Decorator in Python
How To Simplifying Your Code And Boost Your Function — #PurePythonSeries — Episode #08
See this scenario:
A Compatibility issues come up when users are using the same type of software for a task, such as word processors, that cannot communicate with each other. This could be due to a difference in their versions or because they are made by different companiesNow you are called to deal with this problem and bring a solution, and all you have is Python!(thanks god:)You need to change the behavior of a function without modifying the function itself so the system doesn't break:/
Let´s simulate some method to simplifing your task, and brings the point home: Decorator!
Suppose you have this legacy code:
def func_needs_decorator1():
print("I need a Decorator!")This function is desperately in need of an upgrade. Let´s suppose it needs some code before and after its actual output.
There is no reimplementation options. The system must not stop.
This code must always run even after your implementation:
func_needs_decorator1()I need a Decorator!
Here comes the Python’s decorator patterns to rescue us:
def new_decorator(func): def wrap_func():
print("#####Decorator before...#######")
func()
print("#####Decorator after ...#######")
return wrap_func
Now, 🎉 Feel The Magic ✨
func_needs_decorator = new_decorator(func_needs_decorator1)
func_needs_decorator()#####Decorator before...#######
I need a Decorator!
#####Decorator after ...#######
There you have it!
Wait…Let’s make in the pythonic way (it reads: code that is readable and beautiful)!
Decorate your methods like this:
@new_decorator
def func_needs_decorator2():
print("I need a Decorator!")Now type:
func_needs_decorator2()#####Decorator before...#######
I need a Decorator!
#####Decorator after ...#######
This code is Beautful, isn’t it?
Decorators can be extremely useful as they allow the extension of an existing function, without any modification to the original function source code.
That’s all, folks!
See you soon o/
Bye!
👉Jupiter notebook link :)
👉git
Credits And References
Jose Portilla — Python for Data Science and Machine Learning Bootcamp — Learn how to use NumPy, Pandas, Seaborn, Matplotlib, Plotly, Scikit-Learn, Machine Learning, Tensorflow, and more!
Python Decorators I: Introduction to Python Decorators by Bruce Eckel
Python Decorators II: Decorator Arguments by Bruce Eckel
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edited: Nov, 2022 — add replit link ;)
