This example implements a Bloom filter in Python, a probabilistic data structure for fast membership testing. Items are added using multiple hash functions that set bits in a fixed-size array. Membership checks return definitely not present or possibly present, with false positives possible. The source code is part of the 127 algorithms collection.
What is the Gagniuc/The-Bloom-filter GitHub project? Description: "This example implements a Bloom filter in Python, a probabilistic data structure for fast membership testing. Items are added using multiple hash functions that set bits in a fixed-size array. Membership checks return definitely not present or possibly present, with false positives possible. The source code is part of the 127 algorithms collection.". Written in Python. Explain what it does, its main use cases, key features, and who would benefit from using it.
Question is copied to clipboard — paste it after the AI opens.
Clone via HTTPS
Clone via SSH
Download ZIP
Download master.zipReport bugs or request features on the The-Bloom-filter issue tracker:
Open GitHub Issues