gentoo-overlay/dev-haskell/psqueues/metadata.xml

<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE pkgmetadata SYSTEM "https://www.gentoo.org/dtd/metadata.dtd">
<pkgmetadata>
	<maintainer type="project">
		<email>haskell@gentoo.org</email>
		<name>Gentoo Haskell</name>
	</maintainer>
	<longdescription>
		The psqueues package provides
		&lt;https://en.wikipedia.org/wiki/Priority_queue Priority Search Queues&gt; in
		three different flavors.
		
		* @OrdPSQ k p v@, which uses the @Ord k@ instance to provide fast insertion,
		deletion and lookup. This implementation is based on Ralf Hinze's
		&lt;http://citeseer.ist.psu.edu/hinze01simple.html A Simple Implementation Technique for Priority Search Queues&gt;.
		Hence, it is similar to the
		&lt;http://hackage.haskell.org/package/PSQueue PSQueue&gt; library, although it is
		considerably faster and provides a slightly different API.
		
		* @IntPSQ p v@ is a far more efficient implementation. It fixes the key type
		to @Int@ and uses a &lt;https://en.wikipedia.org/wiki/Radix_tree radix tree&gt;
		(like @IntMap@) with an additional min-heap property.
		
		* @HashPSQ k p v@ is a fairly straightforward extension of @IntPSQ@: it
		simply uses the keys' hashes as indices in the @IntPSQ@. If there are any
		hash collisions, it uses an @OrdPSQ@ to resolve those. The performance of
		this implementation is comparable to that of @IntPSQ@, but it is more widely
		applicable since the keys are not restricted to @Int@, but rather to any
		@Hashable@ datatype.
		
		Each of the three implementations provides the same API, so they can be used
		interchangeably. The benchmarks show how they perform relative to one
		another, and also compared to the other Priority Search Queue
		implementations on Hackage:
		&lt;http://hackage.haskell.org/package/PSQueue PSQueue&gt;
		and
		&lt;http://hackage.haskell.org/package/fingertree-psqueue fingertree-psqueue&gt;.
		
		&lt;&lt;http://i.imgur.com/KmbDKR6.png&gt;&gt;
		
		&lt;&lt;http://i.imgur.com/ClT181D.png&gt;&gt;
		
		Typical applications of Priority Search Queues include:
		
		* Caches, and more specifically LRU Caches;
		
		* Schedulers;
		
		* Pathfinding algorithms, such as Dijkstra's and A*.
	</longdescription>
</pkgmetadata>