1 //! A dynamically-sized view into a contiguous sequence, `[T]`.
3 //! *[See also the slice primitive type](../../std/primitive.slice.html).*
5 //! Slices are a view into a block of memory represented as a pointer and a
10 //! let vec = vec![1, 2, 3];
11 //! let int_slice = &vec[..];
12 //! // coercing an array to a slice
13 //! let str_slice: &[&str] = &["one", "two", "three"];
16 //! Slices are either mutable or shared. The shared slice type is `&[T]`,
17 //! while the mutable slice type is `&mut [T]`, where `T` represents the element
18 //! type. For example, you can mutate the block of memory that a mutable slice
22 //! let x = &mut [1, 2, 3];
24 //! assert_eq!(x, &[1, 7, 3]);
27 //! Here are some of the things this module contains:
31 //! There are several structs that are useful for slices, such as [`Iter`], which
32 //! represents iteration over a slice.
34 //! ## Trait Implementations
36 //! There are several implementations of common traits for slices. Some examples
40 //! * [`Eq`], [`Ord`] - for slices whose element type are [`Eq`] or [`Ord`].
41 //! * [`Hash`] - for slices whose element type is [`Hash`].
45 //! The slices implement `IntoIterator`. The iterator yields references to the
49 //! let numbers = &[0, 1, 2];
50 //! for n in numbers {
51 //! println!("{} is a number!", n);
55 //! The mutable slice yields mutable references to the elements:
58 //! let mut scores = [7, 8, 9];
59 //! for score in &mut scores[..] {
64 //! This iterator yields mutable references to the slice's elements, so while
65 //! the element type of the slice is `i32`, the element type of the iterator is
68 //! * [`.iter`] and [`.iter_mut`] are the explicit methods to return the default
70 //! * Further methods that return iterators are [`.split`], [`.splitn`],
71 //! [`.chunks`], [`.windows`] and more.
73 //! [`Clone`]: ../../std/clone/trait.Clone.html
74 //! [`Eq`]: ../../std/cmp/trait.Eq.html
75 //! [`Ord`]: ../../std/cmp/trait.Ord.html
76 //! [`Iter`]: struct.Iter.html
77 //! [`Hash`]: ../../std/hash/trait.Hash.html
78 //! [`.iter`]: ../../std/primitive.slice.html#method.iter
79 //! [`.iter_mut`]: ../../std/primitive.slice.html#method.iter_mut
80 //! [`.split`]: ../../std/primitive.slice.html#method.split
81 //! [`.splitn`]: ../../std/primitive.slice.html#method.splitn
82 //! [`.chunks`]: ../../std/primitive.slice.html#method.chunks
83 //! [`.windows`]: ../../std/primitive.slice.html#method.windows
84 #![stable(feature = "rust1", since = "1.0.0")]
85 // Many of the usings in this module are only used in the test configuration.
86 // It's cleaner to just turn off the unused_imports warning than to fix them.
87 #![cfg_attr(test, allow(unused_imports, dead_code))]
89 use core::borrow::{Borrow, BorrowMut};
90 use core::cmp::Ordering::{self, Less};
91 use core::mem::{self, size_of};
93 use core::{u16, u32, u8};
95 use crate::borrow::ToOwned;
96 use crate::boxed::Box;
99 #[stable(feature = "slice_get_slice", since = "1.28.0")]
100 pub use core::slice::SliceIndex;
101 #[stable(feature = "from_ref", since = "1.28.0")]
102 pub use core::slice::{from_mut, from_ref};
103 #[stable(feature = "rust1", since = "1.0.0")]
104 pub use core::slice::{from_raw_parts, from_raw_parts_mut};
105 #[stable(feature = "rust1", since = "1.0.0")]
106 pub use core::slice::{Chunks, Windows};
107 #[stable(feature = "chunks_exact", since = "1.31.0")]
108 pub use core::slice::{ChunksExact, ChunksExactMut};
109 #[stable(feature = "rust1", since = "1.0.0")]
110 pub use core::slice::{ChunksMut, Split, SplitMut};
111 #[stable(feature = "rust1", since = "1.0.0")]
112 pub use core::slice::{Iter, IterMut};
113 #[stable(feature = "rchunks", since = "1.31.0")]
114 pub use core::slice::{RChunks, RChunksExact, RChunksExactMut, RChunksMut};
115 #[stable(feature = "slice_rsplit", since = "1.27.0")]
116 pub use core::slice::{RSplit, RSplitMut};
117 #[stable(feature = "rust1", since = "1.0.0")]
118 pub use core::slice::{RSplitN, RSplitNMut, SplitN, SplitNMut};
120 ////////////////////////////////////////////////////////////////////////////////
121 // Basic slice extension methods
122 ////////////////////////////////////////////////////////////////////////////////
124 // HACK(japaric) needed for the implementation of `vec!` macro during testing
125 // N.B., see the `hack` module in this file for more details.
