Behavioral

Behavioral patterns take care of effective communication and the assignment of responsibilities between objects.

Code taken fully from refactoring.guru with my descriptions. Again, no code was written by me, I am just able to execute it here.

Chain of Responsibility

Passes request down the chain, until it is handled.

from __future__ import annotations
from abc import ABC, abstractmethod
from typing import Any, Optional


class Handler(ABC):
    """
    The Handler interface declares a method for building the chain of handlers.
    It also declares a method for executing a request.
    """

    @abstractmethod
    def set_next(self, handler: Handler) -> Handler:
        pass

    @abstractmethod
    def handle(self, request) -> Optional[str]:
        pass


class AbstractHandler(Handler):
    """
    The default chaining behavior can be implemented inside a base handler
    class.
    """

    _next_handler: Handler = None

    def set_next(self, handler: Handler) -> Handler:
        self._next_handler = handler
        # Returning a handler from here will let us link handlers in a
        # convenient way like this:
        # monkey.set_next(squirrel).set_next(dog)
        return handler

    @abstractmethod
    def handle(self, request: Any) -> str:
        if self._next_handler:
            return self._next_handler.handle(request)

        return None


"""
All Concrete Handlers either handle a request or pass it to the next handler in
the chain.
"""


class MonkeyHandler(AbstractHandler):
    def handle(self, request: Any) -> str:
        if request == "Banana":
            return f"Monkey: I'll eat the {request}"
        else:
            return super().handle(request)


class SquirrelHandler(AbstractHandler):
    def handle(self, request: Any) -> str:
        if request == "Nut":
            return f"Squirrel: I'll eat the {request}"
        else:
            return super().handle(request)


class DogHandler(AbstractHandler):
    def handle(self, request: Any) -> str:
        if request == "MeatBall":
            return f"Dog: I'll eat the {request}"
        else:
            return super().handle(request)


def client_code(handler: Handler) -> None:
    """
    The client code is usually suited to work with a single handler. In most
    cases, it is not even aware that the handler is part of a chain.
    """

    for food in ["Nut", "Banana", "Cup of coffee"]:
        print(f"\nClient: Who wants a {food}?")
        result = handler.handle(food)
        if result:
            print(f"  {result}", end="")
        else:
            print(f"  {food} was left untouched.", end="")


if __name__ == "__main__":
    monkey = MonkeyHandler()
    squirrel = SquirrelHandler()
    dog = DogHandler()

    monkey.set_next(squirrel).set_next(dog)  # KEY POINT

    # The client should be able to send a request to any handler, not just the
    # first one in the chain.
    print("Chain: Monkey > Squirrel > Dog")
    client_code(monkey)
    print("\n")

    print("Subchain: Squirrel > Dog")
    client_code(squirrel)

Chain: Monkey > Squirrel > Dog

Client: Who wants a Nut?
  Squirrel: I'll eat the Nut
Client: Who wants a Banana?
  Monkey: I'll eat the Banana
Client: Who wants a Cup of coffee?
  Cup of coffee was left untouched.

Subchain: Squirrel > Dog

Client: Who wants a Nut?
  Squirrel: I'll eat the Nut
Client: Who wants a Banana?
  Banana was left untouched.
Client: Who wants a Cup of coffee?
  Cup of coffee was left untouched.

Command

Command can either execute simple stuff or delegate to receiver more complex work.

from __future__ import annotations
from abc import ABC, abstractmethod


class Command(ABC):
    """
    The Command interface declares a method for executing a command.
    """

