| //! 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 { |
| self.join(sep) |
| } |
| } |
| |
| #[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 |
| } |
| } |
| |
| //////////////////////////////////////////////////////////////////////////////// |
| // 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, |
| } |
| } |