Flor implements a Bloom filter class that is fully compatible with our Go Bloom filter implementation.
Flor is compatible with Python 2.7+ and Python 3.2+ as well as PyPy2/3 and does not require any non-standard modules.
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
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.
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.
Flor is licensed under the BSD 3 Clause license (see LICENSE).