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binary_heap.rs
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binary_heap.rs
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//! A priority queue implemented with a binary heap.
//!
//! Insertion and popping the largest element have *O*(log(*n*)) time complexity.
//! Checking the largest element is *O*(1). Converting a vector to a binary heap
//! can be done in-place, and has *O*(*n*) complexity. A binary heap can also be
//! converted to a sorted vector in-place, allowing it to be used for an *O*(*n* * log(*n*))
//! in-place heapsort.
//!
//! # Examples
//!
//! This is a larger example that implements [Dijkstra's algorithm][dijkstra]
//! to solve the [shortest path problem][sssp] on a [directed graph][dir_graph].
//! It shows how to use [`BinaryHeap`] with custom types.
//!
//! [dijkstra]: https://en.wikipedia.org/wiki/Dijkstra%27s_algorithm
//! [sssp]: https://en.wikipedia.org/wiki/Shortest_path_problem
//! [dir_graph]: https://en.wikipedia.org/wiki/Directed_graph
//!
//! ```
//! use std::cmp::Ordering;
//! use std::collections::BinaryHeap;
//!
//! #[derive(Copy, Clone, Eq, PartialEq)]
//! struct State {
//! cost: usize,
//! position: usize,
//! }
//!
//! // The priority queue depends on `Ord`.
//! // Explicitly implement the trait so the queue becomes a min-heap
//! // instead of a max-heap.
//! impl Ord for State {
//! fn cmp(&self, other: &Self) -> Ordering {
//! // Notice that the we flip the ordering on costs.
//! // In case of a tie we compare positions - this step is necessary
//! // to make implementations of `PartialEq` and `Ord` consistent.
//! other.cost.cmp(&self.cost)
//! .then_with(|| self.position.cmp(&other.position))
//! }
//! }
//!
//! // `PartialOrd` needs to be implemented as well.
//! impl PartialOrd for State {
//! fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
//! Some(self.cmp(other))
//! }
//! }
//!
//! // Each node is represented as a `usize`, for a shorter implementation.
//! struct Edge {
//! node: usize,
//! cost: usize,
//! }
//!
//! // Dijkstra's shortest path algorithm.
//!
//! // Start at `start` and use `dist` to track the current shortest distance
//! // to each node. This implementation isn't memory-efficient as it may leave duplicate
//! // nodes in the queue. It also uses `usize::MAX` as a sentinel value,
//! // for a simpler implementation.
//! fn shortest_path(adj_list: &Vec<Vec<Edge>>, start: usize, goal: usize) -> Option<usize> {
//! // dist[node] = current shortest distance from `start` to `node`
//! let mut dist: Vec<_> = (0..adj_list.len()).map(|_| usize::MAX).collect();
//!
//! let mut heap = BinaryHeap::new();
//!
//! // We're at `start`, with a zero cost
//! dist[start] = 0;
//! heap.push(State { cost: 0, position: start });
//!
//! // Examine the frontier with lower cost nodes first (min-heap)
//! while let Some(State { cost, position }) = heap.pop() {
//! // Alternatively we could have continued to find all shortest paths
//! if position == goal { return Some(cost); }
//!
//! // Important as we may have already found a better way
//! if cost > dist[position] { continue; }
//!
//! // For each node we can reach, see if we can find a way with
//! // a lower cost going through this node
//! for edge in &adj_list[position] {
//! let next = State { cost: cost + edge.cost, position: edge.node };
//!
//! // If so, add it to the frontier and continue
//! if next.cost < dist[next.position] {
//! heap.push(next);
//! // Relaxation, we have now found a better way
//! dist[next.position] = next.cost;
//! }
//! }
//! }
//!
//! // Goal not reachable
//! None
//! }
//!
//! fn main() {
//! // This is the directed graph we're going to use.
//! // The node numbers correspond to the different states,
//! // and the edge weights symbolize the cost of moving
//! // from one node to another.
//! // Note that the edges are one-way.
//! //
//! // 7
//! // +-----------------+
//! // | |
//! // v 1 2 | 2
//! // 0 -----> 1 -----> 3 ---> 4
//! // | ^ ^ ^
//! // | | 1 | |
//! // | | | 3 | 1
//! // +------> 2 -------+ |
//! // 10 | |
//! // +---------------+
//! //
//! // The graph is represented as an adjacency list where each index,
//! // corresponding to a node value, has a list of outgoing edges.
