Metadata-Version: 2.1
Name: ngram
Version: 4.0.3
Summary: A `set` subclass providing fuzzy search based on N-grams.
Home-page: https://github.com/gpoulter/python-ngram
Author: Graham Poulter, Michel Albert
Maintainer: Graham Poulter
License: LGPL3
Download-URL: http://pypi.python.org/pypi/ngram
Project-URL: Documentation, https://python-ngram.readthedocs.io/en/latest/
Keywords: ngram set string text similarity
Platform: any
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 or later (LGPLv3+)
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)
Classifier: License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)
Classifier: Natural Language :: English
Classifier: Topic :: Text Processing
Classifier: Topic :: Text Processing :: Indexing
Classifier: Topic :: Text Processing :: Linguistic
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.0
Description-Content-Type: text/x-rst
License-File: COPYING
License-File: COPYING.LESSER

The NGram class extends the Python 'set' class with efficient
fuzzy search for members by means of an N-gram similarity measure.
It also has static methods to compare a pair of strings.

The N-grams are character based not word-based, and the class does not
implement a language model, merely searching for members by string similarity.

See the `documentation`_, which includes a tutorial and release notes.

Use the `GitHub issue tracker`_ to report issues.

Installation
============

To install python-ngram from `PyPI`_::

   pip install ngram

How does it work?
=================

The set stores arbitrary items, but for non-string items a `key` function
(such as `str`) must be specified to provide a string represenation.  The key
function can also be used to normalise string items (e.g. lower-casing) prior
to N-gram indexing.

To index a string it pads the string with a specified dummy character, then
splits it into overlapping substrings of N (default N=3) characters in length
and associates each N-gram to the items that use it.

To find items similar to a query string, it splits the query into N-grams,
collects all items sharing at least one N-gram with the query,
and ranks the items by score based on the ratio of shared to unshared
N-grams between strings.

History
=======

In 2007, Michel Albert (exhuma) wrote the python-ngram module based on Perl's
`String::Trigram`_ module by Tarek Ahmed, and committed the code for 2.0.0b2 to
a now-disused `Sourceforge`_ subversion repo.

Since late 2008, Graham Poulter has maintained python-ngram, initially refactoring
it to build on the `set` class, and also adding features, documentation, tests,
performance improvements and Python 3 support.

Development
===========

Development takes place on `Github`_.  On checking out the repo run `tox` to build
the Sphinx documentation and run tests.  Run `pip install -e .` to install the module 
in editable mode, inside a virtualenv.

.. _documentation: https://python-ngram.readthedocs.io/en/latest/
.. _GitHub: http://github.com/gpoulter/python-ngram
.. _GitHub issue tracker: https://github.com/gpoulter/python-ngram/issues
.. _PyPI: http://pypi.python.org/pypi/ngram
.. _String::Trigram: http://search.cpan.org/dist/String-Trigram/
.. _Sourceforge: https://sourceforge.net/projects/python-ngram/


