jaybaird/python-bloomfilter

Health v2 · maintenance only

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1618 stars · 321 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

pybloom is a Python module implementing Bloom Filters and Scalable Bloom Filters as a probabilistic set membership data structure. It grows filter capacity automatically based on false positive probability targets, following the Almeida et al. GLOBECOM 2007 paper.

Use cases

• check if an element is in a large set without storing it all
• build a scalable bloom filter that grows with the dataset
• avoid expensive lookups with a probabilistic membership test
• deduplicate items with a small memory footprint
• implement a spell checker or cache filter with controlled false positive rate

When to choose

• you need memory-efficient approximate set membership in pure Python
• you don't know the final set size in advance and want automatic scaling
• a small false positive rate is acceptable for your use case

When to avoid

• you need exact membership answers with zero false positives
• you need deletion support, which bloom filters don't provide
• you need a actively maintained or high-performance implementation for production systems

Facets

library · maturity maintenance

caching search-engine data-science databases developer-tools python cross-platform bloom-filter probabilistic-data-structure scalable-bloom-filter algorithms

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