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Decorators in Python are one of the most powerful and useful tools, yet they are often underutilized. They allow you to "wrap" a function to extend its behavior without permanently modifying it. This becomes extremely handy when adding functionalities like logging, authentication, caching, or performance tracking. Mastering decorators boosts your ability to write clean, modular, and professional-grade code.
A decorator is simply a function that takes another function as an argument, adds some functionality, and returns another function.
# Basic decorator that logs the execution of a function
def log_decorator(func):
def wrapper(*args, **kwargs):
print(f"Function '{func.__name__}' is being called")
result = func(*args, **kwargs)
print(f"Function '{func.__name__}' executed successfully")
return result
return wrapper
# Applying the decorator
@log_decorator
def greet(name):
print(f"Hello, {name}!")
# Function call
greet("Tanu")
Function 'greet' is being called Hello, Tanu! Function 'greet' executed successfully
@log_decorator
automatically wraps the greet function.greet("Tanu")
, the wrapper runs first, logs the messages, then executes the actual function.In Python, even built-in features like @staticmethod
and @classmethod
are implemented as decorators!
Mastering decorators empowers you to write cleaner, more efficient Python code. By adding functionality without touching the core logic, decorators make your programs more modular, readable, and professional. Thanks for reading my article, let me know if you have any suggestions or similar implementations via the comment section. Until then, see you next time. Happy coding!