Mémento en Python
Le Mémento est un patron de conception comportemental qui permet de prendre des instantanés de l’état d’un objet et de les restaurer plus tard.
Le mémento ne compromet pas l’intégrité de la structure interne de l’objet avec lequel il interagit, ni celle des données contenues dans l’instantané.
Complexité :
Popularité :
Exemples d’utilisation : Le principe du mémento peut être imité en utilisant la sérialisation, ce qui est assez commun en Python. Ce n’est pas forcément la manière la plus efficace de prendre des instantanés de l’état d’un objet, mais il permet de stocker des sauvegardes de l’état tout en protégeant la structure du créateur des autres objets.
Exemple conceptuel
Dans cet exemple, nous allons voir la structure du Mémento. Nous allons répondre aux questions suivantes :
- Que contiennent les classes ?
- Quels rôles jouent-elles ?
- Comment les éléments du patron sont-ils reliés ?
main.py: Exemple conceptuel
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: Résultat de l’exécution
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
