polyleven 0.11.0
A fast C-implemented library for Levenshtein distance
Requires Python: >=3.8
Keywords: Levenshtein distance

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

:License: MIT License

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

polyleven is a Pythonic Levenshtein distance library that:

- Is **fast** regardless of input types, and hence can be applied to
  both short (like English words) and long inputs (like DNA sequences).

- Is **stand-alone** with no external dependencies.

- Is distributed under the **MIT License**, hence can be used freely
  in private projects.

2. How to install
=================

The official package is available on PyPI::

  $ pip install polyleven

3. 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`.

4. 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
============ =====  =====  =====  =====  =====  =====  ======

4.3. 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)