treap: Efficient implementation of the implicit treap data structure

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Efficient implementation of the implicit treap data structure. Use this data structure if you want dynamic arrays with fast operations on segments.

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0.0.0.0

Versions [RSS]	0.0.0.0
Change log	CHANGELOG.md
Dependencies	base (>=4.11 && <4.13), deepseq (>=1.4 && <1.5), mersenne-random-pure64 (>=0.2.2 && <0.3) [details]
Tested with	ghc ==8.4.4, ghc ==8.6.4
License	MPL-2.0
Copyright	2019-2021 Dmitrii Kovanikov
Author	Dmitrii Kovanikov
Maintainer	kovanikov@gmail.com
Revised	Revision 1 made by vrom911 at 2021-08-02T13:16:20Z
Category	Data Structures, Tree
Home page	https://github.com/chshersh/treap
Bug tracker	https://github.com/chshersh/treap/issues
Source repo	head: git clone https://github.com/chshersh/treap.git
Uploaded	by shersh at 2019-04-29T09:48:01Z
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Downloads	517 total (3 in the last 30 days)
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Status	Docs available [build log] Last success reported on 2019-04-29 [all 1 reports]

Readme for treap-0.0.0.0

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treap

Treap: tree logo

Efficient implementation of the implicit treap data structure.

What does this package provide?

This package implements a tree-like data structure called implicit treap. This data structure implements interface similar to random-access arrays, but with fast (logarithmic time complexity) insert/delete/split/merge/take/drop/rotate operations. In addition, treap allows you to specify and measure values of any monoids on a segment, like a sum of elements or minimal element on some contiguous part of the array.

When to use this package?

Use this package when you want the following operations to be fast:

Access elements by index.
Insert elements by index.
Delete elements by index.
Calculate monoidal operation (like sum, product, min, etc.) of all elements between two indices.
Call slicing operations like take or drop or split.

Below you can find the table of time complexity for all operations (where n is the size of the treap):

Operation	Time complexity	Description
`size`	`O(1)`	Get number of elements in the treap
`at`	`O(log n)`	Access by index
`insert`	`O(log n)`	Insert by index
`delete`	`O(log n)`	Delete by index
`query`	`O(log n)`	Measure monoid on the segment
`splitAt`	`O(log n)`	Split treap by index into two treaps
`merge`	`O(log n)`	Merge two treaps into a single one
`take`	`O(log n)`	Take first `i` elements of the treap
`drop`	`O(log n)`	Drop first `i` elements of the treap
`rotate`	`O(log n)`	Put first `i` elements to the end

The package also comes with nice pretty-printing!

ghci> t = fromList [1..5] :: RTreap (Sum Int) Int
ghci> prettyPrint t
   5,15:2
      ╱╲
     ╱  ╲
    ╱    ╲
   ╱      ╲
1,1:1   3,12:4
          ╱╲
         ╱  ╲
        ╱    ╲
      1,3:3 1,5:5

Alternatives

If you don't need to calculate monoidal operations, you may alternatively use Seq from the containers package as it provides more extended interface but doesn't allow to measure monoidal values on segments.

Acknowledgement

Icons made by Freepik from [www.flaticon.com](https://www.flaticon.com/) is licensed by CC 3.0 BY.