127 pub use hack::into_vec;
129 // HACK(japaric) needed for the implementation of `Vec::clone` during testing
130 // N.B., see the `hack` module in this file for more details.
132 pub use hack::to_vec;
134 // HACK(japaric): With cfg(test) `impl [T]` is not available, these three
135 // functions are actually methods that are in `impl [T]` but not in
136 // `core::slice::SliceExt` - we need to supply these functions for the
137 // `test_permutations` test
139 use crate::boxed::Box;
141 use crate::string::ToString;
144 pub fn into_vec<T>(b: Box<[T]>) -> Vec<T> {
147 let b = Box::into_raw(b);
148 let xs = Vec::from_raw_parts(b as *mut T, len, len);
154 pub fn to_vec<T>(s: &[T]) -> Vec<T>
158 let mut vector = Vec::with_capacity(s.len());
159 vector.extend_from_slice(s);
164 #[lang = "slice_alloc"]
169 /// This sort is stable (i.e., does not reorder equal elements) and `O(n log n)` worst-case.
171 /// When applicable, unstable sorting is preferred because it is generally faster than stable
172 /// sorting and it doesn't allocate auxiliary memory.
173 /// See [`sort_unstable`](#method.sort_unstable).
175 /// # Current implementation
177 /// The current algorithm is an adaptive, iterative merge sort inspired by
178 /// [timsort](https://en.wikipedia.org/wiki/Timsort).
179 /// It is designed to be very fast in cases where the slice is nearly sorted, or consists of
180 /// two or more sorted sequences concatenated one after another.
182 /// Also, it allocates temporary storage half the size of `self`, but for short slices a
183 /// non-allocating insertion sort is used instead.
188 /// let mut v = [-5, 4, 1, -3, 2];
191 /// assert!(v == [-5, -3, 1, 2, 4]);
193 #[stable(feature = "rust1", since = "1.0.0")]
195 pub fn sort(&mut self)
199 merge_sort(self, |a, b| a.lt(b));
202 /// Sorts the slice with a comparator function.
204 /// This sort is stable (i.e., does not reorder equal elements) and `O(n log n)` worst-case.
206 /// The comparator function must define a total ordering for the elements in the slice. If
207 /// the ordering is not total, the order of the elements is unspecified. An order is a
208 /// total order if it is (for all `a`, `b` and `c`):
210 /// * total and antisymmetric: exactly one of `a < b`, `a == b` or `a > b` is true, and
211 /// * transitive, `a < b` and `b < c` implies `a < c`. The same must hold for both `==` and `>`.
213 /// For example, while [`f64`] doesn't implement [`Ord`] because `NaN != NaN`, we can use
214 /// `partial_cmp` as our sort function when we know the slice doesn't contain a `NaN`.
217 /// let mut floats = [5f64, 4.0, 1.0, 3.0, 2.0];
218 /// floats.sort_by(|a, b| a.partial_cmp(b).unwrap());
219 /// assert_eq!(floats, [1.0, 2.0, 3.0, 4.0, 5.0]);
222 /// When applicable, unstable sorting is preferred because it is generally faster than stable
223 /// sorting and it doesn't allocate auxiliary memory.
224 /// See [`sort_unstable_by`](#method.sort_unstable_by).
226 /// # Current implementation
228 /// The current algorithm is an adaptive, iterative merge sort inspired by
229 /// [timsort](https://en.wikipedia.org/wiki/Timsort).
230 /// It is designed to be very fast in cases where the slice is nearly sorted, or consists of
231 /// two or more sorted sequences concatenated one after another.
233 /// Also, it allocates temporary storage half the size of `self`, but for short slices a
234 /// non-allocating insertion sort is used instead.
239 /// let mut v = [5, 4, 1, 3, 2];
240 /// v.sort_by(|a, b| a.cmp(b));
241 /// assert!(v == [1, 2, 3, 4, 5]);
243 /// // reverse sorting
244 /// v.sort_by(|a, b| b.cmp(a));
245 /// assert!(v == [5, 4, 3, 2, 1]);
247 #[stable(feature = "rust1", since = "1.0.0")]
249 pub fn sort_by<F>(&mut self, mut compare: F)
251 F: FnMut(&T, &T) -> Ordering,
253 merge_sort(self, |a, b| compare(a, b) == Less);
256 /// Sorts the slice with a key extraction function.
