I,
f: F,
state: St,
}
#[stable(feature = "core_impl_debug", since = "1.9.0")]
impl<I: fmt::Debug, St: fmt::Debug, F> fmt::Debug for Scan<I, St, F> {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
f.debug_struct("Scan")
.field("iter", &self.iter)
.field("state", &self.state)
.finish()
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<B, I, St, F> Iterator for Scan<I, St, F> where
I: Iterator,
F: FnMut(&mut St, I::Item) -> Option<B>,
{
type Item = B;
#[inline]
fn next(&mut self) -> Option<B> {
self.iter.next().and_then(|a| (self.f)(&mut self.state, a))
}
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
let (_, upper) = self.iter.size_hint();
(0, upper) // can't know a lower bound, due to the scan function
}
#[inline]
fn try_fold<Acc, Fold, R>(&mut self, init: Acc, mut fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
let state = &mut self.state;
let f = &mut self.f;
self.iter.try_fold(init, move |acc, x| {
match f(state, x) {
None => LoopState::Break(Try::from_ok(acc)),
Some(x) => LoopState::from_try(fold(acc, x)),
}
}).into_try()
}
}
/// An iterator that maps each element to an iterator, and yields the elements
/// of the produced iterators.
///
/// This `struct` is created by the [`flat_map`] method on [`Iterator`]. See its
/// documentation for more.
///
/// [`flat_map`]: trait.Iterator.html#method.flat_map
/// [`Iterator`]: trait.Iterator.html
#[must_use = "iterator adaptors are lazy and do nothing unless consumed"]
#[stable(feature = "rust1", since = "1.0.0")]
#[derive(Clone)]
pub struct FlatMap<I, U: IntoIterator, F> {
iter: I,
f: F,
frontiter: Option<U::IntoIter>,
backiter: Option<U::IntoIter>,
}
#[stable(feature = "core_impl_debug", since = "1.9.0")]
impl<I: fmt::Debug, U: IntoIterator, F> fmt::Debug for FlatMap<I, U, F>
where U::IntoIter: fmt::Debug
{
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
f.debug_struct("FlatMap")
.field("iter", &self.iter)
.field("frontiter", &self.frontiter)
.field("backiter", &self.backiter)
.finish()
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I: Iterator, U: IntoIterator, F> Iterator for FlatMap<I, U, F>
where F: FnMut(I::Item) -> U,
{
type Item = U::Item;
#[inline]
fn next(&mut self) -> Option<U::Item> {
loop {
if let Some(ref mut inner) = self.frontiter {
if let Some(x) = inner.by_ref().next() {
return Some(x)
}
}
match self.iter.next().map(&mut self.f) {
None => return self.backiter.as_mut().and_then(|it| it.next()),
next => self.frontiter = next.map(IntoIterator::into_iter),
}
}
}
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
let (flo, fhi) = self.frontiter.as_ref().map_or((0, Some(0)), |it| it.size_hint());
let (blo, bhi) = self.backiter.as_ref().map_or((0, Some(0)), |it| it.size_hint());
let lo = flo.saturating_add(blo);
match (self.iter.size_hint(), fhi, bhi) {
((0, Some(0)), Some(a), Some(b)) => (lo, a.checked_add(b)),
_ => (lo, None)
}
}
#[inline]
fn try_fold<Acc, Fold, R>(&mut self, mut init: Acc, mut fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
if let Some(ref mut front) = self.frontiter {
init = front.try_fold(init, &mut fold)?;
}
self.frontiter = None;
{
let f = &mut self.f;
let frontiter = &mut self.frontiter;
init = self.iter.try_fold(init, |acc, x| {
let mut mid = f(x).into_iter();
let r = mid.try_fold(acc, &mut fold);
*frontiter = Some(mid);
r
})?;
}
self.frontiter = None;
if let Some(ref mut back) = self.backiter {
