Pure Python Bloom Filter module
A pure python bloom filter (low storage requirement, probabilistic set datastructure) is provided. It is known to work on CPython 2.x, CPython 3.x, Pypy and Jython.
Includes mmap, in-memory and disk-seek backends.
The user specifies the desired maximum number of elements and the desired maximum false positive probability, and the module calculates the rest.
from bloom_filter import BloomFilter # instantiate BloomFilter with custom settings, # max_elements is how many elements you expect the filter to hold. # error_rate defines accuracy; You can use defaults with # `BloomFilter()` without any arguments. Following example # is same as defaults: bloom = BloomFilter(max_elements=10000, error_rate=0.1) # Test whether the bloom-filter has seen a key: assert "test-key" in bloom is False # Mark the key as seen bloom.add("test-key") # Now check again assert "test-key" in bloom is True
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