https://github.com/dcso/flor

A Python implementation of our efficient Bloom filter library.
https://github.com/dcso/flor

Last synced: 6 months ago
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A Python implementation of our efficient Bloom filter library.

• Host: GitHub
• URL: https://github.com/dcso/flor
• Owner: DCSO
• License: other
• Created: 2017-07-03T10:43:35.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2020-02-27T12:44:29.000Z (over 5 years ago)
• Last Synced: 2024-05-30T00:04:05.412Z (about 1 year ago)
• Language: Python
• Size: 25.4 KB
• Stars: 29
• Watchers: 5
• Forks: 4
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Flor - A Bloom filter implementation in Python

[![Build Status](https://travis-ci.org/DCSO/flor.svg?branch=master)](https://travis-ci.org/DCSO/flor)

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

[Go Bloom filter implementation](https://github.com/DCSO/bloom).

# 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).