//! // Chosen for its efficiency.
//! let graph = vec![
//! // Node 0
//! vec![Edge { node: 2, cost: 10 },
//! Edge { node: 1, cost: 1 }],
//! // Node 1
//! vec![Edge { node: 3, cost: 2 }],
//! // Node 2
//! vec![Edge { node: 1, cost: 1 },
//! Edge { node: 3, cost: 3 },
//! Edge { node: 4, cost: 1 }],
//! // Node 3
//! vec![Edge { node: 0, cost: 7 },
//! Edge { node: 4, cost: 2 }],
//! // Node 4
//! vec![]];
//!
//! assert_eq!(shortest_path(&graph, 0, 1), Some(1));
//! assert_eq!(shortest_path(&graph, 0, 3), Some(3));
//! assert_eq!(shortest_path(&graph, 3, 0), Some(7));
//! assert_eq!(shortest_path(&graph, 0, 4), Some(5));
//! assert_eq!(shortest_path(&graph, 4, 0), None);
//! }
//! ```
#![allow(missing_docs)]
#![stable(feature = "rust1", since = "1.0.0")]
use core::fmt;
use core::iter::{FromIterator, FusedIterator, InPlaceIterable, SourceIter, TrustedLen};
use core::mem::{self, swap, ManuallyDrop};
use core::ops::{Deref, DerefMut};
use core::ptr;
use crate::collections::TryReserveError;
use crate::slice;
use crate::vec::{self, AsVecIntoIter, Vec};
use super::SpecExtend;
#[cfg(test)]
mod tests;
/// A priority queue implemented with a binary heap.
///
/// This will be a max-heap.
///
/// It is a logic error for an item to be modified in such a way that the
/// item's ordering relative to any other item, as determined by the [`Ord`]
/// trait, changes while it is in the heap. This is normally only possible
/// through [`Cell`], [`RefCell`], global state, I/O, or unsafe code. The
/// behavior resulting from such a logic error is not specified, but will
/// be encapsulated to the `BinaryHeap` that observed the logic error and not
/// result in undefined behavior. This could include panics, incorrect results,
/// aborts, memory leaks, and non-termination.
///
/// # Examples
///
/// ```
/// use std::collections::BinaryHeap;
///
/// // Type inference lets us omit an explicit type signature (which
/// // would be `BinaryHeap<i32>` in this example).
/// let mut heap = BinaryHeap::new();
///
/// // We can use peek to look at the next item in the heap. In this case,
/// // there's no items in there yet so we get None.
/// assert_eq!(heap.peek(), None);
///
/// // Let's add some scores...
/// heap.push(1);
/// heap.push(5);
/// heap.push(2);
///
/// // Now peek shows the most important item in the heap.
/// assert_eq!(heap.peek(), Some(&5));
///
/// // We can check the length of a heap.
/// assert_eq!(heap.len(), 3);
///
/// // We can iterate over the items in the heap, although they are returned in
/// // a random order.
/// for x in &heap {
/// println!("{x}");
/// }
///
/// // If we instead pop these scores, they should come back in order.
/// assert_eq!(heap.pop(), Some(5));
/// assert_eq!(heap.pop(), Some(2));
/// assert_eq!(heap.pop(), Some(1));
/// assert_eq!(heap.pop(), None);
///
/// // We can clear the heap of any remaining items.
/// heap.clear();
///
/// // The heap should now be empty.
/// assert!(heap.is_empty())
/// ```
///
/// A `BinaryHeap` with a known list of items can be initialized from an array:
///
/// ```
/// use std::collections::BinaryHeap;
///
/// let heap = BinaryHeap::from([1, 5, 2]);
/// ```
///
/// ## Min-heap
///
/// Either [`core::cmp::Reverse`] or a custom [`Ord`] implementation can be used to
/// make `BinaryHeap` a min-heap. This makes `heap.pop()` return the smallest
/// value instead of the greatest one.
