Answer.

Decorators in Python historically emerged as a way to make code more compact and readable by encapsulating repetitive behavior around functions and methods. Before the introduction of the @decorator syntax, they were applied explicitly, which complicated code comprehension. Today, decorators play a key role in organizing logic, repetitive checks, logging, caching, and more.

The problem when working with decorators lies in correctly handling the differences between functions, instance methods, and static/class methods. Errors commonly arise related to loss of information about the method, late/early binding of self, as well as function signature issues.

The solution is to use the functools.wraps module when writing universal decorators to preserve metadata, as well as to carefully consider the type of the decorated object (for instance, correctly accounting that instance methods take self as the first argument).

Example code:

import functools

def my_decorator(func):
    @functools.wraps(func)
    def wrapper(*args, **kwargs):
        print(f"Before function: {func.__name__}")
        result = func(*args, **kwargs)
        print(f"After function: {func.__name__}")
        return result
    return wrapper

class Example:
    @my_decorator
    def method(self, x):
        print(f"Method called with {x}")

ex = Example()
ex.method(5)

Key features:

• A method-level decorator receives a function expecting self as the first argument.
• To preserve original metadata, it is recommended to use functools.wraps.
• Decorators can be parameterized for flexibility.

Trick questions.

If you use a decorator written for a function on a class method, is it necessary to use functools.wraps, and what will happen to self?

No, the decorator itself works, but without wraps, the function name, IDE assistance, and documentation are lost. Self will still be the first parameter, but the loss of metadata will hinder debugging and reflection.

def bad_decorator(f):
    def wrapper(*args, **kwargs):
        print("decorated")
        return f(*args, **kwargs)
    return wrapper

class Test:
    @bad_decorator
    def foo(self):
        pass
print(Test().foo.__name__)  # wrapper

Can the same decorator be applied to both an instance method and a static method?

Yes, but remember: static methods do not receive self as the first argument. If the decorator is expected to work with self, there will be errors with @staticmethod/ @classmethod.

How does a decorator affect the method signature and autocompletion?

Simply put: without functools.wraps, the signature and docstring are lost, and the IDE and many suggestion tools may not function correctly.

Common mistakes and anti-patterns

• Not using functools.wraps — losing function name and docstring complicates debugging.
• The decorator is written for a function without considering the presence of self — it works incorrectly on methods.
• Reusing the same decorator without considering context (static/class method/regular method).

Real-life example

Negative case: Decorators without functools.wraps in all class methods.
Pros: quick prototype, it works.
Cons: impossible to trace errors through the stack, the IDE does not suggest the signature.

Positive case: Decorators use functools.wraps, code is documented.
Pros: readability, maintainability, IDE comfort.
Cons: minimal addition to syntax and attention.