Awesome

Flor - A Bloom filter implementation in Python

Flor implements a Bloom filter class that is fully compatible with our Go Bloom filter implementation.

Requirements

Flor is compatible with Python 2.7+ and Python 3.2+ as well as PyPy2/3 and does not require any non-standard modules.

Installation

Flor can be installed via PyPi/pip:

pip install flor

Alternatively, you can install it from source:

git clone https://github.com/DCSO/flor.git
cd flor

#add "sudo" if you're not in a virtual environment
python setup.py install

Basics

A Bloom filter has a capacity n and a false positive probability p that gives the probability that a filter filled to capacity (i.e. with n distinct values inserted) will return True for an element that is not in the filter.

Usage

Creating a new Bloom filter:

from flor import BloomFilter

bf = BloomFilter(n=100000, p=0.001)

bf.add(b"foo")
bf.add(b"bar")
bf.add(b"baz")

b"baz" in bf #returns True
b"nope" in bf #returns False

Writing a Bloom filter to a file:

bf = BloomFilter()
with open('test.bloom', 'wb') as f:
    bf.write(f)

Reading a Bloom filter from a file:

bf = BloomFilter()
with open('test.bloom', 'rb') as f:
    bf.read(f)

The binary format of the filter is compatible with that generated by our Go library, so you can use the two interchangeably.

License

Flor is licensed under the BSD 3 Clause license (see LICENSE).