Memento em Python

O Memento é um padrão de projeto comportamental que permite tirar um “retrato” do estado de um objeto e restaurá-lo no futuro.

O Memento não compromete a estrutura interna do objeto com o qual trabalha, nem os dados mantidos dentro dos retratos.

Saiba mais sobre o Memento

Complexidade:

Popularidade:

Exemplos de uso: O princípio do Memento pode ser alcançado usando a serialização, o que é bastante comum em Python. Embora não seja a única e a maneira mais eficiente de tirar retratos do estado de um objeto, ainda permite armazenar backups de estado, protegendo a estrutura do originador de outros objetos.

Exemplo conceitual

Este exemplo ilustra a estrutura do padrão de projeto Memento. Ele se concentra em responder a estas perguntas:

De quais classes ele consiste?
Quais papéis essas classes desempenham?
De que maneira os elementos do padrão estão relacionados?

main.py: Exemplo conceitual

from __future__ import annotations
from abc import ABC, abstractmethod
from datetime import datetime
from random import sample
from string import ascii_letters


class Originator:
    """
    The Originator holds some important state that may change over time. It also
    defines a method for saving the state inside a memento and another method
    for restoring the state from it.
    """

    _state = None
    """
    For the sake of simplicity, the originator's state is stored inside a single
    variable.
    """

    def __init__(self, state: str) -> None:
        self._state = state
        print(f"Originator: My initial state is: {self._state}")

    def do_something(self) -> None:
        """
        The Originator's business logic may affect its internal state.
        Therefore, the client should backup the state before launching methods
        of the business logic via the save() method.
        """

        print("Originator: I'm doing something important.")
        self._state = self._generate_random_string(30)
        print(f"Originator: and my state has changed to: {self._state}")

    @staticmethod
    def _generate_random_string(length: int = 10) -> str:
        return "".join(sample(ascii_letters, length))

    def save(self) -> Memento:
        """
        Saves the current state inside a memento.
        """

        return ConcreteMemento(self._state)

    def restore(self, memento: Memento) -> None:
        """
        Restores the Originator's state from a memento object.
        """

        self._state = memento.get_state()
        print(f"Originator: My state has changed to: {self._state}")


class Memento(ABC):
    """
    The Memento interface provides a way to retrieve the memento's metadata,
    such as creation date or name. However, it doesn't expose the Originator's
    state.
    """

    @abstractmethod
    def get_name(self) -> str:
        pass

    @abstractmethod
    def get_date(self) -> str:
        pass


class ConcreteMemento(Memento):
    def __init__(self, state: str) -> None:
        self._state = state
        self._date = str(datetime.now())[:19]

    def get_state(self) -> str:
        """
        The Originator uses this method when restoring its state.
        """
        return self._state

    def get_name(self) -> str:
        """
        The rest of the methods are used by the Caretaker to display metadata.
        """

        return f"{self._date} / ({self._state[0:9]}...)"

    def get_date(self) -> str:
        return self._date


class Caretaker:
    """
    The Caretaker doesn't depend on the Concrete Memento class. Therefore, it
    doesn't have access to the originator's state, stored inside the memento. It
    works with all mementos via the base Memento interface.
    """

    def __init__(self, originator: Originator) -> None:
        self._mementos = []
        self._originator = originator

    def backup(self) -> None:
        print("\nCaretaker: Saving Originator's state...")
        self._mementos.append(self._originator.save())

    def undo(self) -> None:
        if not len(self._mementos):
            return

        memento = self._mementos.pop()
        print(f"Caretaker: Restoring state to: {memento.get_name()}")
        try:
            self._originator.restore(memento)
        except Exception:
            self.undo()

    def show_history(self) -> None:
        print("Caretaker: Here's the list of mementos:")
        for memento in self._mementos:
            print(memento.get_name())


if __name__ == "__main__":
    originator = Originator("Super-duper-super-puper-super.")
    caretaker = Caretaker(originator)

    caretaker.backup()
    originator.do_something()

    caretaker.backup()
    originator.do_something()

    caretaker.backup()
    originator.do_something()

    print()
    caretaker.show_history()

    print("\nClient: Now, let's rollback!\n")
    caretaker.undo()

    print("\nClient: Once more!\n")
    caretaker.undo()

Output.txt: Resultados da execução

Originator: My initial state is: Super-duper-super-puper-super.

Caretaker: Saving Originator's state...
Originator: I'm doing something important.
Originator: and my state has changed to: wQAehHYOqVSlpEXjyIcgobrxsZUnat

Caretaker: Saving Originator's state...
Originator: I'm doing something important.
Originator: and my state has changed to: lHxNORKcsgMWYnJqoXjVCbQLEIeiSp

Caretaker: Saving Originator's state...
Originator: I'm doing something important.
Originator: and my state has changed to: cvIYsRilNOtwynaKdEZpDCQkFAXVMf

Caretaker: Here's the list of mementos:
2019-01-26 21:11:24 / (Super-dup...)
2019-01-26 21:11:24 / (wQAehHYOq...)
2019-01-26 21:11:24 / (lHxNORKcs...)

Client: Now, let's rollback!

Caretaker: Restoring state to: 2019-01-26 21:11:24 / (lHxNORKcs...)
Originator: My state has changed to: lHxNORKcsgMWYnJqoXjVCbQLEIeiSp

Client: Once more!

Caretaker: Restoring state to: 2019-01-26 21:11:24 / (wQAehHYOq...)
Originator: My state has changed to: wQAehHYOqVSlpEXjyIcgobrxsZUnat

Memento em Python

Exemplo conceitual

main.py: Exemplo conceitual

Output.txt: Resultados da execução

Memento em outras linguagens