258 /// This sort is stable (i.e., does not reorder equal elements) and `O(m n log(m n))`
259 /// worst-case, where the key function is `O(m)`.
261 /// For expensive key functions (e.g. functions that are not simple property accesses or
262 /// basic operations), [`sort_by_cached_key`](#method.sort_by_cached_key) is likely to be
263 /// significantly faster, as it does not recompute element keys.
265 /// When applicable, unstable sorting is preferred because it is generally faster than stable
266 /// sorting and it doesn't allocate auxiliary memory.
267 /// See [`sort_unstable_by_key`](#method.sort_unstable_by_key).
269 /// # Current implementation
271 /// The current algorithm is an adaptive, iterative merge sort inspired by
272 /// [timsort](https://en.wikipedia.org/wiki/Timsort).
273 /// It is designed to be very fast in cases where the slice is nearly sorted, or consists of
274 /// two or more sorted sequences concatenated one after another.
276 /// Also, it allocates temporary storage half the size of `self`, but for short slices a
277 /// non-allocating insertion sort is used instead.
282 /// let mut v = [-5i32, 4, 1, -3, 2];
284 /// v.sort_by_key(|k| k.abs());
285 /// assert!(v == [1, 2, -3, 4, -5]);
287 #[stable(feature = "slice_sort_by_key", since = "1.7.0")]
289 pub fn sort_by_key<K, F>(&mut self, mut f: F)
294 merge_sort(self, |a, b| f(a).lt(&f(b)));
297 /// Sorts the slice with a key extraction function.
299 /// During sorting, the key function is called only once per element.
301 /// This sort is stable (i.e., does not reorder equal elements) and `O(m n + n log n)`
302 /// worst-case, where the key function is `O(m)`.
304 /// For simple key functions (e.g., functions that are property accesses or
305 /// basic operations), [`sort_by_key`](#method.sort_by_key) is likely to be
308 /// # Current implementation
310 /// The current algorithm is based on [pattern-defeating quicksort][pdqsort] by Orson Peters,
311 /// which combines the fast average case of randomized quicksort with the fast worst case of
312 /// heapsort, while achieving linear time on slices with certain patterns. It uses some
313 /// randomization to avoid degenerate cases, but with a fixed seed to always provide
314 /// deterministic behavior.
316 /// In the worst case, the algorithm allocates temporary storage in a `Vec<(K, usize)>` the
317 /// length of the slice.
322 /// let mut v = [-5i32, 4, 32, -3, 2];
324 /// v.sort_by_cached_key(|k| k.to_string());
325 /// assert!(v == [-3, -5, 2, 32, 4]);
328 /// [pdqsort]: https://github.com/orlp/pdqsort
329 #[stable(feature = "slice_sort_by_cached_key", since = "1.34.0")]
331 pub fn sort_by_cached_key<K, F>(&mut self, f: F)
336 // Helper macro for indexing our vector by the smallest possible type, to reduce allocation.
337 macro_rules! sort_by_key {
338 ($t:ty, $slice:ident, $f:ident) => {{
339 let mut indices: Vec<_> =
340 $slice.iter().map($f).enumerate().map(|(i, k)| (k, i as $t)).collect();
341 // The elements of `indices` are unique, as they are indexed, so any sort will be
342 // stable with respect to the original slice. We use `sort_unstable` here because
343 // it requires less memory allocation.
344 indices.sort_unstable();
345 for i in 0..$slice.len() {
346 let mut index = indices[i].1;
347 while (index as usize) < i {
348 index = indices[index as usize].1;
350 indices[i].1 = index;
351 $slice.swap(i, index as usize);
356 let sz_u8 = mem::size_of::<(K, u8)>();
357 let sz_u16 = mem::size_of::<(K, u16)>();
358 let sz_u32 = mem::size_of::<(K, u32)>();
359 let sz_usize = mem::size_of::<(K, usize)>();
361 let len = self.len();
365 if sz_u8 < sz_u16 && len <= (u8::MAX as usize) {
366 return sort_by_key!(u8, self, f);
368 if sz_u16 < sz_u32 && len <= (u16::MAX as usize) {
369 return sort_by_key!(u16, self, f);
371 if sz_u32 < sz_usize && len <= (u32::MAX as usize) {
372 return sort_by_key!(u32, self, f);
374 sort_by_key!(usize, self, f)
377 /// Copies `self` into a new `Vec`.
