Decorators

In Python, decorators are special functions that allow you to modify or extend the behavior of other functions or methods without changing their source code.

They are commonly used for logging, authentication, caching, performance measurement, and more.

Example: Logging Decorator

def log(func):
    def wrapper(*args, **kwargs):
        print(f"Calling {func.__name__} with {args}")
        result = func(*args, **kwargs)
        print(f"{func.__name__} returned {result}")
        return result
    return wrapper
 
@log
def add(a, b):
    return a + b
 
print(add(2, 3))

Here,

• log is a decorator function that accepts another function (func) as input.
• Inside log, a new function wrapper is defined. This function:
  • Prints the function name and arguments before calling the actual function.
  • Calls the original function (func(*args, **kwargs)) and stores the result.
  • Prints the result before returning it.
• The line @log applies the decorator to the add function. This is shorthand for writing: add = log(add)
• When add(2, 3) is called, it actually runs wrapper, adding the extra logging functionality.

Output:

Calling add with (2, 3)
add returned 5
5

Why Use Decorators?

• Add extra functionality without modifying original code
• Keep code clean and reusable
• Great for cross-cutting concerns like logging, access control, validation

Best Practices

• Always use functools.wraps to preserve the original function’s metadata.
• Keep decorators small and reusable.
• Avoid nesting too many decorators for readability.

When to Use Decorators

• Logging and debugging
• Authentication and authorization
• Measuring performance (timing functions)
• Input validation
• Caching results of expensive computations

👉 Next tutorial: Python Class Methods