///
/// ```
/// use std::collections::BinaryHeap;
/// use std::cmp::Reverse;
///
/// let mut heap = BinaryHeap::new();
///
/// // Wrap values in `Reverse`
/// heap.push(Reverse(1));
/// heap.push(Reverse(5));
/// heap.push(Reverse(2));
///
/// // If we pop these scores now, they should come back in the reverse order.
/// assert_eq!(heap.pop(), Some(Reverse(1)));
/// assert_eq!(heap.pop(), Some(Reverse(2)));
/// assert_eq!(heap.pop(), Some(Reverse(5)));
/// assert_eq!(heap.pop(), None);
/// ```
///
/// # Time complexity
///
/// | [push] | [pop] | [peek]/[peek\_mut] |
/// |---------|---------------|--------------------|
/// | *O*(1)~ | *O*(log(*n*)) | *O*(1) |
///
/// The value for `push` is an expected cost; the method documentation gives a
/// more detailed analysis.
///
/// [`core::cmp::Reverse`]: core::cmp::Reverse
/// [`Ord`]: core::cmp::Ord
/// [`Cell`]: core::cell::Cell
/// [`RefCell`]: core::cell::RefCell
/// [push]: BinaryHeap::push
/// [pop]: BinaryHeap::pop
/// [peek]: BinaryHeap::peek
/// [peek\_mut]: BinaryHeap::peek_mut
#[stable(feature = "rust1", since = "1.0.0")]
#[cfg_attr(not(test), rustc_diagnostic_item = "BinaryHeap")]
pub struct BinaryHeap<T> {
data: Vec<T>,
}
/// Structure wrapping a mutable reference to the greatest item on a
/// `BinaryHeap`.
///
/// This `struct` is created by the [`peek_mut`] method on [`BinaryHeap`]. See
/// its documentation for more.
///
/// [`peek_mut`]: BinaryHeap::peek_mut
#[stable(feature = "binary_heap_peek_mut", since = "1.12.0")]
pub struct PeekMut<'a, T: 'a + Ord> {
heap: &'a mut BinaryHeap<T>,
sift: bool,
}
#[stable(feature = "collection_debug", since = "1.17.0")]
impl<T: Ord + fmt::Debug> fmt::Debug for PeekMut<'_, T> {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
f.debug_tuple("PeekMut").field(&self.heap.data[0]).finish()
}
}
#[stable(feature = "binary_heap_peek_mut", since = "1.12.0")]
impl<T: Ord> Drop for PeekMut<'_, T> {
fn drop(&mut self) {
if self.sift {
// SAFETY: PeekMut is only instantiated for non-empty heaps.
unsafe { self.heap.sift_down(0) };
}
}
}
#[stable(feature = "binary_heap_peek_mut", since = "1.12.0")]
impl<T: Ord> Deref for PeekMut<'_, T> {
type Target = T;
fn deref(&self) -> &T {
debug_assert!(!self.heap.is_empty());
// SAFE: PeekMut is only instantiated for non-empty heaps
unsafe { self.heap.data.get_unchecked(0) }
}
}
#[stable(feature = "binary_heap_peek_mut", since = "1.12.0")]
impl<T: Ord> DerefMut for PeekMut<'_, T> {
fn deref_mut(&mut self) -> &mut T {
debug_assert!(!self.heap.is_empty());
self.sift = true;
// SAFE: PeekMut is only instantiated for non-empty heaps
unsafe { self.heap.data.get_unchecked_mut(0) }
}
}
impl<'a, T: Ord> PeekMut<'a, T> {
/// Removes the peeked value from the heap and returns it.
#[stable(feature = "binary_heap_peek_mut_pop", since = "1.18.0")]
pub fn pop(mut this: PeekMut<'a, T>) -> T {
let value = this.heap.pop().unwrap();
this.sift = false;
value
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<T: Clone> Clone for BinaryHeap<T> {
fn clone(&self) -> Self {
BinaryHeap { data: self.data.clone() }
}
fn clone_from(&mut self, source: &Self) {
self.data.clone_from(&source.data);
}
}
#[stable(feature = "rust1", since = "1.0.0")]
impl<T: Ord> Default for BinaryHeap<T> {
/// Creates an empty `BinaryHeap<T>`.