    @abstractmethod
    def execute(self) -> None:
        pass


class SimpleCommand(Command):
    """
    Some commands can implement simple operations on their own.
    """

    def __init__(self, payload: str) -> None:
        self._payload = payload

    def execute(self) -> None:
        print(f"SimpleCommand: See, I can do simple things like printing"
              f"({self._payload})")


class ComplexCommand(Command):
    """
    However, some commands can delegate more complex operations to other
    objects, called "receivers."
    """

    def __init__(self, receiver: Receiver, a: str, b: str) -> None:
        """
        Complex commands can accept one or several receiver objects along with
        any context data via the constructor.
        """

        self._receiver = receiver
        self._a = a
        self._b = b

    def execute(self) -> None:
        """
        Commands can delegate to any methods of a receiver.
        """

        print("ComplexCommand: Complex stuff should be done by a receiver object", end="")
        self._receiver.do_something(self._a)    # KEY POINT
        self._receiver.do_something_else(self._b)


class Receiver:
    """
    The Receiver classes contain some important business logic. They know how to
    perform all kinds of operations, associated with carrying out a request. In
    fact, any class may serve as a Receiver.
    """

    def do_something(self, a: str) -> None:
        print(f"\nReceiver: Working on ({a}.)", end="")

    def do_something_else(self, b: str) -> None:
        print(f"\nReceiver: Also working on ({b}.)", end="")


class Invoker:
    """
    The Invoker is associated with one or several commands. It sends a request
    to the command.
    """

    _on_start = None
    _on_finish = None

    """
    Initialize commands.
    """

    def set_on_start(self, command: Command):
        self._on_start = command

    def set_on_finish(self, command: Command):
        self._on_finish = command

    def do_something_important(self) -> None:
        """
        The Invoker does not depend on concrete command or receiver classes. The
        Invoker passes a request to a receiver indirectly, by executing a
        command.
        """

        print("Invoker: Does anybody want something done before I begin?")
        if isinstance(self._on_start, Command):
            self._on_start.execute()

        print("Invoker: ...doing something really important...")

        print("Invoker: Does anybody want something done after I finish?")
        if isinstance(self._on_finish, Command):
            self._on_finish.execute()


if __name__ == "__main__":
    """
    The client code can parameterize an invoker with any commands.
    """

    invoker = Invoker()
    invoker.set_on_start(SimpleCommand("Say Hi!"))
    invoker.set_on_finish(ComplexCommand(
        Receiver(), "Send email", "Save report"))

    invoker.do_something_important()

Invoker: Does anybody want something done before I begin?
SimpleCommand: See, I can do simple things like printing(Say Hi!)
Invoker: ...doing something really important...
Invoker: Does anybody want something done after I finish?
ComplexCommand: Complex stuff should be done by a receiver object
Receiver: Working on (Send email.)
Receiver: Also working on (Save report.)

Iterator

Defines how to iterate over a collection.

from __future__ import annotations
from collections.abc import Iterable, Iterator
from typing import Any


"""
To create an iterator in Python, there are two abstract classes from the built-
in `collections` module - Iterable,Iterator.  # KEY POINT

We need to implement the `__iter__()` method in the iterated object (collection), 
and the `__next__ ()` method in the iterator.
"""


class AlphabeticalOrderIterator(Iterator):
    """
    Concrete Iterators implement various traversal algorithms. These classes
    store the current traversal position at all times.
    """

    """
    `_position` attribute stores the current traversal position. An iterator may
    have a lot of other fields for storing iteration state, especially when it
    is supposed to work with a particular kind of collection.
    """
    _position: int = None

    """
    This attribute indicates the traversal direction.
    """
    _reverse: bool = False

    def __init__(self, collection: WordsCollection, reverse: bool = False) -> None:
        self._collection = collection
        self._reverse = reverse
        self._position = -1 if reverse else 0

    def __next__(self) -> Any:
        """
        The __next__() method must return the next item in the sequence. On
        reaching the end, and in subsequent calls, it must raise StopIteration.
        """
        try:
            value = self._collection[self._position]
            self._position += -1 if self._reverse else 1
        except IndexError:
            raise StopIteration()

        return value


class WordsCollection(Iterable):
    """
    Concrete Collections provide one or several methods for retrieving fresh
    iterator instances, compatible with the collection class.
    """

