// Copyright 2013-2014 The Rust Project Developers. See the COPYRIGHT // file at the top-level directory of this distribution and at // http://rust-lang.org/COPYRIGHT. // // Licensed under the Apache License, Version 2.0 or the MIT license // , at your // option. This file may not be copied, modified, or distributed // except according to those terms. //! 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 priority queue can be done in-place, and has `O(n)` //! complexity. A priority queue 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 which implements [Dijkstra's algorithm][dijkstra] //! to solve the [shortest path problem][sssp] on a [directed graph][dir_graph]. //! It showcases how to use the `BinaryHeap` with custom types. //! //! [dijkstra]: http://en.wikipedia.org/wiki/Dijkstra%27s_algorithm //! [sssp]: http://en.wikipedia.org/wiki/Shortest_path_problem //! [dir_graph]: http://en.wikipedia.org/wiki/Directed_graph //! //! ``` //! use std::collections::BinaryHeap; //! use std::uint; //! //! #[deriving(Copy, Eq, PartialEq)] //! struct State { //! cost: uint, //! position: uint //! } //! //! // 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: &State) -> Ordering { //! // Notice that the we flip the ordering here //! other.cost.cmp(&self.cost) //! } //! } //! //! // `PartialOrd` needs to be implemented as well. //! impl PartialOrd for State { //! fn partial_cmp(&self, other: &State) -> Option { //! Some(self.cmp(other)) //! } //! } //! //! // Each node is represented as an `uint`, for a shorter implementation. //! struct Edge { //! node: uint, //! cost: uint //! } //! //! // 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 `uint::MAX` as a sentinel value, //! // for a simpler implementation. //! fn shortest_path(adj_list: &Vec>, start: uint, goal: uint) -> uint { //! // dist[node] = current shortest distance from `start` to `node` //! let mut dist = Vec::from_elem(adj_list.len(), uint::MAX); //! //! let mut heap = BinaryHeap::new(); //! //! // We're at `start`, with a zero cost //! dist[start] = 0u; //! heap.push(State { cost: 0u, position: start }); //! //! // Examine the frontier with lower cost nodes first (min-heap) //! loop { //! let State { cost, position } = match heap.pop() { //! None => break, // empty //! Some(s) => s //! }; //! //! // Alternatively we could have continued to find all shortest paths //! if position == goal { return 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].iter() { //! 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 //! uint::MAX //! } //! //! fn main() { //! // This is the directed graph we're going to use. //! // The node numbers correspond to the different states, //! // and the edge weights symbolises the cost of moving //! // from one node to another. //! // Note that the edges are one-way. //! // //! // 7 //! // +-----------------+ //! // | | //! // v 1 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 it's 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), 1); //! assert_eq!(shortest_path(&graph, 0, 3), 3); //! assert_eq!(shortest_path(&graph, 3, 0), 7); //! assert_eq!(shortest_path(&graph, 0, 4), 5); //! assert_eq!