#[inline]
fn default() -> BinaryHeap<T> {
BinaryHeap::new()
}
}
#[stable(feature = "binaryheap_debug", since = "1.4.0")]
impl<T: fmt::Debug> fmt::Debug for BinaryHeap<T> {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
f.debug_list().entries(self.iter()).finish()
}
}
impl<T: Ord> BinaryHeap<T> {
/// Creates an empty `BinaryHeap` as a max-heap.
///
/// # Examples
///
/// Basic usage:
///
/// ```
/// use std::collections::BinaryHeap;
/// let mut heap = BinaryHeap::new();
/// heap.push(4);
/// ```
#[stable(feature = "rust1", since = "1.0.0")]
#[must_use]
pub fn new() -> BinaryHeap<T> {
BinaryHeap { data: vec![] }
}
/// Creates an empty `BinaryHeap` with at least the specified capacity.
///
/// The binary heap will be able to hold at least `capacity` elements without
/// reallocating. This method is allowed to allocate for more elements than
/// `capacity`. If `capacity` is 0, the binary heap will not allocate.
///
/// # Examples
///
/// Basic usage:
///
/// ```
/// use std::collections::BinaryHeap;
/// let mut heap = BinaryHeap::with_capacity(10);
/// heap.push(4);
/// ```
#[stable(feature = "rust1", since = "1.0.0")]
#[must_use]
pub fn with_capacity(capacity: usize) -> BinaryHeap<T> {
BinaryHeap { data: Vec::with_capacity(capacity) }
}
/// Returns a mutable reference to the greatest item in the binary heap, or
/// `None` if it is empty.
///
/// Note: If the `PeekMut` value is leaked, the heap may be in an
/// inconsistent state.
///
/// # Examples
///
/// Basic usage:
///
/// ```
/// use std::collections::BinaryHeap;
/// let mut heap = BinaryHeap::new();
/// assert!(heap.peek_mut().is_none());
///
/// heap.push(1);
/// heap.push(5);
/// heap.push(2);
/// {
/// let mut val = heap.peek_mut().unwrap();
/// *val = 0;
/// }
/// assert_eq!(heap.peek(), Some(&2));
/// ```
///
/// # Time complexity
///
/// If the item is modified then the worst case time complexity is *O*(log(*n*)),
/// otherwise it's *O*(1).
#[stable(feature = "binary_heap_peek_mut", since = "1.12.0")]
pub fn peek_mut(&mut self) -> Option<PeekMut<'_, T>> {
if self.is_empty() { None } else { Some(PeekMut { heap: self, sift: false }) }
}
/// Removes the greatest item from the binary heap and returns it, or `None` if it
/// is empty.
///
/// # Examples
///
/// Basic usage:
///
/// ```
/// use std::collections::BinaryHeap;
/// let mut heap = BinaryHeap::from([1, 3]);
///
/// assert_eq!(heap.pop(), Some(3));
/// assert_eq!(heap.pop(), Some(1));
/// assert_eq!(heap.pop(), None);
/// ```
///
/// # Time complexity
///
/// The worst case cost of `pop` on a heap containing *n* elements is *O*(log(*n*)).
#[stable(feature = "rust1", since = "1.0.0")]
pub fn pop(&mut self) -> Option<T> {
self.data.pop().map(|mut item| {
if !self.is_empty() {
swap(&mut item, &mut self.data[0]);
// SAFETY: !self.is_empty() means that self.len() > 0
unsafe { self.sift_down_to_bottom(0) };
}
item
})
}
/// Pushes an item onto the binary heap.
///
/// # Examples
///
/// Basic usage:
///
/// ```
/// use std::collections::BinaryHeap;
/// let mut heap = BinaryHeap::new();
/// heap.push(3);
/// heap.push(5);
/// heap.push(1);
///
/// assert_eq!(heap.len(), 3);
/// assert_eq!(heap.peek(), Some(&5));
/// ```
///
/// # Time complexity
///
/// The expected cost of `push`, averaged over every possible ordering of
/// the elements being pushed, and over a sufficiently large number of
/// pushes, is *O*(1). This is the most meaningful cost metric when pushing
/// elements that are *not* already in any sorted pattern.
