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A Python package implementing automata.

Project description


Python implementation of automata theory.


  • from PyPI:

    pip install pythomata
    pip install pythomata=0.3.0a  # for the pre-release.
  • or, from source (master branch):

    pip install git+
  • or, clone the repository and install:

    git clone htts://
    cd pythomata
    pip install .

How to use

  • Define an automaton:
from pythomata import SimpleDFA
alphabet = {"a", "b", "c"}
states = {"s1", "s2", "s3"}
initial_state = "s1"
accepting_states = {"s3"}
transition_function = {
    "s1": {
        "b" : "s1",
        "a" : "s2"
    "s2": {
        "a" : "s3",
        "b" : "s1"
        "c" : "s3"
dfa = SimpleDFA(states, alphabet, initial_state, accepting_states, transition_function)
  • Test word acceptance:
# a word is a list of symbols
word = "bbbac"
dfa.accepts(word)        # True

# without the last symbol c, the final state is not reached
dfa.accepts(word[:-1])   # False
  • Operations such as minimization and trimming:
dfa_minimized = dfa.minimize()
dfa_trimmed = dfa.trim()
graph = dfa.minimize().trim().to_graphviz()

To print the automaton:


For that you will need to install Graphviz. Please look at their download page for detailed instructions depending on your system.

The output looks like the following:


  • Basic DFA and NFA support;
  • Algorithms for DFA minimization and trimming;
  • Algorithm for NFA determinization;
  • Translate automata into Graphviz objects.


To run the tests:


To run only the code style checks:

tox -e flake8


To build the docs:

mkdocs build

To view documentation in a browser

mkdocs serve

and then go to http://localhost:8000


Copyright 2018-2020 WhiteMech


0.1.0 (2019-04-13)

  • Basic support for DFAs and NFAs.
  • Algorithms for DFA minimization and trimming.
  • Algorithm for NFA determinization.

0.2.0 (2019-09-30)

  • Refactoring of the repository

Project details

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pythomata-0.3.0a0.tar.gz (132.0 kB view hashes)

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