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rust/library/alloc/src/slice.rs

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//! A dynamically-sized view into a contiguous sequence, `[T]`.
//!
//! *[See also the slice primitive type](../../std/primitive.slice.html).*
//!
//! Slices are a view into a block of memory represented as a pointer and a
//! length.
//!
//! ```
//! // slicing a Vec
//! let vec = vec![1, 2, 3];
//! let int_slice = &vec[..];
//! // coercing an array to a slice
//! let str_slice: &[&str] = &["one", "two", "three"];
//! ```
//!
//! Slices are either mutable or shared. The shared slice type is `&[T]`,
//! while the mutable slice type is `&mut [T]`, where `T` represents the element
//! type. For example, you can mutate the block of memory that a mutable slice
//! points to:
//!
//! ```
//! let x = &mut [1, 2, 3];
//! x[1] = 7;
//! assert_eq!(x, &[1, 7, 3]);
//! ```
//!
//! Here are some of the things this module contains:
//!
//! ## Structs
//!
//! There are several structs that are useful for slices, such as [`Iter`], which
//! represents iteration over a slice.
//!
//! ## Trait Implementations
//!
//! There are several implementations of common traits for slices. Some examples
//! include:
//!
//! * [`Clone`]
//! * [`Eq`], [`Ord`] - for slices whose element type are [`Eq`] or [`Ord`].
//! * [`Hash`] - for slices whose element type is [`Hash`].
//!
//! ## Iteration
//!
//! The slices implement `IntoIterator`. The iterator yields references to the
//! slice elements.
//!
//! ```
//! let numbers = &[0, 1, 2];
//! for n in numbers {
//! println!("{} is a number!", n);
//! }
//! ```
//!
//! The mutable slice yields mutable references to the elements:
//!
//! ```
//! let mut scores = [7, 8, 9];
//! for score in &mut scores[..] {
//! *score += 1;
//! }
//! ```
//!
//! This iterator yields mutable references to the slice's elements, so while
//! the element type of the slice is `i32`, the element type of the iterator is
//! `&mut i32`.
//!
//! * [`.iter`] and [`.iter_mut`] are the explicit methods to return the default
//! iterators.
//! * Further methods that return iterators are [`.split`], [`.splitn`],
//! [`.chunks`], [`.windows`] and more.
//!
//! [`Hash`]: core::hash::Hash
//! [`.iter`]: ../../std/primitive.slice.html#method.iter
//! [`.iter_mut`]: ../../std/primitive.slice.html#method.iter_mut
//! [`.split`]: ../../std/primitive.slice.html#method.split
//! [`.splitn`]: ../../std/primitive.slice.html#method.splitn
//! [`.chunks`]: ../../std/primitive.slice.html#method.chunks
//! [`.windows`]: ../../std/primitive.slice.html#method.windows
#![stable(feature = "rust1", since = "1.0.0")]
// Many of the usings in this module are only used in the test configuration.
// It's cleaner to just turn off the unused_imports warning than to fix them.
#![cfg_attr(test, allow(unused_imports, dead_code))]
use core::borrow::{Borrow, BorrowMut};
use core::cmp::Ordering::{self, Less};
use core::mem::{self, size_of};
use core::ptr;
use crate::alloc::{Allocator, Global};
use crate::borrow::ToOwned;
use crate::boxed::Box;
use crate::vec::Vec;
#[unstable(feature = "array_chunks", issue = "74985")]
pub use core::slice::ArrayChunks;
#[unstable(feature = "array_chunks", issue = "74985")]
pub use core::slice::ArrayChunksMut;
#[unstable(feature = "array_windows", issue = "75027")]
pub use core::slice::ArrayWindows;
#[stable(feature = "slice_get_slice", since = "1.28.0")]
pub use core::slice::SliceIndex;
#[stable(feature = "from_ref", since = "1.28.0")]
pub use core::slice::{from_mut, from_ref};
#[stable(feature = "rust1", since = "1.0.0")]
pub use core::slice::{from_raw_parts, from_raw_parts_mut};
#[stable(feature = "rust1", since = "1.0.0")]
pub use core::slice::{Chunks, Windows};
#[stable(feature = "chunks_exact", since = "1.31.0")]
pub use core::slice::{ChunksExact, ChunksExactMut};
#[stable(feature = "rust1", since = "1.0.0")]
pub use core::slice::{ChunksMut, Split, SplitMut};
#[stable(feature = "rust1", since = "1.0.0")]
pub use core::slice::{Iter, IterMut};
#[stable(feature = "rchunks", since = "1.31.0")]
pub use core::slice::{RChunks, RChunksExact, RChunksExactMut, RChunksMut};
#[stable(feature = "slice_rsplit", since = "1.27.0")]
pub use core::slice::{RSplit, RSplitMut};
#[stable(feature = "rust1", since = "1.0.0")]
pub use core::slice::{RSplitN, RSplitNMut, SplitN, SplitNMut};
////////////////////////////////////////////////////////////////////////////////
// Basic slice extension methods
////////////////////////////////////////////////////////////////////////////////
// HACK(japaric) needed for the implementation of `vec!` macro during testing
// N.B., see the `hack` module in this file for more details.