///
/// The time complexity degrades if elements are pushed in predominantly
/// ascending order. In the worst case, elements are pushed in ascending
/// sorted order and the amortized cost per push is *O*(log(*n*)) against a heap
/// containing *n* elements.
///
/// The worst case cost of a *single* call to `push` is *O*(*n*). The worst case
/// occurs when capacity is exhausted and needs a resize. The resize cost
/// has been amortized in the previous figures.
#[stable(feature = "rust1", since = "1.0.0")]
pub fn push(&mut self, item: T) {
let old_len = self.len();
self.data.push(item);
// SAFETY: Since we pushed a new item it means that
// old_len = self.len() - 1 < self.len()
unsafe { self.sift_up(0, old_len) };
}
/// Consumes the `BinaryHeap` and returns a vector in sorted
/// (ascending) order.
///
/// # Examples
///
/// Basic usage:
///
/// ```
/// use std::collections::BinaryHeap;
///
/// let mut heap = BinaryHeap::from([1, 2, 4, 5, 7]);
/// heap.push(6);
/// heap.push(3);
///
/// let vec = heap.into_sorted_vec();
/// assert_eq!(vec, [1, 2, 3, 4, 5, 6, 7]);
/// ```
#[must_use = "`self` will be dropped if the result is not used"]
#[stable(feature = "binary_heap_extras_15", since = "1.5.0")]
pub fn into_sorted_vec(mut self) -> Vec<T> {
let mut end = self.len();
while end > 1 {
end -= 1;
// SAFETY: `end` goes from `self.len() - 1` to 1 (both included),
// so it's always a valid index to access.
// It is safe to access index 0 (i.e. `ptr`), because
// 1 <= end < self.len(), which means self.len() >= 2.
unsafe {
let ptr = self.data.as_mut_ptr();
ptr::swap(ptr, ptr.add(end));
}
// SAFETY: `end` goes from `self.len() - 1` to 1 (both included) so:
// 0 < 1 <= end <= self.len() - 1 < self.len()
// Which means 0 < end and end < self.len().
unsafe { self.sift_down_range(0, end) };
}
self.into_vec()
}
// The implementations of sift_up and sift_down use unsafe blocks in
// order to move an element out of the vector (leaving behind a
// hole), shift along the others and move the removed element back into the
// vector at the final location of the hole.
// The `Hole` type is used to represent this, and make sure
// the hole is filled back at the end of its scope, even on panic.
// Using a hole reduces the constant factor compared to using swaps,
// which involves twice as many moves.
/// # Safety
///
/// The caller must guarantee that `pos < self.len()`.
unsafe fn sift_up(&mut self, start: usize, pos: usize) -> usize {
// Take out the value at `pos` and create a hole.
// SAFETY: The caller guarantees that pos < self.len()
let mut hole = unsafe { Hole::new(&mut self.data, pos) };
while hole.pos() > start {
let parent = (hole.pos() - 1) / 2;
// SAFETY: hole.pos() > start >= 0, which means hole.pos() > 0
// and so hole.pos() - 1 can't underflow.
// This guarantees that parent < hole.pos() so
// it's a valid index and also != hole.pos().
if hole.element() <= unsafe { hole.get(parent) } {
break;
}
// SAFETY: Same as above
unsafe { hole.move_to(parent) };
}
hole.pos()
}
/// Take an element at `pos` and move it down the heap,
/// while its children are larger.
///
/// # Safety
///
/// The caller must guarantee that `pos < end <= self.len()`.
unsafe fn sift_down_range(&mut self, pos: usize, end: usize) {
// SAFETY: The caller guarantees that pos < end <= self.len().
let mut hole = unsafe { Hole::new(&mut self.data, pos) };
let mut child = 2 * hole.pos() + 1;
// Loop invariant: child == 2 * hole.pos() + 1.
while child <= end.saturating_sub(2) {
// compare with the greater of the two children
// SAFETY: child < end - 1 < self.len() and
// child + 1 < end <= self.len(), so they're valid indexes.
// child == 2 * hole.pos() + 1 != hole.pos() and
// child + 1 == 2 * hole.pos() + 2 != hole.pos().
// FIXME: 2 * hole.pos() + 1 or 2 * hole.pos() + 2 could overflow
// if T is a ZST
child += unsafe { hole.get(child) <= hole.get(child + 1) } as usize;
// if we are already in order, stop.