init = back.try_fold(init, &mut fold)?;
}
self.backiter = None;
Try::from_ok(init)
}
#[inline]
fn fold<Acc, Fold>(self, init: Acc, mut fold: Fold) -> Acc
where Fold: FnMut(Acc, Self::Item) -> Acc,
{
self.frontiter.into_iter()
.chain(self.iter.map(self.f).map(U::into_iter))
.chain(self.backiter)
.fold(init, |acc, iter| iter.fold(acc, &mut fold))
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I: DoubleEndedIterator, U, F> DoubleEndedIterator for FlatMap<I, U, F> where
F: FnMut(I::Item) -> U,
U: IntoIterator,
U::IntoIter: DoubleEndedIterator
{
#[inline]
fn next_back(&mut self) -> Option<U::Item> {
loop {
if let Some(ref mut inner) = self.backiter {
if let Some(y) = inner.next_back() {
return Some(y)
}
}
match self.iter.next_back().map(&mut self.f) {
None => return self.frontiter.as_mut().and_then(|it| it.next_back()),
next => self.backiter = next.map(IntoIterator::into_iter),
}
}
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn try_rfold<Acc, Fold, R>(&mut self, mut init: Acc, mut fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
if let Some(ref mut back) = self.backiter {
init = back.try_rfold(init, &mut fold)?;
}
self.backiter = None;
{
let f = &mut self.f;
let backiter = &mut self.backiter;
init = self.iter.try_rfold(init, |acc, x| {
let mut mid = f(x).into_iter();
let r = mid.try_rfold(acc, &mut fold);
*backiter = Some(mid);
r
})?;
}
self.backiter = None;
if let Some(ref mut front) = self.frontiter {
init = front.try_rfold(init, &mut fold)?;
}
self.frontiter = None;
Try::from_ok(init)
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn rfold<Acc, Fold>(self, init: Acc, mut fold: Fold) -> Acc
where Fold: FnMut(Acc, Self::Item) -> Acc,
{
self.frontiter.into_iter()
.chain(self.iter.map(self.f).map(U::into_iter))
.chain(self.backiter)
.rfold(init, |acc, iter| iter.rfold(acc, &mut fold))
}
}
#[unstable(feature = "fused", issue = "35602")]
impl<I, U, F> FusedIterator for FlatMap<I, U, F>
where I: FusedIterator, U: IntoIterator, F: FnMut(I::Item) -> U {}
/// An iterator that yields `None` forever after the underlying iterator
/// yields `None` once.
///
/// This `struct` is created by the [`fuse`] method on [`Iterator`]. See its
/// documentation for more.
///
/// [`fuse`]: trait.Iterator.html#method.fuse
/// [`Iterator`]: trait.Iterator.html
#[derive(Clone, Debug)]
#[must_use = "iterator adaptors are lazy and do nothing unless consumed"]
#[stable(feature = "rust1", since = "1.0.0")]
pub struct Fuse<I> {
iter: I,
done: bool
}
#[unstable(feature = "fused", issue = "35602")]
impl<I> FusedIterator for Fuse<I> where I: Iterator {}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I> Iterator for Fuse<I> where I: Iterator {
type Item = <I as Iterator>::Item;
#[inline]
default fn next(&mut self) -> Option<<I as Iterator>::Item> {
if self.done {
None
} else {
let next = self.iter.next();
self.done = next.is_none();
next
}
}
#[inline]
default fn nth(&mut self, n: usize) -> Option<I::Item> {
if self.done {
None
} else {
let nth = self.iter.nth(n);
self.done = nth.is_none();
nth
}
}
#[inline]
default fn last(self) -> Option<I::Item> {
if self.done {
None
} else {
self.iter.last()
}
}
#[inline]
default fn count(self) -> usize {
if self.done {
0
} else {
self.iter.count()
}
}
#[inline]
default fn size_hint(&self) -> (usize, Option<usize>) {
if self.done {
(0, Some(0))
} else {
self.iter.size_hint()
}
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