#[cfg(test)]
pub use hack::into_vec;
// HACK(japaric) needed for the implementation of `Vec::clone` during testing
// N.B., see the `hack` module in this file for more details.
#[cfg(test)]
pub use hack::to_vec;
// HACK(japaric): With cfg(test) `impl [T]` is not available, these three
// functions are actually methods that are in `impl [T]` but not in
// `core::slice::SliceExt` - we need to supply these functions for the
// `test_permutations` test
mod hack {
use core::alloc::Allocator;
use crate::boxed::Box;
use crate::vec::Vec;
// We shouldn't add inline attribute to this since this is used in
// `vec!` macro mostly and causes perf regression. See #71204 for
// discussion and perf results.
pub fn into_vec<T, A: Allocator>(b: Box<[T], A>) -> Vec<T, A> {
unsafe {
let len = b.len();
let (b, alloc) = Box::into_raw_with_allocator(b);
Vec::from_raw_parts_in(b as *mut T, len, len, alloc)
}
}
#[inline]
pub fn to_vec<T: ConvertVec, A: Allocator>(s: &[T], alloc: A) -> Vec<T, A> {
T::to_vec(s, alloc)
}
pub trait ConvertVec {
fn to_vec<A: Allocator>(s: &[Self], alloc: A) -> Vec<Self, A>
where
Self: Sized;
}
impl<T: Clone> ConvertVec for T {
#[inline]
default fn to_vec<A: Allocator>(s: &[Self], alloc: A) -> Vec<Self, A> {
struct DropGuard<'a, T, A: Allocator> {
vec: &'a mut Vec<T, A>,
num_init: usize,
}
impl<'a, T, A: Allocator> Drop for DropGuard<'a, T, A> {
#[inline]
fn drop(&mut self) {
// SAFETY:
// items were marked initialized in the loop below
unsafe {
self.vec.set_len(self.num_init);
}
}
}
let mut vec = Vec::with_capacity_in(s.len(), alloc);
let mut guard = DropGuard { vec: &mut vec, num_init: 0 };
let slots = guard.vec.spare_capacity_mut();
// .take(slots.len()) is necessary for LLVM to remove bounds checks
// and has better codegen than zip.
for (i, b) in s.iter().enumerate().take(slots.len()) {
guard.num_init = i;
slots[i].write(b.clone());
}
core::mem::forget(guard);
// SAFETY:
// the vec was allocated and initialized above to at least this length.
unsafe {
vec.set_len(s.len());
}
vec
}
}
impl<T: Copy> ConvertVec for T {
#[inline]
fn to_vec<A: Allocator>(s: &[Self], alloc: A) -> Vec<Self, A> {
let mut v = Vec::with_capacity_in(s.len(), alloc);
// SAFETY:
// allocated above with the capacity of `s`, and initialize to `s.len()` in
// ptr::copy_to_non_overlapping below.
unsafe {
s.as_ptr().copy_to_nonoverlapping(v.as_mut_ptr(), s.len());
v.set_len(s.len());
}
v
}
}
}
#[lang = "slice_alloc"]
#[cfg(not(test))]
impl<T> [T] {
/// Sorts the slice.
///
/// This sort is stable (i.e., does not reorder equal elements) and *O*(*n* \* log(*n*)) worst-case.
///
/// When applicable, unstable sorting is preferred because it is generally faster than stable
/// sorting and it doesn't allocate auxiliary memory.
/// See [`sort_unstable`](#method.sort_unstable).
///
/// # Current implementation
///
/// The current algorithm is an adaptive, iterative merge sort inspired by
/// [timsort](https://en.wikipedia.org/wiki/Timsort).
/// It is designed to be very fast in cases where the slice is nearly sorted, or consists of
/// two or more sorted sequences concatenated one after another.
///
/// Also, it allocates temporary storage half the size of `self`, but for short slices a
/// non-allocating insertion sort is used instead.
///
/// # Examples
///
/// ```
/// let mut v = [-5, 4, 1, -3, 2];
///
/// v.sort();
/// assert!(v == [-5, -3, 1, 2, 4]);
/// ```
#[stable(feature = "rust1", since = "1.0.0")]
#[inline]
pub fn sort(&mut self)
where
T: Ord,
{
merge_sort(self, |a, b| a.lt(b));
}
/// Sorts the slice with a comparator function.
///
/// This sort is stable (i.e., does not reorder equal elements) and *O*(*n* \* log(*n*)) worst-case.
///
/// The comparator function must define a total ordering for the elements in the slice. If
/// the ordering is not total, the order of the elements is unspecified. An order is a
/// total order if it is (for all `a`, `b` and `c`):
///
/// * total and antisymmetric: exactly one of `a < b`, `a == b` or `a > b` is true, and
/// * transitive, `a < b` and `b < c` implies `a < c`. The same must hold for both `==` and `>`.