382 /// let s = [10, 40, 30];
383 /// let x = s.to_vec();
384 /// // Here, `s` and `x` can be modified independently.
386 #[rustc_conversion_suggestion]
387 #[stable(feature = "rust1", since = "1.0.0")]
389 pub fn to_vec(&self) -> Vec<T>
393 // N.B., see the `hack` module in this file for more details.
397 /// Converts `self` into a vector without clones or allocation.
399 /// The resulting vector can be converted back into a box via
400 /// `Vec<T>`'s `into_boxed_slice` method.
405 /// let s: Box<[i32]> = Box::new([10, 40, 30]);
406 /// let x = s.into_vec();
407 /// // `s` cannot be used anymore because it has been converted into `x`.
409 /// assert_eq!(x, vec![10, 40, 30]);
411 #[stable(feature = "rust1", since = "1.0.0")]
413 pub fn into_vec(self: Box<Self>) -> Vec<T> {
414 // N.B., see the `hack` module in this file for more details.
418 /// Creates a vector by repeating a slice `n` times.
422 /// This function will panic if the capacity would overflow.
429 /// assert_eq!([1, 2].repeat(3), vec![1, 2, 1, 2, 1, 2]);
432 /// A panic upon overflow:
435 /// // this will panic at runtime
436 /// b"0123456789abcdef".repeat(usize::max_value());
438 #[stable(feature = "repeat_generic_slice", since = "1.40.0")]
439 pub fn repeat(&self, n: usize) -> Vec<T>
447 // If `n` is larger than zero, it can be split as
448 // `n = 2^expn + rem (2^expn > rem, expn >= 0, rem >= 0)`.
449 // `2^expn` is the number represented by the leftmost '1' bit of `n`,
450 // and `rem` is the remaining part of `n`.
452 // Using `Vec` to access `set_len()`.
453 let capacity = self.len().checked_mul(n).expect("capacity overflow");
454 let mut buf = Vec::with_capacity(capacity);
456 // `2^expn` repetition is done by doubling `buf` `expn`-times.
460 // If `m > 0`, there are remaining bits up to the leftmost '1'.
462 // `buf.extend(buf)`:
464 ptr::copy_nonoverlapping(
466 (buf.as_mut_ptr() as *mut T).add(buf.len()),
469 // `buf` has capacity of `self.len() * n`.
470 let buf_len = buf.len();
471 buf.set_len(buf_len * 2);
478 // `rem` (`= n - 2^expn`) repetition is done by copying
479 // first `rem` repetitions from `buf` itself.
480 let rem_len = capacity - buf.len(); // `self.len() * rem`
482 // `buf.extend(buf[0 .. rem_len])`:
484 // This is non-overlapping since `2^expn > rem`.
485 ptr::copy_nonoverlapping(
487 (buf.as_mut_ptr() as *mut T).add(buf.len()),
490 // `buf.len() + rem_len` equals to `buf.capacity()` (`= self.len() * n`).
491 buf.set_len(capacity);
497 /// Flattens a slice of `T` into a single value `Self::Output`.
502 /// assert_eq!(["hello", "world"].concat(), "helloworld");
503 /// assert_eq!([[1, 2], [3, 4]].concat(), [1, 2, 3, 4]);
505 #[stable(feature = "rust1", since = "1.0.0")]
506 pub fn concat<Item: ?Sized>(&self) -> <Self as Concat<Item>>::Output
513 /// Flattens a slice of `T` into a single value `Self::Output`, placing a
514 /// given separator between each.
519 /// assert_eq!(["hello", "world"].join(" "), "hello world");
520 /// assert_eq!([[1, 2], [3, 4]].join(&0), [1, 2, 0, 3, 4]);
521 /// assert_eq!([[1, 2], [3, 4]].join(&[0, 0][..]), [1, 2, 0, 0, 3, 4]);
523 #[stable(feature = "rename_connect_to_join", since = "1.3.0")]
524 pub fn join<Separator>(&self, sep: Separator) -> <Self as Join<Separator>>::Output
526 Self: Join<Separator>,
528 Join::join(self, sep)
531 /// Flattens a slice of `T` into a single value `Self::Output`, placing a
532 /// given separator between each.
