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Bloom filter: A Probabilistic data structure

Project Description

This bloom filter is forked from pybloom, and its tightening ratio is changed to 0.9, and this ration is consistently used. Choosing r around 0.8 - 0.9 will result in better average space usage for wide range of growth, therefore the default value of model is set to LARGE_SET_GROWTH. This is a Python implementation of the bloom filter probabilistic data structure. The module also provides a Scalable Bloom Filter that allows a bloom filter to grow without knowing the original set size.

Release History

Release History

This version
History Node

2.3.1

History Node

2.2.0

History Node

2.1.0

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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
pybloom_live-2.3.1.tar.gz (6.7 kB) Copy SHA256 Checksum SHA256 Source Aug 11, 2017

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