(shortest_path(&graph, 4, 0), uint::MAX); //! } //! ``` #![allow(missing_docs)] use core::prelude::*; use core::default::Default; use core::mem::{zeroed, replace, swap}; use core::ptr; use slice; use vec::{mod, Vec}; /// A priority queue implemented with a binary heap. /// /// This will be a max-heap. #[deriving(Clone)] pub struct BinaryHeap { data: Vec, } #[stable] impl Default for BinaryHeap { #[inline] #[stable] fn default() -> BinaryHeap { BinaryHeap::new() } } impl BinaryHeap { /// Creates an empty `BinaryHeap` as a max-heap. /// /// # Examples /// /// ``` /// use std::collections::BinaryHeap; /// let heap: BinaryHeap = BinaryHeap::new(); /// ``` #[unstable = "matches collection reform specification, waiting for dust to settle"] pub fn new() -> BinaryHeap { BinaryHeap{data: vec!(),} } /// Creates an empty `BinaryHeap` with a specific capacity. /// This preallocates enough memory for `capacity` elements, /// so that the `BinaryHeap` does not have to be reallocated /// until it contains at least that many values. /// /// # Examples /// /// ``` /// use std::collections::BinaryHeap; /// let heap: BinaryHeap = BinaryHeap::with_capacity(10u); /// ``` #[unstable = "matches collection reform specification, waiting for dust to settle"] pub fn with_capacity(capacity: uint) -> BinaryHeap { BinaryHeap { data: Vec::with_capacity(capacity) } } /// Creates a `BinaryHeap` from a vector. This is sometimes called /// `heapifying` the vector. /// /// # Examples /// /// ``` /// use std::collections::BinaryHeap; /// let heap = BinaryHeap::from_vec(vec![9i, 1, 2, 7, 3, 2]); /// ``` pub fn from_vec(xs: Vec) -> BinaryHeap { let mut q = BinaryHeap{data: xs,}; let mut n = q.len() / 2; while n > 0 { n -= 1; q.siftdown(n) } q } /// An iterator visiting all values in underlying vector, in /// arbitrary order. /// /// # Examples /// /// ``` /// use std::collections::BinaryHeap; /// let heap = BinaryHeap::from_vec(vec![1i, 2, 3, 4]); /// /// // Print 1, 2, 3, 4 in arbitrary order /// for x in heap.iter() { /// println!("{}", x); /// } /// ``` #[unstable = "matches collection reform specification, waiting for dust to settle"] pub fn iter(&self) -> Iter { Iter { iter: self.data.iter() } } /// Creates a consuming iterator, that is, one that moves each value out of /// the binary heap in arbitrary order. The binary heap cannot be used /// after calling this. /// /// # Examples /// /// ``` /// use std::collections::BinaryHeap; /// let pq = BinaryHeap::from_vec(vec![1i, 2, 3, 4]); /// /// // Print 1, 2, 3, 4 in arbitrary order /// for x in pq.into_iter() { /// // x has type int, not &int /// println!("{}", x); /// } /// ``` #[unstable = "matches collection reform specification, waiting for dust to settle"] pub fn into_iter(self) -> IntoIter { IntoIter { iter: self.data.into_iter() } } /// Returns the greatest item in a queue, or `None` if it is empty. /// /// # Examples /// /// ``` /// use std::collections::BinaryHeap; /// /// let mut heap = BinaryHeap::new(); /// assert_eq!(heap.peek(), None); /// /// heap.push(1i); /// heap.push(5i); /// heap.push(2i); /// assert_eq!(heap.peek(), Some(&5i)); /// /// ``` #[stable] pub fn peek(&self) -> Option<&T> { self.data.get(0) } /// Returns the number of elements the queue can hold without reallocating. /// /// # Examples /// /// ``` /// use std::collections::BinaryHeap; /// /// let heap: BinaryHeap = BinaryHeap::with_capacity(100u); /// assert!