Lec 24 More Design Patterns and Decorators

Design Patterns

• Strategy patterns
  • Allows for altering distance definition at run time
• Maps (Google Maps navigation):
  • Users can choose to prioritize:
    • Shortest path
    • Shortest time
    • Least emissions
    • Least tolls
    • Maximize sightseeing

Decorators

• Functions are objects
  • Can be put in a list of callables
  • Can print their attributes

def bacon():
        print("hi")
    print(bacon.__name__)

• Function decorators mutate a function to modify what it does
  • @time_calls modifies a given fn to print the time it took to run
  • Wrappers will override metadata by default (i.e., fn.__name__ or fn.__docs__)
    • Can use @wraps in inside of the function
• Example making a decorator:

def time_calls(func: Callable[..., Any]) -> Callable[..., Any]:
    def wrapper(*args: Any, **kwargs: Any) -> Any:
        now = time.time()
        return_value = func(*args, **kwargs)
        print(f'Executed {func.__name__} with {args} and {kwargs} in {time.time() - now}ms')
        return return_value
    return wrapper

• Common usage is in temporal caching/memoization

R = TypeVar("R")

def memoize(func: Callable[..., R]) -> Callable[..., R]:
    cache: dict[tuple[Any, ...], R] = {}
    def wrapper():
        if args in cache:
            return cache[args]
        result - func(*args)
        cache[args] = result
        return result
    return wrapper

@memoize
def fibonachi(x):
    # implementation...    
    pass

• Class decorators exist in Python, although more popular in other OOPs, like Java
  • Basically works the same
  • Takes a class as an input and returns a class

def class_wrapper():
    original_init = cls__init
    @warps(original_init)
    def new_init():
        printf("Creating instance of our class, cls")
        original_init(self, *args, **kwargs)

    cls.__init__ = new_init
    return cls