default fn try_fold<Acc, Fold, R>(&mut self, init: Acc, fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
if self.done {
Try::from_ok(init)
} else {
let acc = self.iter.try_fold(init, fold)?;
self.done = true;
Try::from_ok(acc)
}
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
default fn fold<Acc, Fold>(self, init: Acc, fold: Fold) -> Acc
where Fold: FnMut(Acc, Self::Item) -> Acc,
{
if self.done {
init
} else {
self.iter.fold(init, fold)
}
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I> DoubleEndedIterator for Fuse<I> where I: DoubleEndedIterator {
#[inline]
default fn next_back(&mut self) -> Option<<I as Iterator>::Item> {
if self.done {
None
} else {
let next = self.iter.next_back();
self.done = next.is_none();
next
}
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
default fn try_rfold<Acc, Fold, R>(&mut self, init: Acc, fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
if self.done {
Try::from_ok(init)
} else {
let acc = self.iter.try_rfold(init, fold)?;
self.done = true;
Try::from_ok(acc)
}
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
default fn rfold<Acc, Fold>(self, init: Acc, fold: Fold) -> Acc
where Fold: FnMut(Acc, Self::Item) -> Acc,
{
if self.done {
init
} else {
self.iter.rfold(init, fold)
}
}
}
unsafe impl<I> TrustedRandomAccess for Fuse<I>
where I: TrustedRandomAccess,
{
unsafe fn get_unchecked(&mut self, i: usize) -> I::Item {
self.iter.get_unchecked(i)
}
fn may_have_side_effect() -> bool {
I::may_have_side_effect()
}
}
#[unstable(feature = "fused", issue = "35602")]
impl<I> Iterator for Fuse<I> where I: FusedIterator {
#[inline]
fn next(&mut self) -> Option<<I as Iterator>::Item> {
self.iter.next()
}
#[inline]
fn nth(&mut self, n: usize) -> Option<I::Item> {
self.iter.nth(n)
}
#[inline]
fn last(self) -> Option<I::Item> {
self.iter.last()
}
#[inline]
fn count(self) -> usize {
self.iter.count()
}
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
self.iter.size_hint()
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn try_fold<Acc, Fold, R>(&mut self, init: Acc, fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
self.iter.try_fold(init, fold)
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn fold<Acc, Fold>(self, init: Acc, fold: Fold) -> Acc
where Fold: FnMut(Acc, Self::Item) -> Acc,
{
self.iter.fold(init, fold)
}
}
#[unstable(feature = "fused", reason = "recently added", issue = "35602")]
impl<I> DoubleEndedIterator for Fuse<I>
where I: DoubleEndedIterator + FusedIterator
{
#[inline]
fn next_back(&mut self) -> Option<<I as Iterator>::Item> {
self.iter.next_back()
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn try_rfold<Acc, Fold, R>(&mut self, init: Acc, fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
self.iter.try_rfold(init, fold)
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn rfold<Acc, Fold>(self, init: Acc, fold: Fold) -> Acc
where Fold: FnMut(Acc, Self::Item) -> Acc,
{
self.iter.rfold(init, fold)
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I> ExactSizeIterator for Fuse<I> where I: ExactSizeIterator {
fn len(&self) -> usize {
self.iter.len()
}
fn is_empty(&self) -> bool {
self.iter.is_empty()
}
}
/// An iterator that calls a function with a reference to each element before
/// yielding it.
///
/// This `struct` is created by the [`inspect`] method on [`Iterator`]. See its
/// documentation for more.