(heap.capacity() >= 100u); /// ``` #[unstable = "matches collection reform specification, waiting for dust to settle"] pub fn capacity(&self) -> uint { self.data.capacity() } /// Reserves the minimum capacity for exactly `additional` more elements to be inserted in the /// given `BinaryHeap`. 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 `reserve` if future /// insertions are expected. /// /// # Panics /// /// Panics if the new capacity overflows `uint`. /// /// # Examples /// /// ``` /// use std::collections::BinaryHeap; /// /// let mut heap: BinaryHeap = BinaryHeap::new(); /// heap.reserve_exact(100u); /// assert!(heap.capacity() >= 100u); /// ``` #[unstable = "matches collection reform specification, waiting for dust to settle"] pub fn reserve_exact(&mut self, additional: uint) { self.data.reserve_exact(additional) } /// Reserves capacity for at least `additional` more elements to be inserted in the /// `BinaryHeap`. The collection may reserve more space to avoid frequent reallocations. /// /// # Panics /// /// Panics if the new capacity overflows `uint`. /// /// # Examples /// /// ``` /// use std::collections::BinaryHeap; /// /// let mut heap: BinaryHeap = BinaryHeap::new(); /// heap.reserve(100u); /// assert!(heap.capacity() >= 100u); /// ``` #[unstable = "matches collection reform specification, waiting for dust to settle"] pub fn reserve(&mut self, additional: uint) { self.data.reserve(additional) } /// Discards as much additional capacity as possible. #[unstable = "matches collection reform specification, waiting for dust to settle"] pub fn shrink_to_fit(&mut self) { self.data.shrink_to_fit() } /// Removes the greatest item from a queue and returns it, or `None` if it /// is empty. /// /// # Examples /// /// ``` /// use std::collections::BinaryHeap; /// /// let mut heap = BinaryHeap::from_vec(vec![1i, 3]); /// /// assert_eq!(heap.pop(), Some(3i)); /// assert_eq!(heap.pop(), Some(1i)); /// assert_eq!(heap.pop(), None); /// ``` #[unstable = "matches collection reform specification, waiting for dust to settle"] pub fn pop(&mut self) -> Option { match self.data.pop() { None => { None } Some(mut item) => { if !self.is_empty() { swap(&mut item, &mut self.data[0]); self.siftdown(0); } Some(item) } } } /// Pushes an item onto the queue. /// /// # Examples /// /// ``` /// use std::collections::BinaryHeap; /// /// let mut heap = BinaryHeap::new(); /// heap.push(3i); /// heap.push(5i); /// heap.push(1i); /// /// assert_eq!(heap.len(), 3); /// assert_eq!(heap.peek(), Some(&5i)); /// ``` #[unstable = "matches collection reform specification, waiting for dust to settle"] pub fn push(&mut self, item: T) { let old_len = self.len(); self.data.push(item); self.siftup(0, old_len); } /// Pushes an item onto a queue then pops the greatest item off the queue in /// an optimized fashion. /// /// # Examples /// /// ``` /// use std::collections::BinaryHeap; /// /// let mut heap = BinaryHeap::new(); /// heap.push(1i); /// heap.push(5i); /// /// assert_eq!(heap.push_pop(3i), 5); /// assert_eq!(heap.push_pop(9i), 9); /// assert_eq!(heap.len(), 2); /// assert_eq!(heap.peek(), Some(&3i)); /// ``` pub fn push_pop(&mut self, mut item: T) -> T { match self.data.get_mut(0) { None => return item, Some(top) => if *top > item { swap(&mut item, top); } else { return item; }, } self.siftdown(0); item } /// Pops the greatest item off a queue then pushes an item onto the queue in /// an optimized fashion. The push is done regardless of whether the queue /// was empty. /// /// # Examples /// /// ``` /// use std::collections::BinaryHeap; /// /// let mut heap = BinaryHeap::new(); /// /// assert_eq!