Python SciKit Sequitur

SciKit Sequitur_ is an Apache2 licensed Python module for inferring compositional hierarchies from sequences.

Sequitur detects repetition and factors it out by forming rules in a grammar. The rules can be composed of non-terminals, giving rise to a hierarchy. It is useful for recognizing lexical structure in strings, and excels at very long sequences. The Sequitur algorithm was originally developed by Craig Nevill-Manning and Ian Witten.

.. code-block:: python

from sksequitur import parse grammar = parse('hello hello') print(grammar) 0 -> 1 _ 1 1 -> h e l l o hello

SciKit Sequitur_ works on strings, lines, or any sequence of Python objects.

Features

• Pure-Python
• Developed on Python 3.10
• Tested on CPython 3.6, 3.7, 3.8, 3.9, 3.10
• Tested using GitHub Actions on Linux, Mac, and Windows

.. image:: https://github.com/grantjenks/scikit-sequitur/workflows/integration/badge.svg :target: http://www.grantjenks.com/docs/sksequitur/

Quickstart

Installing scikit-sequitur_ is simple with pip <http://www.pip-installer.org/>_::

$ pip install scikit-sequitur

You can access documentation in the interpreter with Python's built-in help function:

.. code-block:: python

import sksequitur help(sksequitur) # doctest: +SKIP

Tutorial

The scikit-sequitur_ module provides utilities for parsing sequences and understanding grammars.

.. code-block:: python

from sksequitur import parse print(parse('abcabc')) 0 -> 1 1 1 -> a b c abc

The parse function is a shortcut for Parser and Grammar objects.

.. code-block:: python

from sksequitur import Parser parser = Parser()

Feed works incrementally.

.. code-block:: python

parser.feed('ab') parser.feed('cab') parser.feed('c')

Parsers can be converted to Grammars.

.. code-block:: python

from sksequitur import Grammar grammar = Grammar(parser.tree) print(grammar) 0 -> 1 1 1 -> a b c abc

Grammars are keyed by Productions.

.. code-block:: python

from sksequitur import Production grammar[Production(0)] [Production(1), Production(1)]

Mark symbols can be used to store metadata about a sequence. The mark symbol is printed as a pipe character "|".

.. code-block:: python

from sksequitur import Mark mark = Mark() mark Mark() print(mark) |

Attributes can be added to mark symbols using keyword arguments.

.. code-block:: python

mark = Mark(kind='start', name='foo.py') mark Mark(kind='start', name='foo.py') mark.kind 'start'

Mark symbols can not be made part of a rule.

.. code-block:: python

parser = Parser() parser.feed('ab') parser.feed([Mark()]) parser.feed('cab') parser.feed([Mark()]) parser.feed('c') grammar = Grammar(parser.tree) print(grammar) 0 -> 1 | c 1 | c 1 -> a b ab

Reference

• scikit-sequitur Documentation_
• scikit-sequitur at PyPI_
• scikit-sequitur at GitHub_
• scikit-sequitur Issue Tracker_

.. _scikit-sequitur Documentation: http://www.grantjenks.com/docs/sksequitur/ .. _scikit-sequitur at PyPI: https://pypi.python.org/pypi/scikit-sequitur/ .. _scikit-sequitur at GitHub: https://github.com/grantjenks/scikit-sequitur/ .. _scikit-sequitur Issue Tracker: https://github.com/grantjenks/scikit-sequitur/issues/

License

Copyright 2021 Grant Jenks

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

.. _SciKit Sequitur: http://www.grantjenks.com/docs/sksequitur/ .. _scikit-sequitur: http://www.grantjenks.com/docs/sksequitur/