// SAFETY: child is now either the old child or the old child+1
// We already proven that both are < self.len() and != hole.pos()
if hole.element() >= unsafe { hole.get(child) } {
return;
}
// SAFETY: same as above.
unsafe { hole.move_to(child) };
child = 2 * hole.pos() + 1;
}
// SAFETY: && short circuit, which means that in the
// second condition it's already true that child == end - 1 < self.len().
if child == end - 1 && hole.element() < unsafe { hole.get(child) } {
// SAFETY: child is already proven to be a valid index and
// child == 2 * hole.pos() + 1 != hole.pos().
unsafe { hole.move_to(child) };
}
}
/// # Safety
///
/// The caller must guarantee that `pos < self.len()`.
unsafe fn sift_down(&mut self, pos: usize) {
let len = self.len();
// SAFETY: pos < len is guaranteed by the caller and
// obviously len = self.len() <= self.len().
unsafe { self.sift_down_range(pos, len) };
}
/// Take an element at `pos` and move it all the way down the heap,
/// then sift it up to its position.
///
/// Note: This is faster when the element is known to be large / should
/// be closer to the bottom.
///
/// # Safety
///
/// The caller must guarantee that `pos < self.len()`.
unsafe fn sift_down_to_bottom(&mut self, mut pos: usize) {
let end = self.len();
let start = pos;
// SAFETY: The caller guarantees that pos < self.len().
let mut hole = unsafe { Hole::new(&mut self.data, pos) };
let mut child = 2 * hole.pos() + 1;
// Loop invariant: child == 2 * hole.pos() + 1.
while child <= end.saturating_sub(2) {
// SAFETY: child < end - 1 < self.len() and
// child + 1 < end <= self.len(), so they're valid indexes.
// child == 2 * hole.pos() + 1 != hole.pos() and
// child + 1 == 2 * hole.pos() + 2 != hole.pos().
// FIXME: 2 * hole.pos() + 1 or 2 * hole.pos() + 2 could overflow
// if T is a ZST
child += unsafe { hole.get(child) <= hole.get(child + 1) } as usize;
// SAFETY: Same as above
unsafe { hole.move_to(child) };
child = 2 * hole.pos() + 1;
}
if child == end - 1 {
// SAFETY: child == end - 1 < self.len(), so it's a valid index
// and child == 2 * hole.pos() + 1 != hole.pos().
unsafe { hole.move_to(child) };
}
pos = hole.pos();
drop(hole);
// SAFETY: pos is the position in the hole and was already proven
// to be a valid index.
unsafe { self.sift_up(start, pos) };
}
/// Rebuild assuming data[0..start] is still a proper heap.
fn rebuild_tail(&mut self, start: usize) {
if start == self.len() {
return;
}
let tail_len = self.len() - start;
#[inline(always)]
fn log2_fast(x: usize) -> usize {
(usize::BITS - x.leading_zeros() - 1) as usize
}
// `rebuild` takes O(self.len()) operations
// and about 2 * self.len() comparisons in the worst case
// while repeating `sift_up` takes O(tail_len * log(start)) operations
// and about 1 * tail_len * log_2(start) comparisons in the worst case,
// assuming start >= tail_len. For larger heaps, the crossover point
// no longer follows this reasoning and was determined empirically.
let better_to_rebuild = if start < tail_len {
true
} else if self.len() <= 2048 {
2 * self.len() < tail_len * log2_fast(start)
} else {
2 * self.len() < tail_len * 11
};
if better_to_rebuild {
self.rebuild();
} else {
for i in start..self.len() {
// SAFETY: The index `i` is always less than self.len().
unsafe { self.sift_up(0, i) };
}
}
}
fn rebuild(&mut self) {
let mut n = self.len() / 2;
while n > 0 {
n -= 1;
// SAFETY: n starts from self.len() / 2 and goes down to 0.
// The only case when !(n < self.len()) is if
// self.len() == 0, but it's ruled out by the loop condition.
unsafe { self.sift_down(n) };
}
}
/// Moves all the elements of `other` into `self`, leaving `other` empty.