(heap.replace(1i), None); /// assert_eq!(heap.replace(3i), Some(1i)); /// assert_eq!(heap.len(), 1); /// assert_eq!(heap.peek(), Some(&3i)); /// ``` pub fn replace(&mut self, mut item: T) -> Option { if !self.is_empty() { swap(&mut item, &mut self.data[0]); self.siftdown(0); Some(item) } else { self.push(item); None } } /// Consumes the `BinaryHeap` and returns the underlying vector /// in arbitrary order. /// /// # Examples /// /// ``` /// use std::collections::BinaryHeap; /// /// let heap = BinaryHeap::from_vec(vec![1i, 2, 3, 4, 5, 6, 7]); /// let vec = heap.into_vec(); /// /// // Will print in some order /// for x in vec.iter() { /// println!("{}", x); /// } /// ``` pub fn into_vec(self) -> Vec { self.data } /// Consumes the `BinaryHeap` and returns a vector in sorted /// (ascending) order. /// /// # Examples /// /// ``` /// use std::collections::BinaryHeap; /// /// let mut heap = BinaryHeap::from_vec(vec![1i, 2, 4, 5, 7]); /// heap.push(6); /// heap.push(3); /// /// let vec = heap.into_sorted_vec(); /// assert_eq!(vec, vec![1i, 2, 3, 4, 5, 6, 7]); /// ``` pub fn into_sorted_vec(mut self) -> Vec { let mut end = self.len(); while end > 1 { end -= 1; self.data.swap(0, end); self.siftdown_range(0, end) } self.into_vec() } // The implementations of siftup and siftdown use unsafe blocks in // order to move an element out of the vector (leaving behind a // zeroed element), shift along the others and move it back into the // vector over the junk element. This reduces the constant factor // compared to using swaps, which involves twice as many moves. fn siftup(&mut self, start: uint, mut pos: uint) { unsafe { let new = replace(&mut self.data[pos], zeroed()); while pos > start { let parent = (pos - 1) >> 1; if new > self.data[parent] { let x = replace(&mut self.data[parent], zeroed()); ptr::write(&mut self.data[pos], x); pos = parent; continue } break } ptr::write(&mut self.data[pos], new); } } fn siftdown_range(&mut self, mut pos: uint, end: uint) { unsafe { let start = pos; let new = replace(&mut self.data[pos], zeroed()); let mut child = 2 * pos + 1; while child < end { let right = child + 1; if right < end && !(self.data[child] > self.data[right]) { child = right; } let x = replace(&mut self.data[child], zeroed()); ptr::write(&mut self.data[pos], x); pos = child; child = 2 * pos + 1; } ptr::write(&mut self.data[pos], new); self.siftup(start, pos); } } fn siftdown(&mut self, pos: uint) { let len = self.len(); self.siftdown_range(pos, len); } /// Returns the length of the queue. #[unstable = "matches collection reform specification, waiting for dust to settle"] pub fn len(&self) -> uint { self.data.len() } /// Returns true if the queue contains no elements #[unstable = "matches collection reform specification, waiting for dust to settle"] pub fn is_empty(&self) -> bool { self.len() == 0 } /// Clears the queue, returning an iterator over the removed elements. #[inline] #[unstable = "matches collection reform specification, waiting for dust to settle"] pub fn drain<'a>(&'a mut self) -> Drain<'a, T> { Drain { iter: self.data.drain(), } } /// Drops all items from the queue. #[unstable = "matches collection reform specification, waiting for