Leftrb is a Left-Leaning Red-Black (LLRB) implementation of 2–3 balanced binary
Leftrb is a Left-Leaning Red-Black (LLRB) implementation of 2–3 balanced binary search trees in Python.
This is a straightforward port of the Java code presented by Robert Sedgewick in [his paper]((http://www.cs.princeton.edu/~rs/talks/LLRB/LLRB.pdf) and in the book [Algorithms, 4th Edition](http://algs4.cs.princeton.edu/home/), which is written by Robert Sedgewick and Kevin Wayne. By their permission, the [original GPL v3 licensed Java code](http://www.cs.princeton.edu/~rs/talks/LLRB/Java/RedBlackBST.java) is licensed as LGPL v3, and ported to Python.
A balanced binary search tree (BBST) maintains elements in sorted order under dynamic updates (inserts and deletes) and can support various order-specific queries.
Red-black trees are the de facto standard BBST algorithms, and are the underlying data structure for symbol-table implementations within C++, Java, Python, BSD Unix, Linux and many other modern systems.
All red–black trees are based on implementing 2-3 or 2-3-4 trees within a binary tree, using red links to bind together internal nodes into 3-nodes or 4-nodes. Search, insert and delete operations are O(log n) and space requirements are O(n).
However, many traditional implementations have lots of repetitive code on the symmetric branches of rotation and deletion operations. So they are not easy to reason about and augment with other properties, which is what BBST’s are often used for: They are used to implement other common data structures like Priority Queues and Interval Trees.
The LLRB method of implementing 2-3 trees is a recent improvement over the traditional implementation — it maintains an additional invariant that all red links must lean left except during inserts and deletes. Because of this, they can be implemented by adding just a few lines of code to standard BST algorithms.
The LLRB tree is based on combining three ideas:
The LLRB approach was discovered relatively recently (in 2008) by Robert Sedgewick of Princeton University. For original code and more information read the paper “Left-leaning Red-Black Trees” at [http://www.cs.princeton.edu/~rs/talks/LLRB/LLRB.pdf](http://www.cs.princeton.edu/~rs/talks/LLRB/LLRB.pdf)
From Python package index:
pip install leftrb
or from Github source:
git clone https://github.com/peterhil/leftrb.git cd leftrb python setup.py install