537 /// # #![allow(deprecated)]
538 /// assert_eq!(["hello", "world"].connect(" "), "hello world");
539 /// assert_eq!([[1, 2], [3, 4]].connect(&0), [1, 2, 0, 3, 4]);
541 #[stable(feature = "rust1", since = "1.0.0")]
542 #[rustc_deprecated(since = "1.3.0", reason = "renamed to join")]
543 pub fn connect<Separator>(&self, sep: Separator) -> <Self as Join<Separator>>::Output
545 Self: Join<Separator>,
547 Join::join(self, sep)
551 #[lang = "slice_u8_alloc"]
554 /// Returns a vector containing a copy of this slice where each byte
555 /// is mapped to its ASCII upper case equivalent.
557 /// ASCII letters 'a' to 'z' are mapped to 'A' to 'Z',
558 /// but non-ASCII letters are unchanged.
560 /// To uppercase the value in-place, use [`make_ascii_uppercase`].
562 /// [`make_ascii_uppercase`]: #method.make_ascii_uppercase
563 #[stable(feature = "ascii_methods_on_intrinsics", since = "1.23.0")]
565 pub fn to_ascii_uppercase(&self) -> Vec<u8> {
566 let mut me = self.to_vec();
567 me.make_ascii_uppercase();
571 /// Returns a vector containing a copy of this slice where each byte
572 /// is mapped to its ASCII lower case equivalent.
574 /// ASCII letters 'A' to 'Z' are mapped to 'a' to 'z',
575 /// but non-ASCII letters are unchanged.
577 /// To lowercase the value in-place, use [`make_ascii_lowercase`].
579 /// [`make_ascii_lowercase`]: #method.make_ascii_lowercase
580 #[stable(feature = "ascii_methods_on_intrinsics", since = "1.23.0")]
582 pub fn to_ascii_lowercase(&self) -> Vec<u8> {
583 let mut me = self.to_vec();
584 me.make_ascii_lowercase();
589 ////////////////////////////////////////////////////////////////////////////////
590 // Extension traits for slices over specific kinds of data
591 ////////////////////////////////////////////////////////////////////////////////
593 /// Helper trait for [`[T]::concat`](../../std/primitive.slice.html#method.concat).
595 /// Note: the `Item` type parameter is not used in this trait,
596 /// but it allows impls to be more generic.
597 /// Without it, we get this error:
600 /// error[E0207]: the type parameter `T` is not constrained by the impl trait, self type, or predica
601 /// --> src/liballoc/slice.rs:608:6
603 /// 608 | impl<T: Clone, V: Borrow<[T]>> Concat for [V] {
604 /// | ^ unconstrained type parameter
607 /// This is because there could exist `V` types with multiple `Borrow<[_]>` impls,
608 /// such that multiple `T` types would apply:
611 /// # #[allow(dead_code)]
612 /// pub struct Foo(Vec<u32>, Vec<String>);
614 /// impl std::borrow::Borrow<[u32]> for Foo {
615 /// fn borrow(&self) -> &[u32] { &self.0 }
618 /// impl std::borrow::Borrow<[String]> for Foo {
619 /// fn borrow(&self) -> &[String] { &self.1 }
622 #[unstable(feature = "slice_concat_trait", issue = "27747")]
623 pub trait Concat<Item: ?Sized> {
624 #[unstable(feature = "slice_concat_trait", issue = "27747")]
625 /// The resulting type after concatenation
628 /// Implementation of [`[T]::concat`](../../std/primitive.slice.html#method.concat)
629 #[unstable(feature = "slice_concat_trait", issue = "27747")]
630 fn concat(slice: &Self) -> Self::Output;
633 /// Helper trait for [`[T]::join`](../../std/primitive.slice.html#method.join)
634 #[unstable(feature = "slice_concat_trait", issue = "27747")]
635 pub trait Join<Separator> {
636 #[unstable(feature = "slice_concat_trait", issue = "27747")]
637 /// The resulting type after concatenation
640 /// Implementation of [`[T]::join`](../../std/primitive.slice.html#method.join)
641 #[unstable(feature = "slice_concat_trait", issue = "27747")]
642 fn join(slice: &Self, sep: Separator) -> Self::Output;
645 #[unstable(feature = "slice_concat_ext", issue = "27747")]
646 impl<T: Clone, V: Borrow<[T]>> Concat<T> for [V] {
647 type Output = Vec<T>;
649 fn concat(slice: &Self) -> Vec<T> {
650 let size = slice.iter().map(|slice| slice.borrow().len()).sum();
651 let mut result = Vec::with_capacity(size);
653 result.extend_from_slice(v.borrow())
659 #[unstable(feature = "slice_concat_ext", issue = "27747")]