dust to settle"] pub fn clear(&mut self) { self.drain(); } } /// `BinaryHeap` iterator. pub struct Iter <'a, T: 'a> { iter: slice::Iter<'a, T>, } impl<'a, T> Iterator<&'a T> for Iter<'a, T> { #[inline] fn next(&mut self) -> Option<&'a T> { self.iter.next() } #[inline] fn size_hint(&self) -> (uint, Option) { self.iter.size_hint() } } impl<'a, T> DoubleEndedIterator<&'a T> for Iter<'a, T> { #[inline] fn next_back(&mut self) -> Option<&'a T> { self.iter.next_back() } } impl<'a, T> ExactSizeIterator<&'a T> for Iter<'a, T> {} /// An iterator that moves out of a `BinaryHeap`. pub struct IntoIter { iter: vec::IntoIter, } impl Iterator for IntoIter { #[inline] fn next(&mut self) -> Option { self.iter.next() } #[inline] fn size_hint(&self) -> (uint, Option) { self.iter.size_hint() } } impl DoubleEndedIterator for IntoIter { #[inline] fn next_back(&mut self) -> Option { self.iter.next_back() } } impl ExactSizeIterator for IntoIter {} /// An iterator that drains a `BinaryHeap`. pub struct Drain<'a, T: 'a> { iter: vec::Drain<'a, T>, } impl<'a, T: 'a> Iterator for Drain<'a, T> { #[inline] fn next(&mut self) -> Option { self.iter.next() } #[inline] fn size_hint(&self) -> (uint, Option) { self.iter.size_hint() } } impl<'a, T: 'a> DoubleEndedIterator for Drain<'a, T> { #[inline] fn next_back(&mut self) -> Option { self.iter.next_back() } } impl<'a, T: 'a> ExactSizeIterator for Drain<'a, T> {} impl FromIterator for BinaryHeap { fn from_iter>(iter: Iter) -> BinaryHeap { BinaryHeap::from_vec(iter.collect()) } } impl Extend for BinaryHeap { fn extend>(&mut self, mut iter: Iter) { let (lower, _) = iter.size_hint(); self.reserve(lower); for elem in iter { self.push(elem); } } } #[cfg(test)] mod tests { use prelude::*; use super::BinaryHeap; #[test] fn test_iterator() { let data = vec!(5i, 9, 3); let iterout = [9i, 5, 3]; let heap = BinaryHeap::from_vec(data); let mut i = 0; for el in heap.iter() { assert_eq!(*el, iterout[i]); i += 1; } } #[test] fn test_iterator_reverse() { let data = vec!(5i, 9, 3); let iterout = vec!(3i, 5, 9); let pq = BinaryHeap::from_vec(data); let v: Vec = pq.iter().rev().map(|&x| x).collect(); assert_eq!(v, iterout); } #[test] fn test_move_iter() { let data = vec!(5i, 9, 3); let iterout = vec!(9i, 5, 3); let pq = BinaryHeap::from_vec(data); let v: Vec = pq.into_iter().collect(); assert_eq!(v, iterout); } #[test] fn test_move_iter_size_hint() { let data = vec!(5i, 9); let pq = BinaryHeap::from_vec(data); let mut it = pq.into_iter(); assert_eq!(it.size_hint(), (2, Some(2))); assert_eq!(it.next(), Some(9i)); assert_eq!(it.size_hint(), (1, Some(1))); assert_eq!(it.next(), Some(5i)); assert_eq!(it.size_hint(), (0, Some(0))); assert_eq!(it.next(), None); } #[test] fn test_move_iter_reverse() { let data = vec!(5i, 9, 3); let iterout = vec!(3i, 5, 9); let pq = BinaryHeap::from_vec(data); let v: Vec = pq.into_iter().rev().collect(); assert_eq!(v, iterout); } #[test] fn test_peek_and_pop() { let data = vec!(2u, 4, 6, 2, 1, 8, 10, 3, 5, 7, 0, 9, 1); let mut sorted = data.clone(); sorted.sort(); let mut heap = BinaryHeap::from_vec(data); while !heap.is_empty() { assert_eq!(heap.peek().unwrap(), sorted.last().unwrap()); assert_eq!(heap.pop().unwrap(), sorted.pop().unwrap()); } } #[test] fn test_push() { let mut heap = BinaryHeap::from_vec(vec!(2i, 4, 9)); assert_eq!(heap.len(), 3); assert!