///
/// For example, while [`f64`] doesn't implement [`Ord`] because `NaN != NaN`, we can use
/// `partial_cmp` as our sort function when we know the slice doesn't contain a `NaN`.
///
/// ```
/// let mut floats = [5f64, 4.0, 1.0, 3.0, 2.0];
/// floats.sort_by(|a, b| a.partial_cmp(b).unwrap());
/// assert_eq!(floats, [1.0, 2.0, 3.0, 4.0, 5.0]);
/// ```
///
/// When applicable, unstable sorting is preferred because it is generally faster than stable
/// sorting and it doesn't allocate auxiliary memory.
/// See [`sort_unstable_by`](#method.sort_unstable_by).
///
/// # Current implementation
///
/// The current algorithm is an adaptive, iterative merge sort inspired by
/// [timsort](https://en.wikipedia.org/wiki/Timsort).
/// It is designed to be very fast in cases where the slice is nearly sorted, or consists of
/// two or more sorted sequences concatenated one after another.
///
/// Also, it allocates temporary storage half the size of `self`, but for short slices a
/// non-allocating insertion sort is used instead.
///
/// # Examples
///
/// ```
/// let mut v = [5, 4, 1, 3, 2];
/// v.sort_by(|a, b| a.cmp(b));
/// assert!(v == [1, 2, 3, 4, 5]);
///
/// // reverse sorting
/// v.sort_by(|a, b| b.cmp(a));
/// assert!(v == [5, 4, 3, 2, 1]);
/// ```
#[stable(feature = "rust1", since = "1.0.0")]
#[inline]
pub fn sort_by<F>(&mut self, mut compare: F)
where
F: FnMut(&T, &T) -> Ordering,
{
merge_sort(self, |a, b| compare(a, b) == Less);
}
/// Sorts the slice with a key extraction function.
///
/// This sort is stable (i.e., does not reorder equal elements) and *O*(*m* \* *n* \* log(*n*))
/// worst-case, where the key function is *O*(*m*).
///
/// For expensive key functions (e.g. functions that are not simple property accesses or
/// basic operations), [`sort_by_cached_key`](#method.sort_by_cached_key) is likely to be
/// significantly faster, as it does not recompute element keys.
///
/// When applicable, unstable sorting is preferred because it is generally faster than stable
/// sorting and it doesn't allocate auxiliary memory.
/// See [`sort_unstable_by_key`](#method.sort_unstable_by_key).
///
/// # Current implementation
///
/// The current algorithm is an adaptive, iterative merge sort inspired by
/// [timsort](https://en.wikipedia.org/wiki/Timsort).
/// It is designed to be very fast in cases where the slice is nearly sorted, or consists of
/// two or more sorted sequences concatenated one after another.
///
/// Also, it allocates temporary storage half the size of `self`, but for short slices a
/// non-allocating insertion sort is used instead.
///
/// # Examples
///
/// ```
/// let mut v = [-5i32, 4, 1, -3, 2];
///
/// v.sort_by_key(|k| k.abs());
/// assert!(v == [1, 2, -3, 4, -5]);
/// ```
#[stable(feature = "slice_sort_by_key", since = "1.7.0")]
#[inline]
pub fn sort_by_key<K, F>(&mut self, mut f: F)
where
F: FnMut(&T) -> K,
K: Ord,
{
merge_sort(self, |a, b| f(a).lt(&f(b)));
}
/// Sorts the slice with a key extraction function.
///
/// During sorting, the key function is called only once per element.
///
/// This sort is stable (i.e., does not reorder equal elements) and *O*(*m* \* *n* + *n* \* log(*n*))
/// worst-case, where the key function is *O*(*m*).
///
/// For simple key functions (e.g., functions that are property accesses or
/// basic operations), [`sort_by_key`](#method.sort_by_key) is likely to be
/// faster.
///
/// # Current implementation
///
/// The current algorithm is based on [pattern-defeating quicksort][pdqsort] by Orson Peters,
/// which combines the fast average case of randomized quicksort with the fast worst case of
/// heapsort, while achieving linear time on slices with certain patterns. It uses some
/// randomization to avoid degenerate cases, but with a fixed seed to always provide
/// deterministic behavior.
///
/// In the worst case, the algorithm allocates temporary storage in a `Vec<(K, usize)>` the
/// length of the slice.
///
/// # Examples
///
/// ```
/// let mut v = [-5i32, 4, 32, -3, 2];
///
/// v.sort_by_cached_key(|k| k.to_string());
/// assert!(v == [-3, -5, 2, 32, 4]);
/// ```
///
/// [pdqsort]: https://github.com/orlp/pdqsort
#[stable(feature = "slice_sort_by_cached_key", since = "1.34.0")]
#[inline]
pub fn sort_by_cached_key<K, F>(&mut self, f: F)
where
F: FnMut(&T) -> K,
K: Ord,
{
// Helper macro for indexing our vector by the smallest possible type, to reduce allocation.
