polyleven

============================================== Polyleven -- Fast Pythonic Levenshtein Library

:Website: https://ceptord.net/ :Latest Release: v0.8 (2022-10-02) :License: MIT License

1. Introduction ===============

polyleven is a Pythonic Levenshtein distance library that:

• Is fast independent of input types, and hence can be used for both short (like English words) and long input types (like DNA sequences).

• Can be used readily in a manner not covered by restrictive licenses such as GPL, hence can be used freely in private codes.

• Supports Python 3.x.

1. How to install =================

The official package is available on PyPI::

$ pip install polyleven

1. How to use =============

Polyleven provides a single interface function levenshtein(). You can use this function to measure the similarity of two strings.

from polyleven import levenshtein levenshtein('aaa', 'ccc') 3

If you only care about distances under a certain threshold, you can pass the max threshold to the third argument.

levenshtein('acc', 'ccc', 1) 1 levenshtein('aaa', 'ccc', 1) 2

In general, you can gain a noticeable speed boost with threshold :math:k < 3.

1. Benchmark ============

4.1 English Words

To compare Polyleven with other Pythonic edit distance libraries, a million word pairs was generated from SCOWL_.

.. _SCOWL: http://wordlist.aspell.net/

Each library was measured how long it takes to evaluate all of these words. The following table summarises the result:

============================== ============ ================ Function Name TIME[sec] SPEED[pairs/s] ============================== ============ ================ edlib 4.763 208216 editdistance 1.943 510450 jellyfish.levenshtein_distance 0.722 1374081 distance.levenshtein 0.623 1591396 Levenshtein.distance 0.500 1982764 polyleven.levenshtein 0.431 2303420 ============================== ============ ================

4.2. Longer Inputs

To evaluate the efficiency for longer inputs, I created 5000 pairs of random strings of size 16, 32, 64, 128, 256, 512 and 1024.

Each library was measured how fast it can process these entries. [#fn1]_

============ ===== ===== ===== ===== ===== ===== ====== Library N=16 N=32 N=64 N=128 N=256 N=512 N=1024 ============ ===== ===== ===== ===== ===== ===== ====== edlib 0.040 0.063 0.094 0.205 0.432 0.908 2.089 editdistance 0.027 0.049 0.086 0.178 0.336 0.740 58.139 jellyfish 0.009 0.032 0.118 0.470 1.874 8.877 42.848 distance 0.007 0.029 0.109 0.431 1.726 6.950 27.998 Levenshtein 0.006 0.022 0.085 0.336 1.328 5.286 21.097 polyleven 0.003 0.005 0.010 0.043 0.149 0.550 2.109 ============ ===== ===== ===== ===== ===== ===== ======

3.3. List of Libraries

============ ======= ========================================== Library Version URL ============ ======= ========================================== edlib v1.2.1 https://github.com/Martinsos/edlib editdistance v0.4 https://github.com/aflc/editdistance jellyfish v0.5.6 https://github.com/jamesturk/jellyfish distance v0.1.3 https://github.com/doukremt/distance Levenshtein v0.12 https://github.com/ztane/python-Levenshtein polyleven v0.3 https://github.com/fujimotos/polyleven ============ ======= ==========================================

.. [#fn1] Measured using Python 3.5.3 on Debian Jessie with Intel Core i3-4010U (1.70GHz)