660 impl<T: Clone, V: Borrow<[T]>> Join<&T> for [V] {
661 type Output = Vec<T>;
663 fn join(slice: &Self, sep: &T) -> Vec<T> {
664 let mut iter = slice.iter();
665 let first = match iter.next() {
666 Some(first) => first,
667 None => return vec![],
669 let size = slice.iter().map(|v| v.borrow().len()).sum::<usize>() + slice.len() - 1;
670 let mut result = Vec::with_capacity(size);
671 result.extend_from_slice(first.borrow());
674 result.push(sep.clone());
675 result.extend_from_slice(v.borrow())
681 #[unstable(feature = "slice_concat_ext", issue = "27747")]
682 impl<T: Clone, V: Borrow<[T]>> Join<&[T]> for [V] {
683 type Output = Vec<T>;
685 fn join(slice: &Self, sep: &[T]) -> Vec<T> {
686 let mut iter = slice.iter();
687 let first = match iter.next() {
688 Some(first) => first,
689 None => return vec![],
692 slice.iter().map(|v| v.borrow().len()).sum::<usize>() + sep.len() * (slice.len() - 1);
693 let mut result = Vec::with_capacity(size);
694 result.extend_from_slice(first.borrow());
697 result.extend_from_slice(sep);
698 result.extend_from_slice(v.borrow())
704 ////////////////////////////////////////////////////////////////////////////////
705 // Standard trait implementations for slices
706 ////////////////////////////////////////////////////////////////////////////////
708 #[stable(feature = "rust1", since = "1.0.0")]
709 impl<T> Borrow<[T]> for Vec<T> {
710 fn borrow(&self) -> &[T] {
715 #[stable(feature = "rust1", since = "1.0.0")]
716 impl<T> BorrowMut<[T]> for Vec<T> {
717 fn borrow_mut(&mut self) -> &mut [T] {
722 #[stable(feature = "rust1", since = "1.0.0")]
723 impl<T: Clone> ToOwned for [T] {
726 fn to_owned(&self) -> Vec<T> {
731 fn to_owned(&self) -> Vec<T> {
735 fn clone_into(&self, target: &mut Vec<T>) {
736 // drop anything in target that will not be overwritten
737 target.truncate(self.len());
738 let len = target.len();
740 // reuse the contained values' allocations/resources.
741 target.clone_from_slice(&self[..len]);
743 // target.len <= self.len due to the truncate above, so the
744 // slice here is always in-bounds.
745 target.extend_from_slice(&self[len..]);
749 ////////////////////////////////////////////////////////////////////////////////
751 ////////////////////////////////////////////////////////////////////////////////
753 /// Inserts `v[0]` into pre-sorted sequence `v[1..]` so that whole `v[..]` becomes sorted.
755 /// This is the integral subroutine of insertion sort.
756 fn insert_head<T, F>(v: &mut [T], is_less: &mut F)
758 F: FnMut(&T, &T) -> bool,
760 if v.len() >= 2 && is_less(&v[1], &v[0]) {
762 // There are three ways to implement insertion here:
764 // 1. Swap adjacent elements until the first one gets to its final destination.
765 // However, this way we copy data around more than is necessary. If elements are big
766 // structures (costly to copy), this method will be slow.
768 // 2. Iterate until the right place for the first element is found. Then shift the
769 // elements succeeding it to make room for it and finally place it into the
770 // remaining hole. This is a good method.
772 // 3. Copy the first element into a temporary variable. Iterate until the right place
773 // for it is found. As we go along, copy every traversed element into the slot
774 // preceding it. Finally, copy data from the temporary variable into the remaining
775 // hole. This method is very good. Benchmarks demonstrated slightly better
776 // performance than with the 2nd method.
778 // All methods were benchmarked, and the 3rd showed best results. So we chose that one.
779 let mut tmp = mem::ManuallyDrop::new(ptr::read(&v[0]));
781 // Intermediate state of the insertion process is always tracked by `hole`, which
782 // serves two purposes:
783 // 1. Protects integrity of `v` from panics in `is_less`.
784 // 2. Fills the remaining hole in `v` in the end.
788 // If `is_less` panics at any point during the process, `hole` will get dropped and
789 // fill the hole in `v` with `tmp`, thus ensuring that `v` still holds every object it
790 // initially held exactly once.