    def __init__(self, collection: list[Any] | None = None) -> None:
        self._collection = collection or []


    def __getitem__(self, index: int) -> Any:
        return self._collection[index]

    def __iter__(self) -> AlphabeticalOrderIterator:
        """
        The __iter__() method returns the iterator object itself, by default we
        return the iterator in ascending order.
        """
        return AlphabeticalOrderIterator(self)

    def get_reverse_iterator(self) -> AlphabeticalOrderIterator:
        return AlphabeticalOrderIterator(self, True)

    def add_item(self, item: Any) -> None:
        self._collection.append(item)


if __name__ == "__main__":
    # The client code may or may not know about the Concrete Iterator or
    # Collection classes, depending on the level of indirection you want to keep
    # in your program.
    collection = WordsCollection()
    collection.add_item("First")
    collection.add_item("Second")
    collection.add_item("Third")

    print("Straight traversal:")
    print("\n".join(collection))
    print("")

    print("Reverse traversal:")
    print("\n".join(collection.get_reverse_iterator()), end="")

Straight traversal:
First
Second
Third

Reverse traversal:
Third
Second
First

Mediator

Enables communication between objects.

from __future__ import annotations
from abc import ABC


class Mediator(ABC):
    """
    The Mediator interface declares a method used by components to notify the
    mediator about various events. The Mediator may react to these events and
    pass the execution to other components.
    """

    def notify(self, sender: object, event: str) -> None:
        pass


class ConcreteMediator(Mediator):
    def __init__(self, component1: Component1, component2: Component2) -> None:
        self._component1 = component1
        self._component1.mediator = self
        self._component2 = component2
        self._component2.mediator = self

    def notify(self, sender: object, event: str) -> None:
        if event == "A":
            print("Mediator reacts on A and triggers following operations:")
            self._component2.do_c()
        elif event == "D":
            print("Mediator reacts on D and triggers following operations:")
            self._component1.do_b()
            self._component2.do_c()


class BaseComponent:
    """
    The Base Component provides the basic functionality of storing a mediator's
    instance inside component objects.
    """

    def __init__(self, mediator: Mediator = None) -> None:
        self._mediator = mediator

    @property
    def mediator(self) -> Mediator:
        return self._mediator

    @mediator.setter
    def mediator(self, mediator: Mediator) -> None:
        self._mediator = mediator


"""
Concrete Components implement various functionality. They don't depend on other
components. They also don't depend on any concrete mediator classes.
"""


class Component1(BaseComponent):
    def do_a(self) -> None:
        print("Component 1 does A.")
        self.mediator.notify(self, "A")

    def do_b(self) -> None:
        print("Component 1 does B.")
        self.mediator.notify(self, "B")


class Component2(BaseComponent):
    def do_c(self) -> None:
        print("Component 2 does C.")
        self.mediator.notify(self, "C")

    def do_d(self) -> None:
        print("Component 2 does D.")
        self.mediator.notify(self, "D")


if __name__ == "__main__":
    # The client code.
    c1 = Component1()
    c2 = Component2()
    mediator = ConcreteMediator(c1, c2)   # KEY POINT

    print("Client triggers operation A.")
    c1.do_a()

    print("\n", end="")

    print("Client triggers operation D.")
    c2.do_d()

Client triggers operation A.
Component 1 does A.
Mediator reacts on A and triggers following operations:
Component 2 does C.

Client triggers operation D.
Component 2 does D.
Mediator reacts on D and triggers following operations:
Component 1 does B.
Component 2 does C.

Memento

Save a state, when you want to undo an action.

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)    # KEY POINT

    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-duper-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()

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

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

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

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

Caretaker: Here's the list of mementos:
2024-03-19 16:25:42 / (Super-dup...)
2024-03-19 16:25:42 / (MkTDBwnJE...)
2024-03-19 16:25:42 / (lcGDuJvmH...)

Client: Now, let's rollback!

