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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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Bloom filter: A Probabilistic data structure
We found that pybloom-live demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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