///
/// # Examples
///
/// Basic usage:
///
/// ```
/// use std::collections::BinaryHeap;
///
/// let mut a = BinaryHeap::from([-10, 1, 2, 3, 3]);
/// let mut b = BinaryHeap::from([-20, 5, 43]);
///
/// a.append(&mut b);
///
/// assert_eq!(a.into_sorted_vec(), [-20, -10, 1, 2, 3, 3, 5, 43]);
/// assert!(b.is_empty());
/// ```
#[stable(feature = "binary_heap_append", since = "1.11.0")]
pub fn append(&mut self, other: &mut Self) {
if self.len() < other.len() {
swap(self, other);
}
let start = self.data.len();
self.data.append(&mut other.data);
self.rebuild_tail(start);
}
/// Clears the binary heap, returning an iterator over the removed elements
/// in heap order. If the iterator is dropped before being fully consumed,
/// it drops the remaining elements in heap order.
///
/// The returned iterator keeps a mutable borrow on the heap to optimize
/// its implementation.
///
/// Note:
/// * `.drain_sorted()` is *O*(*n* \* log(*n*)); much slower than `.drain()`.
/// You should use the latter for most cases.
///
/// # Examples
///
/// Basic usage:
///
/// ```
/// #![feature(binary_heap_drain_sorted)]
/// use std::collections::BinaryHeap;
///
/// let mut heap = BinaryHeap::from([1, 2, 3, 4, 5]);
/// assert_eq!(heap.len(), 5);
///
/// drop(heap.drain_sorted()); // removes all elements in heap order
/// assert_eq!(heap.len(), 0);
/// ```
#[inline]
#[unstable(feature = "binary_heap_drain_sorted", issue = "59278")]
pub fn drain_sorted(&mut self) -> DrainSorted<'_, T> {
DrainSorted { inner: self }
}
/// Retains only the elements specified by the predicate.
///
/// In other words, remove all elements `e` for which `f(&e)` returns
/// `false`. The elements are visited in unsorted (and unspecified) order.
///
/// # Examples
///
/// Basic usage:
///
/// ```
/// #![feature(binary_heap_retain)]
/// use std::collections::BinaryHeap;
///
/// let mut heap = BinaryHeap::from([-10, -5, 1, 2, 4, 13]);
///
/// heap.retain(|x| x % 2 == 0); // only keep even numbers
///
/// assert_eq!(heap.into_sorted_vec(), [-10, 2, 4])
/// ```
#[unstable(feature = "binary_heap_retain", issue = "71503")]
pub fn retain<F>(&mut self, mut f: F)
where
F: FnMut(&T) -> bool,
{
let mut first_removed = self.len();
let mut i = 0;
self.data.retain(|e| {
let keep = f(e);
if !keep && i < first_removed {
first_removed = i;
}
i += 1;
keep
});
// data[0..first_removed] is untouched, so we only need to rebuild the tail:
self.rebuild_tail(first_removed);
}
}
impl<T> BinaryHeap<T> {
/// Returns an iterator visiting all values in the underlying vector, in
/// arbitrary order.
///
/// # Examples
///
/// Basic usage:
///
/// ```
/// use std::collections::BinaryHeap;
/// let heap = BinaryHeap::from([1, 2, 3, 4]);
///
/// // Print 1, 2, 3, 4 in arbitrary order
/// for x in heap.iter() {
/// println!("{x}");
/// }
/// ```
#[stable(feature = "rust1", since = "1.0.0")]
pub fn iter(&self) -> Iter<'_, T> {
Iter { iter: self.data.iter() }
}
/// Returns an iterator which retrieves elements in heap order.
/// This method consumes the original heap.
///
/// # Examples
///
/// Basic usage:
///
/// ```
/// #![feature(binary_heap_into_iter_sorted)]
/// use std::collections::BinaryHeap;
/// let heap = BinaryHeap::from([1, 2, 3, 4, 5]);
///
/// assert_eq!(heap.into_iter_sorted().take(2).collect::<Vec<_>>(), [5, 4]);
/// ```
#[unstable(feature = "binary_heap_into_iter_sorted", issue = "59278")]
pub fn into_iter_sorted(self) -> IntoIterSorted<T> {
IntoIterSorted { inner: self }
}
/// Returns the greatest item in the binary heap, or `None` if it is empty.