///
/// [`inspect`]: trait.Iterator.html#method.inspect
/// [`Iterator`]: trait.Iterator.html
#[must_use = "iterator adaptors are lazy and do nothing unless consumed"]
#[stable(feature = "rust1", since = "1.0.0")]
#[derive(Clone)]
pub struct Inspect<I, F> {
iter: I,
f: F,
}
#[stable(feature = "core_impl_debug", since = "1.9.0")]
impl<I: fmt::Debug, F> fmt::Debug for Inspect<I, F> {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
f.debug_struct("Inspect")
.field("iter", &self.iter)
.finish()
}
}
impl<I: Iterator, F> Inspect<I, F> where F: FnMut(&I::Item) {
#[inline]
fn do_inspect(&mut self, elt: Option<I::Item>) -> Option<I::Item> {
if let Some(ref a) = elt {
(self.f)(a);
}
elt
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I: Iterator, F> Iterator for Inspect<I, F> where F: FnMut(&I::Item) {
type Item = I::Item;
#[inline]
fn next(&mut self) -> Option<I::Item> {
let next = self.iter.next();
self.do_inspect(next)
}
#[inline]
fn size_hint(&self) -> (usize, Option<usize>) {
self.iter.size_hint()
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn try_fold<Acc, Fold, R>(&mut self, init: Acc, mut fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
let f = &mut self.f;
self.iter.try_fold(init, move |acc, item| { f(&item); fold(acc, item) })
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn fold<Acc, Fold>(self, init: Acc, mut fold: Fold) -> Acc
where Fold: FnMut(Acc, Self::Item) -> Acc,
{
let mut f = self.f;
self.iter.fold(init, move |acc, item| { f(&item); fold(acc, item) })
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I: DoubleEndedIterator, F> DoubleEndedIterator for Inspect<I, F>
where F: FnMut(&I::Item),
{
#[inline]
fn next_back(&mut self) -> Option<I::Item> {
let next = self.iter.next_back();
self.do_inspect(next)
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn try_rfold<Acc, Fold, R>(&mut self, init: Acc, mut fold: Fold) -> R where
Self: Sized, Fold: FnMut(Acc, Self::Item) -> R, R: Try<Ok=Acc>
{
let f = &mut self.f;
self.iter.try_rfold(init, move |acc, item| { f(&item); fold(acc, item) })
}
Add more custom folding to `core::iter` adaptors Many of the iterator adaptors will perform faster folds if they forward to their inner iterator's folds, especially for inner types like `Chain` which are optimized too. The following types are newly specialized: | Type | `fold` | `rfold` | | ----------- | ------ | ------- | | `Enumerate` | ✓ | ✓ | | `Filter` | ✓ | ✓ | | `FilterMap` | ✓ | ✓ | | `FlatMap` | exists | ✓ | | `Fuse` | ✓ | ✓ | | `Inspect` | ✓ | ✓ | | `Peekable` | ✓ | N/A¹ | | `Skip` | ✓ | N/A² | | `SkipWhile` | ✓ | N/A¹ | ¹ not a `DoubleEndedIterator` ² `Skip::next_back` doesn't pull skipped items at all, but this couldn't be avoided if `Skip::rfold` were to call its inner iterator's `rfold`. Benchmarks ---------- In the following results, plain `_sum` computes the sum of a million integers -- note that `sum()` is implemented with `fold()`. The `_ref_sum` variants do the same on a `by_ref()` iterator, which is limited to calling `next()` one by one, without specialized `fold`. The `chain` variants perform the same tests on two iterators chained together, to show a greater benefit of forwarding `fold` internally. test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228) test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676) test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110) test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334) test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051) test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013) test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188) test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894) test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440) test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972) test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507) test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472) test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395) test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341) test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748) test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616) test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371) test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928) test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702) test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320) test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186) test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712) test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480) test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309) test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198) test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645) test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252) test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054) test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845) test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892) test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804) test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
2017-09-25 22:53:08 -05:00
#[inline]
fn rfold<Acc, Fold>(self, init: Acc, mut fold: Fold) -> Acc
where Fold: FnMut(Acc, Self::Item) -> Acc,
{
let mut f = self.f;
self.iter.rfold(init, move |acc, item| { f(&item); fold(acc, item) })
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<I: ExactSizeIterator, F> ExactSizeIterator for Inspect<I, F>
where F: FnMut(&I::Item)
{
fn len(&self) -> usize {
self.iter.len()
}
fn is_empty(&self) -> bool {
self.iter.is_empty()
}
}
#[unstable(feature = "fused", issue = "35602")]
impl<I: FusedIterator, F> FusedIterator for Inspect<I, F>
where F: FnMut(&I::Item) {}