🤖 Pytomatas

📌 Version 1.1.4

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Pytomatas allows to simulate Acceptor Automata in the console with Python, implementing its characteristics using different definitions (mathematics included), with the following types:

• DFA (Deterministic Finite Automaton);
• NFA (Non-deterministic Finite Automaton);
• PDA (Push-Down Automaton);
• TM (Turing Machine);

What can do?

• Create and manage various types of automaton: DFA, NFA, PDA, TM.
• Visualize automata information in console.
• Simulate automata acceptors based on strings.
• Observe the processes of steps and transitions when introducing a string to the automaton.

📍 Index

• 🛠 Installation;
• 💻 Usage;
  • 🧿 First implementation;
  • 🧿 Second implementation;
• 📓 Documentation;
• 📚 Examples;
  • 🤖 DFA;
  • 🤖 NFA;
  • 🤖 PDA;
  • 🤖 TM;
  • 🔐 Safebox;
• 📁 Repository;
• ✍ Contributing;
• 📜 License;

🛠 Installation

You can install Pytomatas using pip:

pip install Pytomatas

💻 Usage

There are two ways in which automata can be implemented:

1. Creating the empty automaton and then adding the properties.
2. Creating the automaton by passing its characteristics as in the mathematical definition.

Example of a DFA implementation...

🧿 First implementation

1. Creating empty automata and then give the data:

fromPytomatas.dfaimportDFA# Creates a DFA called "my_dfa":my_dfa=DFA()
# Define to "my_dfa" a set of states names:my_dfa.setStates( {"q0", "q1", "qfinal"} )
# Define to "my_dfa" a set of states characters of the alphabet:my_dfa.setAlphabet( {"a", "b"} )
# Set the "Initial state" name of "my_dfa":my_dfa.setInitial( "q0" )
# Define to "my_dfa" the set of "Final states" names:my_dfa.setFinals( {"qfinal", "qf2"} )
# Add transitions to the DFA:my_dfa.addTransition( ("q0", "a", "q1") )
my_dfa.addTransition( ("q0", "b", "qfinal") )
my_dfa.addTransition( ("q1", "a", "q1") )
my_dfa.addTransition( ("q1", "b", "q1") )
my_dfa.addTransition( ("qfinal", "a", "qfinal") )
my_dfa.addTransition( ("qfinal", "b", "qfinal") )
# Add more data to the existing one already in the automata:my_dfa.addSymbol("c")
my_dfa.addState("qx")
my_dfa.addState("finalState2")
my_dfa.addFinal("finalState2")
# Prints the DFA information:my_dfa.show()
# Check if a string is accepted on the defined automata "my_dfa":# It returns True or False if the string is accepted or not:word="aaabb"my_dfa.accepts(word)
# Checks if the string is accepted, but prints all the process and steps on transitions;# Shows the flow of states while reading the string;my_dfa.accepts(word, stepByStep=True)

🧿 Second implementation

2. Creating the automata passing the data:

fromPytomatas.dfaimportDFA# Declare the States:Q= {"q0", "qa", "q1", "qb", "q2", "qf", "qx"}
# Declare the Alphabet:A= {"a", "b"}
# Declare the Initial (start) state:S="q0"# Declare the Finals states:F= {"q2", "q3"}
# Declare the Transitions:T= [
("q0", "a", "qa"),
("q0", "b", "q1"),
("qa", "a", "qa"),
("qa", "b", "qb"),
("qf", "b", "qf"),
("qx", "a", "qx"),
("qx", "b", "qx")
]
# Declare the Automata:my_dfa=DFA(Q, A, T, S, F)
# Show the automata information:my_dfa.show()
# Check if a string is accepted on the defined automata "my_dfa":# It returns True or False if the string is accepted or not:word="aaabb"my_dfa.accepts(word)
# Checks if the string is accepted, but prints all the process and steps on transitions;# Shows the flow of states while reading the string;# It returns True or False if the string is accepted or not:my_dfa.accepts(word, stepByStep=True)

🛑 NOTE: These are only implementation examples, not actual implementations, so they are not complete real automata definitions 👆

• For more detailed information about the attributes and methods of the class, refer to Documentation.

• For more detailed usage instructions and examples, please refer to Examples.

📓 Documentation

Go to THIS LINK to see the documentation on all the features of the different types of automata, the functions they have, and examples of their implementation.

📚 Examples

1. DFA (Deterministic Finite Automaton).

2. NFA (Non-deterministic Finite Automaton).

3. PDA (Push-Down Automaton).

4. TM (Turing Machine).

5. Safebox Automata Implementation Project.

📁 Repository

Go to THIS LINK to check out the source code.

✍ Contributing

Contributions are welcome! If you encounter any issues, have suggestions, or would like to contribute to the project, please feel free to open an issue or submit a pull request on this repository.

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

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Made with 💜 by @arhcoder;