Fast Non-Standard Data Structures for Python

http://kmike.ru/python-data-structures/

by krat0sprakhar • 13 years ago

156 9 13 years ago

kmike.ru

cloudshoring• 13 years ago

Thanks for sharing!

jfb• 13 years ago

Very useful, thanks.

willvarfar• 13 years ago

Just a random anecdote: I've been badly burned by the heapq for timeouts; although I understand the advantages of the heap in general I think the Python library version is shot-down in practice due to being a purely-Python implementation. I moved to rbtree and suddenly my throughput shot up.

dalke• 13 years ago

Ever since Python 2.4, the heapq module has been written in C. It was only Python 2.3 which had the pure Python implementation.

I've used heapq for several of my projects, including one where I did extensive performance testing, and I haven't found it to be a problem.

z-factor• 13 years ago

I want to add that I've been using heapq for scheduling in every piece of software as well and it's never been a problem even in heavily loaded projects.

ch0wn• 13 years ago

bintrees is a fantastic package. There are even Cython-powered implementations that give a nice speed boost, if you need it.

sbrother• 13 years ago

I'd like to add scipy.spatial.cKDTree for really fast kd-trees. Just used it for a geospatial data analysis application (find the closest N facilities to a given point) and it blew the numpy and standard python alternatives out of the water in terms of speed.

kmike84• 13 years ago

Added to the list, thanks!

michaelhoffman• 13 years ago

This is a great resource to have. Thank you!

Fast Non-Standard Data Structures for Python

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