BloomFilter

A Bloom Filter is a space-efficient probabilistic data structure. Presented solution is implemented in Python. Java implementation is available here. It contains few methods for generating independent hash functions:

• Double Hashing
• Triple Hashing
• Enhanced Double Hashing

All the approaches are described in "Bloom Filters in Probabilistic Verification" by Peter C. Dillinger and Panagiotis Manolios. The paper is available here.

Pre-requisites

Just run the following command:

pip3 install -r requirements.txt

Example

Using Bloom Filter with Double Hashing method:

filter = DoubleHashBloomFilter(0.001, 10)
filter.add("Test")
filter.might_contains("Test")