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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. //! //! [`Clone`]: ../../std/clone/trait.Clone.html //! [`Eq`]: ../../std/cmp/trait.Eq.html //! [`Ord`]: ../../std/cmp/trait.Ord.html //! [`Iter`]: struct.Iter.html //! [`Hash`]: ../../std/hash/trait.Hash.html //! [`.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 core::{u8, u16, u32}; use crate::borrow::ToOwned; use crate::boxed::Box; use crate::vec::Vec; #[stable(feature = "rust1", since = "1.0.0")] pub use core::slice::{Chunks, Windows}; #[stable(feature = "rust1", since = "1.0.0")] pub use core::slice::{Iter, IterMut}; #[stable(feature = "rust1", since = "1.0.0")] pub use core::slice::{SplitMut, ChunksMut, Split}; #[stable(feature = "rust1", since = "1.0.0")] pub use core::slice::{SplitN, RSplitN, SplitNMut, RSplitNMut}; #[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::{from_raw_parts, from_raw_parts_mut}; #[stable(feature = "from_ref", since = "1.28.0")] pub use core::slice::{from_ref, from_mut}; #[stable(feature = "slice_get_slice", since = "1.28.0")] pub use core::slice::SliceIndex; #[stable(feature = "chunks_exact", since = "1.31.0")] pub use core::slice::{ChunksExact, ChunksExactMut}; #[stable(feature = "rchunks", since = "1.31.0")] pub use core::slice::{RChunks, RChunksMut, RChunksExact, RChunksExactMut}; //////////////////////////////////////////////////////////////////////////////// // 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 crate::boxed::Box; use crate::vec::Vec; #[cfg(test)] use crate::string::ToString; pub fn into_vec<T>(b: Box<[T]>) -> Vec<T> { unsafe { let len = b.len(); let b = Box::into_raw(b); let xs = Vec::from_raw_parts(b as *mut T, len, len); xs } } #[inline] pub fn to_vec<T>(s: &[T]) -> Vec<T> where T: Clone { let mut vector = Vec::with_capacity(s.len()); vector.extend_from_slice(s); vector } } #[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(m 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 { // N.B., see the `hack` module in this file for more details. hack::to_vec(self) } /// 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(self: Box<Self>) -> Vec<T> { // 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: /// /// ``` /// #![feature(repeat_generic_slice)] /// /// fn main() { /// assert_eq!([1, 2].repeat(3), vec![1, 2, 1, 2, 1, 2]); /// } /// ``` /// /// A panic upon overflow: /// /// ```should_panic /// #![feature(repeat_generic_slice)] /// fn main() { /// // this will panic at runtime /// b"0123456789abcdef".repeat(usize::max_value()); /// } /// ``` #[unstable(feature = "repeat_generic_slice", reason = "it's on str, why not on slice?", issue = "48784")] 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 mut buf = Vec::with_capacity(self.len().checked_mul(n).expect("capacity overflow")); // `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 = self.len() * n - 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`). let buf_cap = buf.capacity(); buf.set_len(buf_cap); } } buf } } #[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`]: #method.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`]: #method.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 //////////////////////////////////////////////////////////////////////////////// #[unstable(feature = "slice_concat_ext", reason = "trait should not have to exist", issue = "27747")] /// An extension trait for concatenating slices /// /// While this trait is unstable, the methods are stable. `SliceConcatExt` is /// included in the [standard library prelude], so you can use [`join()`] and /// [`concat()`] as if they existed on `[T]` itself. /// /// [standard library prelude]: ../../std/prelude/index.html /// [`join()`]: #tymethod.join /// [`concat()`]: #tymethod.concat pub trait SliceConcatExt<T: ?Sized> { #[unstable(feature = "slice_concat_ext", reason = "trait should not have to exist", issue = "27747")] /// The resulting type after concatenation type Output; /// 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")] fn concat(&self) -> Self::Output; /// 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]); /// ``` #[stable(feature = "rename_connect_to_join", since = "1.3.0")] fn join(&self, sep: &T) -> Self::Output; /// 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")] fn connect(&self, sep: &T) -> Self::Output; } #[unstable(feature = "slice_concat_ext", reason = "trait should not have to exist", issue = "27747")] impl<T: Clone, V: Borrow<[T]>> SliceConcatExt<T> for [V] { type Output = Vec<T>; fn concat(&self) -> Vec<T> { let size = self.iter().map(|slice| slice.borrow().len()).sum(); let mut result = Vec::with_capacity(size); for v in self { result.extend_from_slice(v.borrow()) } result } fn join(&self, sep: &T) -> Vec<T> { let mut iter = self.iter(); let first = match iter.next() { Some(first) => first, None => return vec![], }; let size = self.iter().map(|slice| slice.borrow().len()).sum::<usize>() + self.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 } fn connect(&self, sep: &T) -> Vec<T> { self.join(sep) } } //////////////////////////////////////////////////////////////////////////////// // 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) } fn clone_into(&self, target: &mut Vec<T>) { // drop anything in target that will not be overwritten target.truncate(self.len()); let len = target.len(); // reuse the contained values' allocations/resources. target.clone_from_slice(&self[..len]); // target.len <= self.len due to the truncate above, so the // slice here is always in-bounds. target.extend_from_slice(&self[len..]); } } //////////////////////////////////////////////////////////////////////////////// // 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.add(mid); let v_end = 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. 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. 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. 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. 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 = ptr.offset(1); old } unsafe fn decrement_and_get<T>(ptr: &mut *mut T) -> *mut T { *ptr = 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, } }