This crate implements a Priority Queue with a function to change the priority of an object.
Priority and items are stored in an IndexMap
and the queue is implemented as a Heap of indexes.
Please read the API documentation here
To use this crate, simply add the following string to your Cargo.toml
:
priority-queue = "2.0.0"
or use the command cargo add priority-queue
Version numbers follow the semver convention.
Then use the data structure inside your Rust source code as in the following Example.
Remember that, if you need serde support, you should compile using --features serde
.
use priority_queue::PriorityQueue;
fn main() {
let mut pq = PriorityQueue::new();
assert!(pq.is_empty());
pq.push("Apples", 5);
pq.push("Bananas", 8);
pq.push("Strawberries", 23);
assert_eq!(pq.peek(), Some((&"Strawberries", &23)));
for (item, _) in pq.into_sorted_iter() {
println!("{}", item);
}
}
By default, the highest priority element will be extracted first. The order can be easily reversed using the standard wrapper Reverse<T>
.
use priority_queue::PriorityQueue;
use std::cmp::Reverse;
fn main() {
let mut pq = PriorityQueue::new();
assert!(pq.is_empty());
pq.push("Apples", Reverse(5));
pq.push("Bananas", Reverse(8));
pq.push("Strawberries", Reverse(23));
assert_eq!(pq.peek(), Some((&"Apples", &Reverse(5))));
for (item, _) in pq.into_sorted_iter() {
println!("{}", item);
}
}
You can use custom BuildHasher for the underlying IndexMap and therefore achieve better performance. For example you can create the queue with the speedy FxHash hasher:
use hashbrown::hash_map::DefaultHashBuilder;
let mut pq = PriorityQueue::<_, _, DefaultHashBuilder>::with_default_hasher();
Attention: FxHash does not offer any protection for dos attacks. This means that some pathological inputs can make the operations on the hashmap O(n^2). Use the standard hasher if you cannot control the inputs.
Some benchmarks have been run to compare the performances of this priority queue to the standard BinaryHeap, also using the FxHash hasher. On a Ryzen 9 3900X, the benchmarks produced the following results:
test benchmarks::priority_change_on_large_double_queue ... bench: 25 ns/iter (+/- 1)
test benchmarks::priority_change_on_large_double_queue_fx ... bench: 21 ns/iter (+/- 1)
test benchmarks::priority_change_on_large_queue ... bench: 15 ns/iter (+/- 0)
test benchmarks::priority_change_on_large_queue_fx ... bench: 11 ns/iter (+/- 0)
test benchmarks::priority_change_on_large_queue_std ... bench: 190,345 ns/iter (+/- 4,976)
test benchmarks::priority_change_on_small_double_queue ... bench: 26 ns/iter (+/- 0)
test benchmarks::priority_change_on_small_double_queue_fx ... bench: 20 ns/iter (+/- 0)
test benchmarks::priority_change_on_small_queue ... bench: 15 ns/iter (+/- 0)
test benchmarks::priority_change_on_small_queue_fx ... bench: 10 ns/iter (+/- 0)
test benchmarks::priority_change_on_small_queue_std ... bench: 1,694 ns/iter (+/- 21)
test benchmarks::push_and_pop ... bench: 31 ns/iter (+/- 0)
test benchmarks::push_and_pop_double ... bench: 31 ns/iter (+/- 0)
test benchmarks::push_and_pop_double_fx ... bench: 24 ns/iter (+/- 1)
test benchmarks::push_and_pop_fx ... bench: 26 ns/iter (+/- 0)
test benchmarks::push_and_pop_min_on_large_double_queue ... bench: 101 ns/iter (+/- 2)
test benchmarks::push_and_pop_min_on_large_double_queue_fx ... bench: 98 ns/iter (+/- 0)
test benchmarks::push_and_pop_on_large_double_queue ... bench: 107 ns/iter (+/- 2)
test benchmarks::push_and_pop_on_large_double_queue_fx ... bench: 106 ns/iter (+/- 2)
test benchmarks::push_and_pop_on_large_queue ... bench: 84 ns/iter (+/- 1)
test benchmarks::push_and_pop_on_large_queue_fx ... bench: 78 ns/iter (+/- 2)
test benchmarks::push_and_pop_on_large_queue_std ... bench: 71 ns/iter (+/- 1)
test benchmarks::push_and_pop_std ... bench: 4 ns/iter (+/- 0)
The priority change on the standard queue was obtained with the following:
pq = pq.drain().map(|Entry(i, p)| {
if i == 50_000 {
Entry(i, p/2)
} else {
Entry(i, p)
}
}).collect()
The interpretation of the benchmarks is that the data structures provided by this crate is generally slightly slower than the standard Binary Heap.
