HOPS - Highly Optimized Pythonic Structures
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The goal of this project's is to build a collection of efficient and
practical data structures (in C), and then wrap'em up using Cython to
obtain lightning-speed data structures at the Python level.  I am now
taking my first glance at the Cython docs and the wrapping process
looks promisingly easy.

Most of the C code is currently derived by the VIS GLU library
(licensing issues not clear here, but I think the package should be
more or less under a BSD-like license. My goal would be to place
everything under LGPL so if needed, I will end up rewriting my own
implementation of non-LGPL compatible pieces of code.

The library should be equipped with a complete test suite covering
both the C and Python interfaces.

A reasonable set of data structures would be:

1. AVL self-balancing trees (done)
2. Dynamic Arrays
3. Hash tables
4. SLists, DLists, Stacks and Queues
5. Priority Queues
6. Graphs (both Directed and Undirected)

Future structures

7. BDDs
8. ... who knows?

All of those structures should be fully available both at the C level
and, most importantly, at the Python level.