from functools import wraps
from inspect import signature


def logger(func):
    """ Function Decorator for Logging """

    @wraps(func)  # preserves meta data of the func
    def wrapper(*args, **kwargs):
        result = func(*args, **kwargs)
        arg_obj = signature(func).bind(*args, **kwargs).arguments.items()
        print(f"LOG: {func.__name__}", end='(')
        print(', '.join(f'{k}={v}' for k, v in arg_obj), end=') ')
        print(f"is {result}")
        return result

    return wrapper

# Before: No Logging
def mul(x, y):
    """ Multiplies x by y. """
    return x * y

var = mul(2, 3)

# Nothing Printed

# After: Logging Enabled
@logger
def mul(x, y):
    """ Multiplies x by y. """
    return x * y

var1 = mul(2, 3)
var2 = mul(4, y=3)
var3 = mul(x=6, y=5)

import pickle


class Cache:
    """ Function Cache """

    def __init__(self, function):
        self.cache = {}
        self.function = function
        self.__doc__ = function.__doc__

    def __call__(self, *args, **kwargs):
        key = (pickle.dumps(args), pickle.dumps(kwargs))
        if key in self.cache:
            result = self.cache[key]
        else:
            result = self.cache[key] = self.function(*args, **kwargs)
            print(f"Cached Value: {result}")
        return result

@Cache
def fib(n):
    """ Recursive Fibonacci """
    return 1 if n < 3 else fib(n - 1) + fib(n - 2)


print(fib(10))
print(fib(12))  # Notice the cache only caches new values.