///
/// # Examples
///
/// Basic usage:
///
/// ```
/// use std::collections::BinaryHeap;
/// let mut heap = BinaryHeap::new();
/// assert_eq!(heap.peek(), None);
///
/// heap.push(1);
/// heap.push(5);
/// heap.push(2);
/// assert_eq!(heap.peek(), Some(&5));
///
/// ```
///
/// # Time complexity
///
/// Cost is *O*(1) in the worst case.
#[must_use]
#[stable(feature = "rust1", since = "1.0.0")]
pub fn peek(&self) -> Option<&T> {
self.data.get(0)
}
/// Returns the number of elements the binary heap can hold without reallocating.
///
/// # Examples
///
/// Basic usage:
///
/// ```
/// use std::collections::BinaryHeap;
/// let mut heap = BinaryHeap::with_capacity(100);
/// assert!(heap.capacity() >= 100);
/// heap.push(4);
/// ```
#[must_use]
#[stable(feature = "rust1", since = "1.0.0")]
pub fn capacity(&self) -> usize {
self.data.capacity()
}
/// Reserves the minimum capacity for at least `additional` elements more than
/// the current length. Unlike [`reserve`], this will not
/// deliberately over-allocate to speculatively avoid frequent allocations.
/// After calling `reserve_exact`, capacity will be greater than or equal to
/// `self.len() + additional`. Does nothing if the capacity is already
/// sufficient.
///
/// [`reserve`]: BinaryHeap::reserve
///
/// # Panics
///
/// Panics if the new capacity overflows [`usize`].
///
/// # Examples
///
/// Basic usage:
///
/// ```
/// use std::collections::BinaryHeap;
/// let mut heap = BinaryHeap::new();
/// heap.reserve_exact(100);
/// assert!(heap.capacity() >= 100);
/// heap.push(4);
/// ```
///
/// [`reserve`]: BinaryHeap::reserve
#[stable(feature = "rust1", since = "1.0.0")]
pub fn reserve_exact(&mut self, additional: usize) {
self.data.reserve_exact(additional);
}
/// Reserves capacity for at least `additional` elements more than the
/// current length. The allocator may reserve more space to speculatively
/// avoid frequent allocations. After calling `reserve`,
/// capacity will be greater than or equal to `self.len() + additional`.
/// Does nothing if capacity is already sufficient.
///
/// # Panics
///
/// Panics if the new capacity overflows [`usize`].
///
/// # Examples
///
/// Basic usage:
///
/// ```
/// use std::collections::BinaryHeap;
/// let mut heap = BinaryHeap::new();
/// heap.reserve(100);
/// assert!(heap.capacity() >= 100);
/// heap.push(4);
/// ```
#[stable(feature = "rust1", since = "1.0.0")]
pub fn reserve(&mut self, additional: usize) {
self.data.reserve(additional);
}
/// Tries to reserve the minimum capacity for at least `additional` elements
/// more than the current length. Unlike [`try_reserve`], this will not
/// deliberately over-allocate to speculatively avoid frequent allocations.
/// After calling `try_reserve_exact`, capacity will be greater than or
/// equal to `self.len() + additional` if it returns `Ok(())`.
/// Does nothing if the capacity is already sufficient.
///
/// Note that the allocator may give the collection more space than it
/// requests. Therefore, capacity can not be relied upon to be precisely
/// minimal. Prefer [`try_reserve`] if future insertions are expected.
///
/// [`try_reserve`]: BinaryHeap::try_reserve
///
/// # Errors
///
/// If the capacity overflows, or the allocator reports a failure, then an error
/// is returned.
///
/// # Examples
///
/// ```
/// use std::collections::BinaryHeap;
/// use std::collections::TryReserveError;
///
/// fn find_max_slow(data: &[u32]) -> Result<Option<u32>, TryReserveError> {
/// let mut heap = BinaryHeap::new();
///
/// // Pre-reserve the memory, exiting if we can't
/// heap.try_reserve_exact(data.len())?;
///
/// // Now we know this can't OOM in the middle of our complex work
/// heap.extend(data.iter());
///
/// Ok(heap.pop())