Caretaker: Restoring state to: 2024-03-19 16:25:42 / (lcGDuJvmH...)
Originator: My state has changed to: lcGDuJvmHLdaCpkWKSiBIjneXAftxs

Client: Once more!

Caretaker: Restoring state to: 2024-03-19 16:25:42 / (MkTDBwnJE...)
Originator: My state has changed to: MkTDBwnJEdosCOpXrgbfYWeLAUGRza

Observer

It enables subscription, so when the state of the subject changes, the observer is notified and can react.

from __future__ import annotations
from abc import ABC, abstractmethod
from random import randrange
from typing import List


class Subject(ABC):
    """
    The Subject interface declares a set of methods for managing subscribers.
    """

    @abstractmethod
    def attach(self, observer: Observer) -> None:
        """
        Attach an observer to the subject.
        """
        pass

    @abstractmethod
    def detach(self, observer: Observer) -> None:
        """
        Detach an observer from the subject.
        """
        pass

    @abstractmethod
    def notify(self) -> None:
        """
        Notify all observers about an event.
        """
        pass


class ConcreteSubject(Subject):
    """
    The Subject owns some important state and notifies observers when the state
    changes.
    """

    _state: int = None
    """
    For the sake of simplicity, the Subject's state, essential to all
    subscribers, is stored in this variable.
    """

    _observers: List[Observer] = []
    """
    List of subscribers. In real life, the list of subscribers can be stored
    more comprehensively (categorized by event type, etc.).
    """

    def attach(self, observer: Observer) -> None:
        print("Subject: Attached an observer.")
        self._observers.append(observer)    # KEY POINT

    def detach(self, observer: Observer) -> None:
        self._observers.remove(observer)

    """
    The subscription management methods.
    """

    def notify(self) -> None:
        """
        Trigger an update in each subscriber.
        """

        print("Subject: Notifying observers...")
        for observer in self._observers:
            observer.update(self)

    def some_business_logic(self) -> None:
        """
        Usually, the subscription logic is only a fraction of what a Subject can
        really do. Subjects commonly hold some important business logic, that
        triggers a notification method whenever something important is about to
        happen (or after it).
        """

        print("\nSubject: I'm doing something important.")
        self._state = randrange(0, 10)

        print(f"Subject: My state has just changed to: {self._state}")
        self.notify()


class Observer(ABC):
    """
    The Observer interface declares the update method, used by subjects.
    """

    @abstractmethod
    def update(self, subject: Subject) -> None:
        """
        Receive update from subject.
        """
        pass


"""
Concrete Observers react to the updates issued by the Subject they had been
attached to.
"""


class ConcreteObserverA(Observer):
    def update(self, subject: Subject) -> None:
        if subject._state < 3:
            print("ConcreteObserverA: Reacted to the event")


class ConcreteObserverB(Observer):
    def update(self, subject: Subject) -> None:
        if subject._state == 0 or subject._state >= 2:
            print("ConcreteObserverB: Reacted to the event")


if __name__ == "__main__":
    # The client code.

    subject = ConcreteSubject()

    observer_a = ConcreteObserverA()
    subject.attach(observer_a)

    observer_b = ConcreteObserverB()
    subject.attach(observer_b)

    subject.some_business_logic()
    subject.some_business_logic()

    subject.detach(observer_a)

    subject.some_business_logic()

Subject: Attached an observer.
Subject: Attached an observer.

