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Python implementation of automata.

Project description

=========
Pythomata
=========


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Python implementation of automata.


* Free software: MIT license
* Documentation: https://pythomata.readthedocs.io.

Install
-------

.. code-block:: console

$ wget http://ftp.it.debian.org/debian/pool/main/g/graphviz/graphviz_2.38.0-17_amd64.deb
$ sudo dpkg -i graphviz_2.38.0-1~saucy_amd64.deb
$ sudo apt-get install -f

How to use
--------

* Define an automaton:

.. code-block:: python

a, b, c = Symbol("a"), Symbol("b"), Symbol("c")
alphabet = Alphabet({a, b, c})
states = frozenset({"s1", "s2", "s3"})
initial_state = "s1"
accepting_states = frozenset({"s3"})
transition_function = {
"s1": {
b : "s1",
a : "s2"
},
"s2": {
a : "s3",
b : "s1"
},
"s3":{
c : "s3"
}
}

dfa = DFA(alphabet, states, initial_state, accepting_states, transition_function)

* Test word acceptance:

.. code-block:: python

# a word is a list of symbols
word = [b, b, b, a, b, c]

dfa.word_acceptance(word) # True

# without the last symbol c, the final state is not reached
dfa.word_acceptance(word[:-1]) # False

* Operations such as minimization and trimming:

.. code-block:: python


dfa_minimized = dfa.minimize()
dfa_trimmed = dfa.trim()

* Print the automata:

.. code-block:: python

filepath = "./my_awesome_automaton"
dfa.minimize().trim().to_dot(filepath)

The output in .svg format is the following:

.. image:: https://github.com/MarcoFavorito/pythomata/tree/master/docs/my_awesome_automaton.svg


Features
--------

* Basic DFA and NFA support;
* Algorithms for DFA minimization and trimming;
* Algorithm for NFA determinization;
* Print automata in SVG format.

Credits
-------

This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage


=======
History
=======

0.1.0 (2018-03-13)
------------------

* First release on PyPI.

0.1.1 (2018-03-15)
------------------

* Basic DFA and NFA support;
* Algorithms for DFA minimization and trimming;
* Algorithm for NFA determinization.

0.1.2 (2018-03-16)
------------------

* Minor bug fixes

0.1.3 (2018-03-16)
------------------

* Changes in word acceptance procedure for DFAs

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