Skip to main content
This is a pre-production deployment of Warehouse. Changes made here affect the production instance of PyPI (
Help us improve Python packaging - Donate today!

A spelling similarity measure for cognate identification.

Project Description

spsim is a Python 3 module that implements a spelling similarity measure for identifying cognates across languages, taking into account spelling differences that are characteristic of each language pair, as described in [Gomes2011].

Note: in the examples below, $ denotes the Bash prompt and a Linux, MacOs or similar *nix environment is assumed.

Install as usual:

$ pip3 install spsim

Example command line usage:

$ # first let's get some pairs of words that may be cognates:
$ wget
$ cat maybe_enpt.txt
pharmacy    farmácia
arithmetic  aritmética

$ # If we don't give any example cognates, SpSim will be equivalent to
$ #             1 - edit_distance / max_len_of_strings
$ # Note that by default spsim matches accentuated characters, i.e. a == á
$ echo "" > empty.txt
$ spsim empty.txt maybe_enpt.txt
pharmacy    farmácia    0.5
arithmetic  aritmética  0.8

$ now let's get some example cognates:
$ wget
$ cat examples_enpt.txt
alcohol     álcool
alpha       alfa
anomaly     anomalia
mathematics matemática
methodology metodologia
metric      métrica
morphine    morfina
photos      fotos

$ # by giving these examples to spsim, it will learn to ignore certain differences:
$ spsim examples_enpt.txt maybe_enpt.txt
pharmacy    farmácia    1.0
arithmetic  aritmética  1.0
[Gomes2011]Measuring Spelling Similarity for Cognate Identification, Luís Gomes and Gabriel Pereira Lopes in Progress in Artificial Intelligence, 15th Portuguese Conference in Artificial Intelligence, EPIA 2011, Lisboa, Portugal, October 2011,

Release History

This version
History Node


History Node


History Node


History Node


History Node


History Node


History Node


History Node


History Node


Download Files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

File Name & Hash SHA256 Hash Help Version File Type Upload Date
(8.6 kB) Copy SHA256 Hash SHA256
py3 Wheel Jul 26, 2017
(6.0 kB) Copy SHA256 Hash SHA256
Source Jul 26, 2017

Supported By

WebFaction WebFaction Technical Writing Elastic Elastic Search Pingdom Pingdom Monitoring Dyn Dyn DNS Sentry Sentry Error Logging CloudAMQP CloudAMQP RabbitMQ Heroku Heroku PaaS Kabu Creative Kabu Creative UX & Design Fastly Fastly CDN DigiCert DigiCert EV Certificate Rackspace Rackspace Cloud Servers DreamHost DreamHost Log Hosting