791 let mut hole = InsertionHole { src: &mut *tmp, dest: &mut v[1] };
792 ptr::copy_nonoverlapping(&v[1], &mut v[0], 1);
794 for i in 2..v.len() {
795 if !is_less(&v[i], &*tmp) {
798 ptr::copy_nonoverlapping(&v[i], &mut v[i - 1], 1);
799 hole.dest = &mut v[i];
801 // `hole` gets dropped and thus copies `tmp` into the remaining hole in `v`.
805 // When dropped, copies from `src` into `dest`.
806 struct InsertionHole<T> {
811 impl<T> Drop for InsertionHole<T> {
814 ptr::copy_nonoverlapping(self.src, self.dest, 1);
820 /// Merges non-decreasing runs `v[..mid]` and `v[mid..]` using `buf` as temporary storage, and
821 /// stores the result into `v[..]`.
825 /// The two slices must be non-empty and `mid` must be in bounds. Buffer `buf` must be long enough
826 /// to hold a copy of the shorter slice. Also, `T` must not be a zero-sized type.
827 unsafe fn merge<T, F>(v: &mut [T], mid: usize, buf: *mut T, is_less: &mut F)
829 F: FnMut(&T, &T) -> bool,
832 let v = v.as_mut_ptr();
833 let v_mid = v.add(mid);
834 let v_end = v.add(len);
836 // The merge process first copies the shorter run into `buf`. Then it traces the newly copied
837 // run and the longer run forwards (or backwards), comparing their next unconsumed elements and
838 // copying the lesser (or greater) one into `v`.
840 // As soon as the shorter run is fully consumed, the process is done. If the longer run gets
841 // consumed first, then we must copy whatever is left of the shorter run into the remaining
844 // Intermediate state of the process is always tracked by `hole`, which serves two purposes:
845 // 1. Protects integrity of `v` from panics in `is_less`.
846 // 2. Fills the remaining hole in `v` if the longer run gets consumed first.
850 // If `is_less` panics at any point during the process, `hole` will get dropped and fill the
851 // hole in `v` with the unconsumed range in `buf`, thus ensuring that `v` still holds every
852 // object it initially held exactly once.
855 if mid <= len - mid {
856 // The left run is shorter.
857 ptr::copy_nonoverlapping(v, buf, mid);
858 hole = MergeHole { start: buf, end: buf.add(mid), dest: v };
860 // Initially, these pointers point to the beginnings of their arrays.
861 let left = &mut hole.start;
862 let mut right = v_mid;
863 let out = &mut hole.dest;
865 while *left < hole.end && right < v_end {
866 // Consume the lesser side.
867 // If equal, prefer the left run to maintain stability.
868 let to_copy = if is_less(&*right, &**left) {
869 get_and_increment(&mut right)
871 get_and_increment(left)
873 ptr::copy_nonoverlapping(to_copy, get_and_increment(out), 1);
876 // The right run is shorter.
877 ptr::copy_nonoverlapping(v_mid, buf, len - mid);
878 hole = MergeHole { start: buf, end: buf.add(len - mid), dest: v_mid };
880 // Initially, these pointers point past the ends of their arrays.
881 let left = &mut hole.dest;
882 let right = &mut hole.end;
885 while v < *left && buf < *right {
886 // Consume the greater side.
887 // If equal, prefer the right run to maintain stability.
888 let to_copy = if is_less(&*right.offset(-1), &*left.offset(-1)) {
889 decrement_and_get(left)
891 decrement_and_get(right)
893 ptr::copy_nonoverlapping(to_copy, decrement_and_get(&mut out), 1);
896 // Finally, `hole` gets dropped. If the shorter run was not fully consumed, whatever remains of
897 // it will now be copied into the hole in `v`.
899 unsafe fn get_and_increment<T>(ptr: &mut *mut T) -> *mut T {
901 *ptr = ptr.offset(1);
905 unsafe fn decrement_and_get<T>(ptr: &mut *mut T) -> *mut T {
906 *ptr = ptr.offset(-1);
910 // When dropped, copies the range `start..end` into `dest..`.
911 struct MergeHole<T> {
917 impl<T> Drop for MergeHole<T> {
919 // `T` is not a zero-sized type, so it's okay to divide by its size.
920 let len = (self.end as usize - self.start as usize) / mem::size_of::<T>();
922 ptr::copy_nonoverlapping(self.start, self.dest, len);
928 /// This merge sort borrows some (but not all) ideas from TimSort, which is described in detail
929 /// [here](http://svn.python.org/projects/python/trunk/Objects/listsort.txt).
