Metadata-Version: 1.0
Name: leftrb
Version: 0.1.2
Summary: 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 `code`_ presented
by Robert Sedgewick in `his paper`_.

`README`_ at Github.

.. _code: http://www.cs.princeton.edu/~rs/talks/LLRB/Java/RedBlackBST.java
.. _`his paper`: http://www.cs.princeton.edu/~rs/talks/LLRB/LLRB.pdf
.. _README: https://github.com/peterhil/leftrb/blob/master/README.md

Home-page: https://github.com/peterhil/leftrb
Author: Peter Hillerström
Author-email: peter.hillerstrom@gmail.com
License: MIT License
Description: # Leftrb/LLRB
        
        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.
        
        ## Overview
        
        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:
        
        - Use a recursive implementation.
        - Require that all 3-nodes lean left.
        - Perform rotations on the way up the tree (after the recursive calls).
        
        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)
        
        ## Installation
        
        From Python package index:  
        
            pip install leftrb
        
        or from Github source:  
        
            git clone https://github.com/peterhil/leftb.git
            cd leftrb 
            python setyp.py install
        
        ## About
        
        Leftrb/LLRB was written by [Peter Hillerström](http://composed.nu/peterhil/).  
        Follow me on Twitter [@peterhil](http://www.twitter.com/peterhil)!
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Other Environment
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 or later (LGPLv3+)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Other/Nonlisted Topic
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries :: Python Modules