macro_rules! sort_by_key {
($t:ty, $slice:ident, $f:ident) => {{
let mut indices: Vec<_> =
$slice.iter().map($f).enumerate().map(|(i, k)| (k, i as $t)).collect();
// The elements of `indices` are unique, as they are indexed, so any sort will be
// stable with respect to the original slice. We use `sort_unstable` here because
// it requires less memory allocation.
indices.sort_unstable();
for i in 0..$slice.len() {
let mut index = indices[i].1;
while (index as usize) < i {
index = indices[index as usize].1;
}
indices[i].1 = index;
$slice.swap(i, index as usize);
}
}};
}
let sz_u8 = mem::size_of::<(K, u8)>();
let sz_u16 = mem::size_of::<(K, u16)>();
let sz_u32 = mem::size_of::<(K, u32)>();
let sz_usize = mem::size_of::<(K, usize)>();
let len = self.len();
if len < 2 {
return;
}
if sz_u8 < sz_u16 && len <= (u8::MAX as usize) {
return sort_by_key!(u8, self, f);
}
if sz_u16 < sz_u32 && len <= (u16::MAX as usize) {
return sort_by_key!(u16, self, f);
}
if sz_u32 < sz_usize && len <= (u32::MAX as usize) {
return sort_by_key!(u32, self, f);
}
sort_by_key!(usize, self, f)
}
/// Copies `self` into a new `Vec`.
///
/// # Examples
///
/// ```
/// let s = [10, 40, 30];
/// let x = s.to_vec();
/// // Here, `s` and `x` can be modified independently.
/// ```
#[rustc_conversion_suggestion]
#[stable(feature = "rust1", since = "1.0.0")]
#[inline]
pub fn to_vec(&self) -> Vec<T>
where
T: Clone,
{
self.to_vec_in(Global)
}
/// Copies `self` into a new `Vec` with an allocator.
///
/// # Examples
///
/// ```
/// #![feature(allocator_api)]
///
/// use std::alloc::System;
///
/// let s = [10, 40, 30];
/// let x = s.to_vec_in(System);
/// // Here, `s` and `x` can be modified independently.
/// ```
#[inline]
#[unstable(feature = "allocator_api", issue = "32838")]
pub fn to_vec_in<A: Allocator>(&self, alloc: A) -> Vec<T, A>
where
T: Clone,
{
// N.B., see the `hack` module in this file for more details.
hack::to_vec(self, alloc)
}
/// Converts `self` into a vector without clones or allocation.
///
/// The resulting vector can be converted back into a box via
/// `Vec<T>`'s `into_boxed_slice` method.
///
/// # Examples
///
/// ```
/// let s: Box<[i32]> = Box::new([10, 40, 30]);
/// let x = s.into_vec();
/// // `s` cannot be used anymore because it has been converted into `x`.
///
/// assert_eq!(x, vec![10, 40, 30]);
/// ```
#[stable(feature = "rust1", since = "1.0.0")]
#[inline]
pub fn into_vec<A: Allocator>(self: Box<Self, A>) -> Vec<T, A> {
// N.B., see the `hack` module in this file for more details.
hack::into_vec(self)
}
/// Creates a vector by repeating a slice `n` times.
///
/// # Panics
///
/// This function will panic if the capacity would overflow.
///
/// # Examples
///
/// Basic usage:
///
/// ```
/// assert_eq!([1, 2].repeat(3), vec![1, 2, 1, 2, 1, 2]);
/// ```
///
/// A panic upon overflow:
///
/// ```should_panic
/// // this will panic at runtime
/// b"0123456789abcdef".repeat(usize::MAX);
/// ```
#[stable(feature = "repeat_generic_slice", since = "1.40.0")]
pub fn repeat(&self, n: usize) -> Vec<T>
where
T: Copy,
{
if n == 0 {
return Vec::new();
}
// If `n` is larger than zero, it can be split as
// `n = 2^expn + rem (2^expn > rem, expn >= 0, rem >= 0)`.
// `2^expn` is the number represented by the leftmost '1' bit of `n`,
// and `rem` is the remaining part of `n`.
// Using `Vec` to access `set_len()`.
let capacity = self.len().checked_mul(n).expect("capacity overflow");
let mut buf = Vec::with_capacity(capacity);
// `2^expn` repetition is done by doubling `buf` `expn`-times.
buf.extend(self);
{
let mut m = n >> 1;
// If `m > 0`, there are remaining bits up to the leftmost '1'.
while m > 0 {
// `buf.extend(buf)`:
unsafe {
ptr::copy_nonoverlapping(
buf.as_ptr(),
(buf.as_mut_ptr() as *mut T).add(buf.len()),
buf.len(),
);
// `buf` has capacity of `self.len() * n`.
let buf_len = buf.len();
buf.set_len(buf_len * 2);
}
m >>= 1;
}
}
// `rem` (`= n - 2^expn`) repetition is done by copying
// first `rem` repetitions from `buf` itself.
let rem_len = capacity - buf.len(); // `self.len() * rem`
if rem_len > 0 {
// `buf.extend(buf[0 .. rem_len])`:
unsafe {
// This is non-overlapping since `2^expn > rem`.
ptr::copy_nonoverlapping(
buf.as_ptr(),
(buf.as_mut_ptr() as *mut T).add(buf.len()),
rem_len,
);
// `buf.len() + rem_len` equals to `buf.capacity()` (`= self.len() * n`).
buf.set_len(capacity);
}
}
buf
}
/// Flattens a slice of `T` into a single value `Self::Output`.