(*heap.peek().unwrap() == 9); heap.push(11); assert_eq!(heap.len(), 4); assert!(*heap.peek().unwrap() == 11); heap.push(5); assert_eq!(heap.len(), 5); assert!(*heap.peek().unwrap() == 11); heap.push(27); assert_eq!(heap.len(), 6); assert!(*heap.peek().unwrap() == 27); heap.push(3); assert_eq!(heap.len(), 7); assert!(*heap.peek().unwrap() == 27); heap.push(103); assert_eq!(heap.len(), 8); assert!(*heap.peek().unwrap() == 103); } #[test] fn test_push_unique() { let mut heap = BinaryHeap::from_vec(vec!(box 2i, box 4, box 9)); assert_eq!(heap.len(), 3); assert!(*heap.peek().unwrap() == box 9); heap.push(box 11); assert_eq!(heap.len(), 4); assert!(*heap.peek().unwrap() == box 11); heap.push(box 5); assert_eq!(heap.len(), 5); assert!(*heap.peek().unwrap() == box 11); heap.push(box 27); assert_eq!(heap.len(), 6); assert!(*heap.peek().unwrap() == box 27); heap.push(box 3); assert_eq!(heap.len(), 7); assert!(*heap.peek().unwrap() == box 27); heap.push(box 103); assert_eq!(heap.len(), 8); assert!(*heap.peek().unwrap() == box 103); } #[test] fn test_push_pop() { let mut heap = BinaryHeap::from_vec(vec!(5i, 5, 2, 1, 3)); assert_eq!(heap.len(), 5); assert_eq!(heap.push_pop(6), 6); assert_eq!(heap.len(), 5); assert_eq!(heap.push_pop(0), 5); assert_eq!(heap.len(), 5); assert_eq!(heap.push_pop(4), 5); assert_eq!(heap.len(), 5); assert_eq!(heap.push_pop(1), 4); assert_eq!(heap.len(), 5); } #[test] fn test_replace() { let mut heap = BinaryHeap::from_vec(vec!(5i, 5, 2, 1, 3)); assert_eq!(heap.len(), 5); assert_eq!(heap.replace(6).unwrap(), 5); assert_eq!(heap.len(), 5); assert_eq!(heap.replace(0).unwrap(), 6); assert_eq!(heap.len(), 5); assert_eq!(heap.replace(4).unwrap(), 5); assert_eq!(heap.len(), 5); assert_eq!(heap.replace(1).unwrap(), 4); assert_eq!(heap.len(), 5); } fn check_to_vec(mut data: Vec) { let heap = BinaryHeap::from_vec(data.clone()); let mut v = heap.clone().into_vec(); v.sort(); data.sort(); assert_eq!(v, data); assert_eq!(heap.into_sorted_vec(), data); } #[test] fn test_to_vec() { check_to_vec(vec!()); check_to_vec(vec!(5i)); check_to_vec(vec!(3i, 2)); check_to_vec(vec!(2i, 3)); check_to_vec(vec!(5i, 1, 2)); check_to_vec(vec!(1i, 100, 2, 3)); check_to_vec(vec!(1i, 3, 5, 7, 9, 2, 4, 6, 8, 0)); check_to_vec(vec!(2i, 4, 6, 2, 1, 8, 10, 3, 5, 7, 0, 9, 1)); check_to_vec(vec!(9i, 11, 9, 9, 9, 9, 11, 2, 3, 4, 11, 9, 0, 0, 0, 0)); check_to_vec(vec!(0i, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10)); check_to_vec(vec!(10i, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0)); check_to_vec(vec!(0i, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 0, 0, 1, 2)); check_to_vec(vec!(5i, 4, 3, 2, 1, 5, 4, 3, 2, 1, 5, 4, 3, 2, 1)); } #[test] fn test_empty_pop() { let mut heap = BinaryHeap::::new(); assert!(heap.pop().is_none()); } #[test] fn test_empty_peek() { let empty = BinaryHeap::::new(); assert!(empty.peek().is_none()); } #[test] fn test_empty_replace() { let mut heap = BinaryHeap::::new(); assert!(heap.replace(5).is_none()); } #[test] fn test_from_iter() { let xs = vec!(9u, 8, 7, 6, 5, 4, 3, 2, 1); let mut q: BinaryHeap = xs.iter().rev().map(|&x| x).collect(); for &x in xs.iter() { assert_eq!(q.pop().unwrap(), x); } } #[test] fn test_drain() { let mut q: BinaryHeap<_> = [9u, 8, 7, 6, 5, 4, 3, 2, 1].iter().cloned().collect(); assert_eq!(q.drain().take(5).count(), 5); assert!(q.is_empty()); } }