931 /// The algorithm identifies strictly descending and non-descending subsequences, which are called
932 /// natural runs. There is a stack of pending runs yet to be merged. Each newly found run is pushed
933 /// onto the stack, and then some pairs of adjacent runs are merged until these two invariants are
936 /// 1. for every `i` in `1..runs.len()`: `runs[i - 1].len > runs[i].len`
937 /// 2. for every `i` in `2..runs.len()`: `runs[i - 2].len > runs[i - 1].len + runs[i].len`
939 /// The invariants ensure that the total running time is `O(n log n)` worst-case.
940 fn merge_sort<T, F>(v: &mut [T], mut is_less: F)
942 F: FnMut(&T, &T) -> bool,
944 // Slices of up to this length get sorted using insertion sort.
945 const MAX_INSERTION: usize = 20;
946 // Very short runs are extended using insertion sort to span at least this many elements.
947 const MIN_RUN: usize = 10;
949 // Sorting has no meaningful behavior on zero-sized types.
950 if size_of::<T>() == 0 {
956 // Short arrays get sorted in-place via insertion sort to avoid allocations.
957 if len <= MAX_INSERTION {
959 for i in (0..len - 1).rev() {
960 insert_head(&mut v[i..], &mut is_less);
966 // Allocate a buffer to use as scratch memory. We keep the length 0 so we can keep in it
967 // shallow copies of the contents of `v` without risking the dtors running on copies if
968 // `is_less` panics. When merging two sorted runs, this buffer holds a copy of the shorter run,
969 // which will always have length at most `len / 2`.
970 let mut buf = Vec::with_capacity(len / 2);
972 // In order to identify natural runs in `v`, we traverse it backwards. That might seem like a
973 // strange decision, but consider the fact that merges more often go in the opposite direction
974 // (forwards). According to benchmarks, merging forwards is slightly faster than merging
975 // backwards. To conclude, identifying runs by traversing backwards improves performance.
976 let mut runs = vec![];
979 // Find the next natural run, and reverse it if it's strictly descending.
980 let mut start = end - 1;
984 if is_less(v.get_unchecked(start + 1), v.get_unchecked(start)) {
985 while start > 0 && is_less(v.get_unchecked(start), v.get_unchecked(start - 1)) {
988 v[start..end].reverse();
990 while start > 0 && !is_less(v.get_unchecked(start), v.get_unchecked(start - 1))
998 // Insert some more elements into the run if it's too short. Insertion sort is faster than
999 // merge sort on short sequences, so this significantly improves performance.
1000 while start > 0 && end - start < MIN_RUN {
1002 insert_head(&mut v[start..end], &mut is_less);
1005 // Push this run onto the stack.
1006 runs.push(Run { start, len: end - start });
1009 // Merge some pairs of adjacent runs to satisfy the invariants.
1010 while let Some(r) = collapse(&runs) {
1011 let left = runs[r + 1];
1012 let right = runs[r];
1015 &mut v[left.start..right.start + right.len],
1021 runs[r] = Run { start: left.start, len: left.len + right.len };
1026 // Finally, exactly one run must remain in the stack.
1027 debug_assert!(runs.len() == 1 && runs[0].start == 0 && runs[0].len == len);
1029 // Examines the stack of runs and identifies the next pair of runs to merge. More specifically,
1030 // if `Some(r)` is returned, that means `runs[r]` and `runs[r + 1]` must be merged next. If the
1031 // algorithm should continue building a new run instead, `None` is returned.
1033 // TimSort is infamous for its buggy implementations, as described here:
1034 // http://envisage-project.eu/timsort-specification-and-verification/
1036 // The gist of the story is: we must enforce the invariants on the top four runs on the stack.
1037 // Enforcing them on just top three is not sufficient to ensure that the invariants will still
1038 // hold for *all* runs in the stack.
1040 // This function correctly checks invariants for the top four runs. Additionally, if the top
1041 // run starts at index 0, it will always demand a merge operation until the stack is fully
1042 // collapsed, in order to complete the sort.
1044 fn collapse(runs: &[Run]) -> Option<usize> {
1047 && (runs[n - 1].start == 0
1048 || runs[n - 2].len <= runs[n - 1].len
1049 || (n >= 3 && runs[n - 3].len <= runs[n - 2].len + runs[n - 1].len)
1050 || (n >= 4 && runs[n - 4].len <= runs[n - 3].len + runs[n - 2].len))
1052 if n >= 3 && runs[n - 3].len < runs[n - 1].len { Some(n - 3) } else { Some(n - 2) }
1058 #[derive(Clone, Copy)]