///
/// # Examples
///
/// ```
/// assert_eq!(["hello", "world"].concat(), "helloworld");
/// assert_eq!([[1, 2], [3, 4]].concat(), [1, 2, 3, 4]);
/// ```
#[stable(feature = "rust1", since = "1.0.0")]
pub fn concat<Item: ?Sized>(&self) -> <Self as Concat<Item>>::Output
where
Self: Concat<Item>,
{
Concat::concat(self)
}
/// Flattens a slice of `T` into a single value `Self::Output`, placing a
/// given separator between each.
///
/// # Examples
///
/// ```
/// assert_eq!(["hello", "world"].join(" "), "hello world");
/// assert_eq!([[1, 2], [3, 4]].join(&0), [1, 2, 0, 3, 4]);
/// assert_eq!([[1, 2], [3, 4]].join(&[0, 0][..]), [1, 2, 0, 0, 3, 4]);
/// ```
#[stable(feature = "rename_connect_to_join", since = "1.3.0")]
pub fn join<Separator>(&self, sep: Separator) -> <Self as Join<Separator>>::Output
where
Self: Join<Separator>,
{
Join::join(self, sep)
}
/// Flattens a slice of `T` into a single value `Self::Output`, placing a
/// given separator between each.
///
/// # Examples
///
/// ```
/// # #![allow(deprecated)]
/// assert_eq!(["hello", "world"].connect(" "), "hello world");
/// assert_eq!([[1, 2], [3, 4]].connect(&0), [1, 2, 0, 3, 4]);
/// ```
#[stable(feature = "rust1", since = "1.0.0")]
#[rustc_deprecated(since = "1.3.0", reason = "renamed to join")]
pub fn connect<Separator>(&self, sep: Separator) -> <Self as Join<Separator>>::Output
where
Self: Join<Separator>,
{
Join::join(self, sep)
}
}
#[lang = "slice_u8_alloc"]
#[cfg(not(test))]
impl [u8] {
/// Returns a vector containing a copy of this slice where each byte
/// is mapped to its ASCII upper case equivalent.
///
/// ASCII letters 'a' to 'z' are mapped to 'A' to 'Z',
/// but non-ASCII letters are unchanged.
///
/// To uppercase the value in-place, use [`make_ascii_uppercase`].
///
/// [`make_ascii_uppercase`]: u8::make_ascii_uppercase
#[stable(feature = "ascii_methods_on_intrinsics", since = "1.23.0")]
#[inline]
pub fn to_ascii_uppercase(&self) -> Vec<u8> {
let mut me = self.to_vec();
me.make_ascii_uppercase();
me
}
/// Returns a vector containing a copy of this slice where each byte
/// is mapped to its ASCII lower case equivalent.
///
/// ASCII letters 'A' to 'Z' are mapped to 'a' to 'z',
/// but non-ASCII letters are unchanged.
///
/// To lowercase the value in-place, use [`make_ascii_lowercase`].
///
/// [`make_ascii_lowercase`]: u8::make_ascii_lowercase
#[stable(feature = "ascii_methods_on_intrinsics", since = "1.23.0")]
#[inline]
pub fn to_ascii_lowercase(&self) -> Vec<u8> {
let mut me = self.to_vec();
me.make_ascii_lowercase();
me
}
}
////////////////////////////////////////////////////////////////////////////////
// Extension traits for slices over specific kinds of data
////////////////////////////////////////////////////////////////////////////////
/// Helper trait for [`[T]::concat`](../../std/primitive.slice.html#method.concat).
///
/// Note: the `Item` type parameter is not used in this trait,
/// but it allows impls to be more generic.