Subject: I'm doing something important.
Subject: My state has just changed to: 9
Subject: Notifying observers...
ConcreteObserverB: Reacted to the event

Subject: I'm doing something important.
Subject: My state has just changed to: 1
Subject: Notifying observers...
ConcreteObserverA: Reacted to the event

Subject: I'm doing something important.
Subject: My state has just changed to: 5
Subject: Notifying observers...
ConcreteObserverB: Reacted to the event

State

Records states of a Context and transitions between the states. State knows about Context and vice versa.

from __future__ import annotations
from abc import ABC, abstractmethod


class Context:
    """
    The Context defines the interface of interest to clients. It also maintains
    a reference to an instance of a State subclass, which represents the current
    state of the Context.
    """

    _state = None
    """
    A reference to the current state of the Context.
    """

    def __init__(self, state: State) -> None:
        self.transition_to(state)

    def transition_to(self, state: State):   # KEY POINT
        """
        The Context allows changing the State object at runtime.
        """

        print(f"Context: Transition to {type(state).__name__}")
        self._state = state
        self._state.context = self

    """
    The Context delegates part of its behavior to the current State object.
    """

    def request1(self):
        self._state.handle1()

    def request2(self):
        self._state.handle2()


class State(ABC):
    """
    The base State class declares methods that all Concrete State should
    implement and also provides a backreference to the Context object,
    associated with the State. This backreference can be used by States to
    transition the Context to another State.
    """

    @property
    def context(self) -> Context:
        return self._context

    @context.setter
    def context(self, context: Context) -> None:
        self._context = context

    @abstractmethod
    def handle1(self) -> None:
        pass

    @abstractmethod
    def handle2(self) -> None:
        pass


"""
Concrete States implement various behaviors, associated with a state of the
Context.
"""


class ConcreteStateA(State):
    def handle1(self) -> None:
        print("ConcreteStateA handles request1.")
        print("ConcreteStateA wants to change the state of the context.")
        self.context.transition_to(ConcreteStateB())

    def handle2(self) -> None:
        print("ConcreteStateA handles request2.")


class ConcreteStateB(State):
    def handle1(self) -> None:
        print("ConcreteStateB handles request1.")

    def handle2(self) -> None:
        print("ConcreteStateB handles request2.")
        print("ConcreteStateB wants to change the state of the context.")
        self.context.transition_to(ConcreteStateA())


if __name__ == "__main__":
    # The client code.

    context = Context(ConcreteStateA())
    context.request1()
    context.request2()

Context: Transition to ConcreteStateA
ConcreteStateA handles request1.
ConcreteStateA wants to change the state of the context.
Context: Transition to ConcreteStateB
ConcreteStateB handles request2.
ConcreteStateB wants to change the state of the context.
Context: Transition to ConcreteStateA

Strategy

Strategy is a way to select an algorithm at runtime.

from __future__ import annotations
from abc import ABC, abstractmethod
from typing import List


class Context():
    """
    The Context defines the interface of interest to clients.
    """

    def __init__(self, strategy: Strategy) -> None:    # KEY POINT
        """
        Usually, the Context accepts a strategy through the constructor, but
        also provides a setter to change it at runtime.
        """

        self._strategy = strategy

    @property
    def strategy(self) -> Strategy:
        """
        The Context maintains a reference to one of the Strategy objects. The
        Context does not know the concrete class of a strategy. It should work
        with all strategies via the Strategy interface.
        """

        return self._strategy

    @strategy.setter
    def strategy(self, strategy: Strategy) -> None:
        """
        Usually, the Context allows replacing a Strategy object at runtime.
        """

        self._strategy = strategy

    def do_some_business_logic(self) -> None:
        """
        The Context delegates some work to the Strategy object instead of
        implementing multiple versions of the algorithm on its own.
        """

        # ...

        print("Context: Sorting data using the strategy (not sure how it'll do it)")
        result = self._strategy.do_algorithm(["a", "b", "c", "d", "e"])
        print(",".join(result))

        # ...


class Strategy(ABC):
    """
    The Strategy interface declares operations common to all supported versions
    of some algorithm.