On small queues (<10000 elements), the change_priority function, obtained on the standard Binary Heap with the code above, is way slower than the one provided by PriorityQueue
and DoublePriorityQueue
.
With the queue becoming bigger, the operation takes almost the same amount of time on PriorityQueue
and DoublePriorityQueue
, while it takes more and more time for the standard queue.
It also emerges that the ability to arbitrarily pop the minimum or maximum element comes with a cost, that is visible in all the operations on DoublePriorityQueue
, that are slower then the corresponding operations executed on the PriorityQueue
.
Feel free to contribute to this project with pull requests and/or issues.
All contribution shall be under a license compatible with the GNU LGPL version 3 or any later version and with the MPL version 2.0.
- 2.1.1 Bug fix: #56
- 2.1.0 Implement
drain
andreserve
variations - 2.0.3 Some licensing-related housekeeping
- 2.0.2 Fix docs.rs build
- 2.0.1 Documentation improvements
- 2.0.0 This release contains breaking changes
- Some methods now require the trait bound
H: BuildHasher
. This change will likely have a small impact or none. - The standard library support is no longer auto-detected. The feature "std" is included in the default feature set, or else can be enabled like any other Cargo feature. Users that need to support
no_std
targets will have to disable default features.
- Some methods now require the trait bound
- 1.4.0 Improve
shrink_to_fit
to also shrink the internal IndexMap (#50) - 1.3.2 Bug fix in the
log2_fast
internal function - 1.3.1 Bug fix: #42
- 1.3.0 Return bool from
change_priority_by
(Merged #41) - 1.2.3 Further performance optimizations (mainly on
DoublePriorityQueue
) - 1.2.2 Performance optimizations
- 1.2.1 Bug fix: #34
- 1.2.0 Implement DoublePriorityQueue data structure
- 1.1.1 Convert documentation to Markdown
- 1.1.0 Smooth
Q: Sized
requirement on some methods (fix #32) - 1.0.5 Bug fix: #28
- 1.0.4 Bug fix: #28
- 1.0.3 Bug fix: #26
- 1.0.2 Added documentation link to Cargo.toml so the link is shown in the results page of crates.io
- 1.0.1 Documentation
- 1.0.0 This release contains breaking changes!
-
From
andFromIterator
now accept custom hashers -- Breaking: every usage offrom
andfrom_iter
must specify some type to help the type inference. To use the default hasher (RandomState
), often it will be enough to add something likelet pq: PriorityQueue<_, _> = PriorityQueue::from...
or you can add a type definition like
type Pq<I, P> = PriorityQueue<I, P>
and then use
Pq::from()
orPq::from_iter()
-
Support no-std architectures
-
Add a method to remove elements at arbitrary positions
-
Remove
take_mut
dependency -- Breaking:change_priority_by
signature has changed. Now it takes a priority_setterF: FnOnce(&mut P)
. If you want you can use the unsafetake_mut
yourself or also usestd::mem::replace
-
- 0.7.0 Implement the
push_increase
andpush_decrease
convenience methods. - 0.6.0 Allow the usage of custom hasher
- 0.5.4 Prevent panic on extending an empty queue
- 0.5.3 New implementation of the
Default
trait avoids the requirement thatP: Default
- 0.5.2 Fix documentation formatting
- 0.5.1 Add some documentation for
iter_mut()
- 0.5.0 Fix #7 implementing the
iter_mut
features - 0.4.5 Fix #6 for
change_priority
andchange_priority_by
- 0.4.4 Fix #6
- 0.4.3 Fix #4 changing the way
PriorityQueue
serializes. Note that old serializedPriorityQueue
s may be incompatible with the new version. The API should not be changed instead. - 0.4.2 Improved performance using some unsafe code in the implementation.
- 0.4.1 Support for
serde
when compiled with--features serde
.serde
marked as optional andserde-test
as dev-dipendency. Now compiling the crate won't download and compile alsoserde-test
, neitherserde
if not needed. - 0.4.0 Support for serde when compiled with
cfg(serde)
- 0.3.1 Fix #3
- 0.3.0 Implement PartialEq and Eq traits