/// Without it, we get this error:
///
/// ```error
/// error[E0207]: the type parameter `T` is not constrained by the impl trait, self type, or predica
/// --> src/liballoc/slice.rs:608:6
/// |
/// 608 | impl<T: Clone, V: Borrow<[T]>> Concat for [V] {
/// | ^ unconstrained type parameter
/// ```
///
/// This is because there could exist `V` types with multiple `Borrow<[_]>` impls,
/// such that multiple `T` types would apply:
///
/// ```
/// # #[allow(dead_code)]
/// pub struct Foo(Vec<u32>, Vec<String>);
///
/// impl std::borrow::Borrow<[u32]> for Foo {
/// fn borrow(&self) -> &[u32] { &self.0 }
/// }
///
/// impl std::borrow::Borrow<[String]> for Foo {
/// fn borrow(&self) -> &[String] { &self.1 }
/// }
/// ```
#[unstable(feature = "slice_concat_trait", issue = "27747")]
pub trait Concat<Item: ?Sized> {
#[unstable(feature = "slice_concat_trait", issue = "27747")]
/// The resulting type after concatenation
type Output;
/// Implementation of [`[T]::concat`](../../std/primitive.slice.html#method.concat)
#[unstable(feature = "slice_concat_trait", issue = "27747")]
fn concat(slice: &Self) -> Self::Output;
}
/// Helper trait for [`[T]::join`](../../std/primitive.slice.html#method.join)
#[unstable(feature = "slice_concat_trait", issue = "27747")]
pub trait Join<Separator> {
#[unstable(feature = "slice_concat_trait", issue = "27747")]
/// The resulting type after concatenation
type Output;
/// Implementation of [`[T]::join`](../../std/primitive.slice.html#method.join)
#[unstable(feature = "slice_concat_trait", issue = "27747")]
fn join(slice: &Self, sep: Separator) -> Self::Output;
}
#[unstable(feature = "slice_concat_ext", issue = "27747")]
impl<T: Clone, V: Borrow<[T]>> Concat<T> for [V] {
type Output = Vec<T>;
fn concat(slice: &Self) -> Vec<T> {
let size = slice.iter().map(|slice| slice.borrow().len()).sum();
let mut result = Vec::with_capacity(size);
for v in slice {
result.extend_from_slice(v.borrow())
}
result
}
}
#[unstable(feature = "slice_concat_ext", issue = "27747")]
impl<T: Clone, V: Borrow<[T]>> Join<&T> for [V] {
type Output = Vec<T>;
fn join(slice: &Self, sep: &T) -> Vec<T> {
let mut iter = slice.iter();
let first = match iter.next() {
Some(first) => first,
None => return vec![],
};
let size = slice.iter().map(|v| v.borrow().len()).sum::<usize>() + slice.len() - 1;
let mut result = Vec::with_capacity(size);
result.extend_from_slice(first.borrow());
for v in iter {
result.push(sep.clone());
result.extend_from_slice(v.borrow())
}
result
}
}
#[unstable(feature = "slice_concat_ext", issue = "27747")]
impl<T: Clone, V: Borrow<[T]>> Join<&[T]> for [V] {
type Output = Vec<T>;
fn join(slice: &Self, sep: &[T]) -> Vec<T> {
let mut iter = slice.iter();
let first = match iter.next() {
Some(first) => first,
None => return vec![],
};
let size =
slice.iter().map(|v| v.borrow().len()).sum::<usize>() + sep.len() * (slice.len() - 1);
let mut result = Vec::with_capacity(size);
result.extend_from_slice(first.borrow());
for v in iter {
result.extend_from_slice(sep);
result.extend_from_slice(v.borrow())
}
result
}
}
////////////////////////////////////////////////////////////////////////////////
// Standard trait implementations for slices
////////////////////////////////////////////////////////////////////////////////
#[stable(feature = "rust1", since = "1.0.0")]
impl<T> Borrow<[T]> for Vec<T> {
fn borrow(&self) -> &[T] {
&self[..]
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<T> BorrowMut<[T]> for Vec<T> {
fn borrow_mut(&mut self) -> &mut [T] {
&mut self[..]
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<T: Clone> ToOwned for [T] {
type Owned = Vec<T>;
#[cfg(not(test))]
fn to_owned(&self) -> Vec<T> {
self.to_vec()
}
#[cfg(test)]
fn to_owned(&self) -> Vec<T> {
hack::to_vec(self, Global)
}
fn clone_into(&self, target: &mut Vec<T>) {
// drop anything in target that will not be overwritten
target.truncate(self.len());
// target.len <= self.len due to the truncate above, so the
// slices here are always in-bounds.
let (init, tail) = self.split_at(target.len());
// reuse the contained values' allocations/resources.
target.clone_from_slice(init);
target.extend_from_slice(tail);
}
}
////////////////////////////////////////////////////////////////////////////////
// Sorting
////////////////////////////////////////////////////////////////////////////////
/// Inserts `v[0]` into pre-sorted sequence `v[1..]` so that whole `v[..]` becomes sorted.
///
/// This is the integral subroutine of insertion sort.
fn insert_head<T, F>(v: &mut [T], is_less: &mut F)
where
F: FnMut(&T, &T) -> bool,
{
if v.len() >= 2 && is_less(&v[1], &v[0]) {
unsafe {
// There are three ways to implement insertion here:
//
// 1. Swap adjacent elements until the first one gets to its final destination.
// However, this way we copy data around more than is necessary. If elements are big
// structures (costly to copy), this method will be slow.
//
// 2. Iterate until the right place for the first element is found. Then shift the
// elements succeeding it to make room for it and finally place it into the
// remaining hole. This is a good method.
//
// 3. Copy the first element into a temporary variable. Iterate until the right place
// for it is found. As we go along, copy every traversed element into the slot
// preceding it. Finally, copy data from the temporary variable into the remaining
// hole. This method is very good. Benchmarks demonstrated slightly better
// performance than with the 2nd method.
//
// All methods were benchmarked, and the 3rd showed best results. So we chose that one.
let mut tmp = mem::ManuallyDrop::new(ptr::read(&v[0]));
// Intermediate state of the insertion process is always tracked by `hole`, which
// serves two purposes:
// 1. Protects integrity of `v` from panics in `is_less`.