    The Context uses this interface to call the algorithm defined by Concrete
    Strategies.
    """

    @abstractmethod
    def do_algorithm(self, data: List):
        pass


"""
Concrete Strategies implement the algorithm while following the base Strategy
interface. The interface makes them interchangeable in the Context.
"""


class ConcreteStrategyA(Strategy):
    def do_algorithm(self, data: List) -> List:
        return sorted(data)


class ConcreteStrategyB(Strategy):
    def do_algorithm(self, data: List) -> List:
        return reversed(sorted(data))


if __name__ == "__main__":
    # The client code picks a concrete strategy and passes it to the context.
    # The client should be aware of the differences between strategies in order
    # to make the right choice.

    context = Context(ConcreteStrategyA())
    print("Client: Strategy is set to normal sorting.")
    context.do_some_business_logic()
    print()

    print("Client: Strategy is set to reverse sorting.")
    context.strategy = ConcreteStrategyB()
    context.do_some_business_logic()

Client: Strategy is set to normal sorting.
Context: Sorting data using the strategy (not sure how it'll do it)
a,b,c,d,e

Client: Strategy is set to reverse sorting.
Context: Sorting data using the strategy (not sure how it'll do it)
e,d,c,b,a

Template

Have a template parent class, where children can override some methods.

from abc import ABC, abstractmethod


class AbstractClass(ABC):
    """
    The Abstract Class defines a template method that contains a skeleton of
    some algorithm, composed of calls to (usually) abstract primitive
    operations.

    Concrete subclasses should implement these operations, but leave the
    template method itself intact.
    """

    def template_method(self) -> None:    # KEY POINT
        """
        The template method defines the skeleton of an algorithm.
        """

        self.base_operation1()
        self.required_operations1()
        self.base_operation2()
        self.hook1()
        self.required_operations2()
        self.base_operation3()
        self.hook2()

    # These operations already have implementations.

    def base_operation1(self) -> None:
        print("AbstractClass says: I am doing the bulk of the work")

    def base_operation2(self) -> None:
        print("AbstractClass says: But I let subclasses override some operations")

    def base_operation3(self) -> None:
        print("AbstractClass says: But I am doing the bulk of the work anyway")

    # These operations have to be implemented in subclasses.

    @abstractmethod
    def required_operations1(self) -> None:
        pass

    @abstractmethod
    def required_operations2(self) -> None:
        pass

    # These are "hooks." Subclasses may override them, but it's not mandatory
    # since the hooks already have default (but empty) implementation. Hooks
    # provide additional extension points in some crucial places of the
    # algorithm.

    def hook1(self) -> None:
        pass

    def hook2(self) -> None:
        pass


class ConcreteClass1(AbstractClass):
    """
    Concrete classes have to implement all abstract operations of the base
    class. They can also override some operations with a default implementation.
    """

    def required_operations1(self) -> None:
        print("ConcreteClass1 says: Implemented Operation1")

    def required_operations2(self) -> None:
        print("ConcreteClass1 says: Implemented Operation2")


class ConcreteClass2(AbstractClass):
    """
    Usually, concrete classes override only a fraction of base class'
    operations.
    """

    def required_operations1(self) -> None:
        print("ConcreteClass2 says: Implemented Operation1")

    def required_operations2(self) -> None:
        print("ConcreteClass2 says: Implemented Operation2")

    def hook1(self) -> None:
        print("ConcreteClass2 says: Overridden Hook1")


def client_code(abstract_class: AbstractClass) -> None:
    """
    The client code calls the template method to execute the algorithm. Client
    code does not have to know the concrete class of an object it works with, as
    long as it works with objects through the interface of their base class.
    """

    # ...
    abstract_class.template_method()
    # ...


if __name__ == "__main__":
    print("Same client code can work with different subclasses:")
    client_code(ConcreteClass1())
    print("")

    print("Same client code can work with different subclasses:")
    client_code(ConcreteClass2())

Same client code can work with different subclasses:
AbstractClass says: I am doing the bulk of the work
ConcreteClass1 says: Implemented Operation1
AbstractClass says: But I let subclasses override some operations
ConcreteClass1 says: Implemented Operation2
AbstractClass says: But I am doing the bulk of the work anyway

