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.
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Release files for pybloom-live 4.0.0
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| File | Size | Uploaded | |
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| pybloom_live-4.0.0.tar.gz | 10.1 kB | Details |
Release files / pybloom_live-4.0.0.tar.gz
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