// 2. Fills the remaining hole in `v` in the end.
//
// Panic safety:
//
// If `is_less` panics at any point during the process, `hole` will get dropped and
// fill the hole in `v` with `tmp`, thus ensuring that `v` still holds every object it
// initially held exactly once.
let mut hole = InsertionHole { src: &mut *tmp, dest: &mut v[1] };
ptr::copy_nonoverlapping(&v[1], &mut v[0], 1);
for i in 2..v.len() {
if !is_less(&v[i], &*tmp) {
break;
}
ptr::copy_nonoverlapping(&v[i], &mut v[i - 1], 1);
hole.dest = &mut v[i];
}
// `hole` gets dropped and thus copies `tmp` into the remaining hole in `v`.
}
}
// When dropped, copies from `src` into `dest`.
struct InsertionHole<T> {
src: *mut T,
dest: *mut T,
}
impl<T> Drop for InsertionHole<T> {
fn drop(&mut self) {
unsafe {
ptr::copy_nonoverlapping(self.src, self.dest, 1);
}
}
}
}
/// Merges non-decreasing runs `v[..mid]` and `v[mid..]` using `buf` as temporary storage, and
/// stores the result into `v[..]`.
///
/// # Safety
///
/// The two slices must be non-empty and `mid` must be in bounds. Buffer `buf` must be long enough
/// to hold a copy of the shorter slice. Also, `T` must not be a zero-sized type.
unsafe fn merge<T, F>(v: &mut [T], mid: usize, buf: *mut T, is_less: &mut F)
where
F: FnMut(&T, &T) -> bool,
{
let len = v.len();
let v = v.as_mut_ptr();
let (v_mid, v_end) = unsafe { (v.add(mid), v.add(len)) };
// The merge process first copies the shorter run into `buf`. Then it traces the newly copied
// run and the longer run forwards (or backwards), comparing their next unconsumed elements and
// copying the lesser (or greater) one into `v`.
//
// As soon as the shorter run is fully consumed, the process is done. If the longer run gets
// consumed first, then we must copy whatever is left of the shorter run into the remaining
// hole in `v`.
//
// Intermediate state of the process is always tracked by `hole`, which serves two purposes:
// 1. Protects integrity of `v` from panics in `is_less`.
// 2. Fills the remaining hole in `v` if the longer run gets consumed first.
//
// Panic safety:
//
// If `is_less` panics at any point during the process, `hole` will get dropped and fill the
// hole in `v` with the unconsumed range in `buf`, thus ensuring that `v` still holds every
// object it initially held exactly once.
let mut hole;
if mid <= len - mid {
// The left run is shorter.
unsafe {
ptr::copy_nonoverlapping(v, buf, mid);
hole = MergeHole { start: buf, end: buf.add(mid), dest: v };
}
// Initially, these pointers point to the beginnings of their arrays.
let left = &mut hole.start;
let mut right = v_mid;
let out = &mut hole.dest;
while *left < hole.end && right < v_end {
// Consume the lesser side.
// If equal, prefer the left run to maintain stability.
unsafe {
let to_copy = if is_less(&*right, &**left) {
get_and_increment(&mut right)
} else {
get_and_increment(left)
};
ptr::copy_nonoverlapping(to_copy, get_and_increment(out), 1);
}
}
} else {
// The right run is shorter.
unsafe {
ptr::copy_nonoverlapping(v_mid, buf, len - mid);
hole = MergeHole { start: buf, end: buf.add(len - mid), dest: v_mid };
}
// Initially, these pointers point past the ends of their arrays.
let left = &mut hole.dest;
let right = &mut hole.end;
let mut out = v_end;
while v < *left && buf < *right {
// Consume the greater side.
// If equal, prefer the right run to maintain stability.
unsafe {
let to_copy = if is_less(&*right.offset(-1), &*left.offset(-1)) {
decrement_and_get(left)
} else {
decrement_and_get(right)
};
ptr::copy_nonoverlapping(to_copy, decrement_and_get(&mut out), 1);
}
}
}
// Finally, `hole` gets dropped. If the shorter run was not fully consumed, whatever remains of
// it will now be copied into the hole in `v`.
unsafe fn get_and_increment<T>(ptr: &mut *mut T) -> *mut T {
let old = *ptr;
*ptr = unsafe { ptr.offset(1) };
old
}
unsafe fn decrement_and_get<T>(ptr: &mut *mut T) -> *mut T {
*ptr = unsafe { ptr.offset(-1) };
*ptr
}
// When dropped, copies the range `start..end` into `dest..`.
struct MergeHole<T> {
start: *mut T,
end: *mut T,
dest: *mut T,
}
impl<T> Drop for MergeHole<T> {
fn drop(&mut self) {
// `T` is not a zero-sized type, so it's okay to divide by its size.
let len = (self.end as usize - self.start as usize) / mem::size_of::<T>();
unsafe {
ptr::copy_nonoverlapping(self.start, self.dest, len);
}
}
}
}
/// This merge sort borrows some (but not all) ideas from TimSort, which is described in detail
/// [here](http://svn.python.org/projects/python/trunk/Objects/listsort.txt).