Same client code can work with different subclasses:
AbstractClass says: I am doing the bulk of the work
ConcreteClass2 says: Implemented Operation1
AbstractClass says: But I let subclasses override some operations
ConcreteClass2 says: Overridden Hook1
ConcreteClass2 says: Implemented Operation2
AbstractClass says: But I am doing the bulk of the work anyway

Visitor

Visitor allows to add new operations to existing classes without modifying them.

from __future__ import annotations
from abc import ABC, abstractmethod
from typing import List


class Component(ABC):
    """
    The Component interface declares an `accept` method that should take the
    base visitor interface as an argument.
    """

    @abstractmethod
    def accept(self, visitor: Visitor) -> None:
        pass


class ConcreteComponentA(Component):
    """
    Each Concrete Component must implement the `accept` method in such a way
    that it calls the visitor's method corresponding to the component's class.
    """

    def accept(self, visitor: Visitor) -> None:
        """
        Note that we're calling `visitConcreteComponentA`, which matches the
        current class name. This way we let the visitor know the class of the
        component it works with.
        """

        visitor.visit_concrete_component_a(self)

    def exclusive_method_of_concrete_component_a(self) -> str:
        """
        Concrete Components may have special methods that don't exist in their
        base class or interface. The Visitor is still able to use these methods
        since it's aware of the component's concrete class.
        """

        return "A"


class ConcreteComponentB(Component):
    """
    Same here: visitConcreteComponentB => ConcreteComponentB
    """

    def accept(self, visitor: Visitor):
        visitor.visit_concrete_component_b(self)

    def special_method_of_concrete_component_b(self) -> str:
        return "B"


class Visitor(ABC):
    """
    The Visitor Interface declares a set of visiting methods that correspond to
    component classes. The signature of a visiting method allows the visitor to
    identify the exact class of the component that it's dealing with.   # KEY POINT
    """

    @abstractmethod
    def visit_concrete_component_a(self, element: ConcreteComponentA) -> None:
        pass

    @abstractmethod
    def visit_concrete_component_b(self, element: ConcreteComponentB) -> None:
        pass


"""
Concrete Visitors implement several versions of the same algorithm, which can
work with all concrete component classes.

You can experience the biggest benefit of the Visitor pattern when using it with
a complex object structure, such as a Composite tree. In this case, it might be
helpful to store some intermediate state of the algorithm while executing
visitor's methods over various objects of the structure.
"""


class ConcreteVisitor1(Visitor):
    def visit_concrete_component_a(self, element) -> None:
        print(f"{element.exclusive_method_of_concrete_component_a()} + ConcreteVisitor1")

    def visit_concrete_component_b(self, element) -> None:
        print(f"{element.special_method_of_concrete_component_b()} + ConcreteVisitor1")


class ConcreteVisitor2(Visitor):
    def visit_concrete_component_a(self, element) -> None:
        print(f"{element.exclusive_method_of_concrete_component_a()} + ConcreteVisitor2")

    def visit_concrete_component_b(self, element) -> None:
        print(f"{element.special_method_of_concrete_component_b()} + ConcreteVisitor2")


def client_code(components: List[Component], visitor: Visitor) -> None:
    """
    The client code can run visitor operations over any set of elements without
    figuring out their concrete classes. The accept operation directs a call to
    the appropriate operation in the visitor object.
    """

    # ...
    for component in components:
        component.accept(visitor)
    # ...


if __name__ == "__main__":
    components = [ConcreteComponentA(), ConcreteComponentB()]

    print("The client code works with all visitors via the base Visitor interface:")
    visitor1 = ConcreteVisitor1()
    client_code(components, visitor1)

    print("It allows the same client code to work with different types of visitors:")
    visitor2 = ConcreteVisitor2()
    client_code(components, visitor2)

The client code works with all visitors via the base Visitor interface:
A + ConcreteVisitor1
B + ConcreteVisitor1
It allows the same client code to work with different types of visitors:
A + ConcreteVisitor2
B + ConcreteVisitor2