///
/// The algorithm identifies strictly descending and non-descending subsequences, which are called
/// natural runs. There is a stack of pending runs yet to be merged. Each newly found run is pushed
/// onto the stack, and then some pairs of adjacent runs are merged until these two invariants are
/// satisfied:
///
/// 1. for every `i` in `1..runs.len()`: `runs[i - 1].len > runs[i].len`
/// 2. for every `i` in `2..runs.len()`: `runs[i - 2].len > runs[i - 1].len + runs[i].len`
///
/// The invariants ensure that the total running time is *O*(*n* \* log(*n*)) worst-case.
fn merge_sort<T, F>(v: &mut [T], mut is_less: F)
where
F: FnMut(&T, &T) -> bool,
{
// Slices of up to this length get sorted using insertion sort.
const MAX_INSERTION: usize = 20;
// Very short runs are extended using insertion sort to span at least this many elements.
const MIN_RUN: usize = 10;
// Sorting has no meaningful behavior on zero-sized types.
if size_of::<T>() == 0 {
return;
}
let len = v.len();
// Short arrays get sorted in-place via insertion sort to avoid allocations.
if len <= MAX_INSERTION {
if len >= 2 {
for i in (0..len - 1).rev() {
insert_head(&mut v[i..], &mut is_less);
}
}
return;
}
// Allocate a buffer to use as scratch memory. We keep the length 0 so we can keep in it
// shallow copies of the contents of `v` without risking the dtors running on copies if
// `is_less` panics. When merging two sorted runs, this buffer holds a copy of the shorter run,
// which will always have length at most `len / 2`.
let mut buf = Vec::with_capacity(len / 2);
// In order to identify natural runs in `v`, we traverse it backwards. That might seem like a
// strange decision, but consider the fact that merges more often go in the opposite direction
// (forwards). According to benchmarks, merging forwards is slightly faster than merging
// backwards. To conclude, identifying runs by traversing backwards improves performance.
let mut runs = vec![];
let mut end = len;
while end > 0 {
// Find the next natural run, and reverse it if it's strictly descending.
let mut start = end - 1;
if start > 0 {
start -= 1;
unsafe {
if is_less(v.get_unchecked(start + 1), v.get_unchecked(start)) {
while start > 0 && is_less(v.get_unchecked(start), v.get_unchecked(start - 1)) {
start -= 1;
}
v[start..end].reverse();
} else {
while start > 0 && !is_less(v.get_unchecked(start), v.get_unchecked(start - 1))
{
start -= 1;
}
}
}
}
// Insert some more elements into the run if it's too short. Insertion sort is faster than
// merge sort on short sequences, so this significantly improves performance.
while start > 0 && end - start < MIN_RUN {
start -= 1;
insert_head(&mut v[start..end], &mut is_less);
}
// Push this run onto the stack.
runs.push(Run { start, len: end - start });
end = start;
// Merge some pairs of adjacent runs to satisfy the invariants.
while let Some(r) = collapse(&runs) {
let left = runs[r + 1];
let right = runs[r];
unsafe {
merge(
&mut v[left.start..right.start + right.len],
left.len,
buf.as_mut_ptr(),
&mut is_less,
);
}
runs[r] = Run { start: left.start, len: left.len + right.len };
runs.remove(r + 1);
}
}
// Finally, exactly one run must remain in the stack.
debug_assert!(runs.len() == 1 && runs[0].start == 0 && runs[0].len == len);
// Examines the stack of runs and identifies the next pair of runs to merge. More specifically,
// if `Some(r)` is returned, that means `runs[r]` and `runs[r + 1]` must be merged next. If the
// algorithm should continue building a new run instead, `None` is returned.
//
// TimSort is infamous for its buggy implementations, as described here:
// http://envisage-project.eu/timsort-specification-and-verification/
//
// The gist of the story is: we must enforce the invariants on the top four runs on the stack.
// Enforcing them on just top three is not sufficient to ensure that the invariants will still
// hold for *all* runs in the stack.
//
// This function correctly checks invariants for the top four runs. Additionally, if the top
// run starts at index 0, it will always demand a merge operation until the stack is fully
// collapsed, in order to complete the sort.
#[inline]
fn collapse(runs: &[Run]) -> Option<usize> {
let n = runs.len();
if n >= 2
&& (runs[n - 1].start == 0
|| runs[n - 2].len <= runs[n - 1].len
|| (n >= 3 && runs[n - 3].len <= runs[n - 2].len + runs[n - 1].len)
|| (n >= 4 && runs[n - 4].len <= runs[n - 3].len + runs[n - 2].len))
{
if n >= 3 && runs[n - 3].len < runs[n - 1].len { Some(n - 3) } else { Some(n - 2) }
} else {
None
}
}
#[derive(Clone, Copy)]
struct Run {
start: usize,
len: usize,
}
}
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