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What are the common uses of Python decorators?

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What are the common uses of Python decorators?

In this article, we will learn the common uses of Python decorators

What is a Python decorator?

A Python decorator is a piece of code that allows additions or updates to existing functions without having to change the underlying function definition. When a program runs, it tries to edit another part of itself, which is called metaprogramming.

Decorator is a function type that accepts a function and returns another function, or accepts a class and returns another class. It can be any callable (function, class, method, etc.) and can return anything; it can also take a method.

Python decorators are easy to use.

The decorator accepts a

callable object, which implements the special method __call()__, which is called a callable object. It adds some functionality and returns a Callable object. The Chinese translation of

Example

is:

Example

@somedecorator
def exmple_decorators():
   print("Hello tutorialspoint python decorators")
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Writing decorators, on the other hand, requires an entirely different set of skills. This is not a simple matter; you must fully understand the following -

    closure
  • Use functions as first-class parameters,
  • Variable parameters
  • Parameter unpacking and
  • Even some information about how Python loads its source code.
It takes a long time to master and perfect all of this. And you already have a long list of things to learn.

Is this worth your time?

The answer is obviously

is . What are the main advantages of writing decorators? Do they enable you to effortlessly excel in your daily development?

let us see!

Analysis, Logging and Detection

We often need to specifically measure what is happening and collect metrics that quantify different operations, especially for large applications. Decorators can solve this requirement in an extremely readable and simple way by encapsulating these noteworthy events in their own functions or methods.

Validation and Runtime Checks

Python's type system is strongly typed but dynamic. Although it has many advantages, it also means that some problems may be detected at compile time by more statically typed languages ​​such as Java.

In addition to this, you may wish to implement more complex custom checks on data entering and exiting the system. Decorators help you manage all of this and apply it to multiple functions at the same time.

Create framework

Once you learn to write decorators, you can benefit from their concise syntax, which allows you to easily add semantics to the language. This is as close as you can get to being able to extend Python syntax.

Many well-known open source frameworks use it. The web application framework

Flask uses this to route URLs to functions that handle HTTP requests.

Reuse non-reusable code

Through elegant function syntax, functional programming support, and a complete object system, Python provides some very powerful tools for encapsulating code into an easily reusable form. However, these tools alone cannot capture certain code reuse patterns.

Consider using the Flakey API. You send a query over HTTP to an object that understands JSON, and 99.9% of the time it works. However, a small percentage of all requests will cause the server to return an internal error, requiring you to retry the request. In this case you need to add some retry logic.

The Chinese translation of

Example

is:

Example

# Creating a decorator function
def decoratorFunction(demofunction):
	def innerFunc():
		print("Yup...It is a decorated function")
		demofunction()
	return innerFunc()

# Creating a regular ordinary function
def normalFunction():
	print("Yup...It is a normal ordinary function")

decoratedResult = decoratorFunction(normalFunction)
decoratedResult
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Output

When executed, the above program will generate the following output -

Yup...It is a decorated function
Yup...It is a normal ordinary function
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decoratorFunction() is a decorator in the previous example. Simply put, a decorator is a wrapper that wraps an object (without changing it) and adds new functionality to the original object. Because this is a commonly used technique, Python provides a syntax feature (called a decorator) that makes it easier to use. Consider the following as an example −

Following functions:

@decorated_func
def ordinary_function():
   print("This is ordinary function")
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equal

def ordinary_function():
   print("This is ordinary function")
decorated = decorated_func(ordinary_func)
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Improve your career

Writing decorators is difficult at first. It's not rocket science either, but it takes a lot of effort to learn and understand details that many developers never bother with. This works to your advantage. If you become the person on the team who learns to write decorators correctly and writes decorators that answer real-world questions, other developers will use your decorators. Once the hard work of writing decorators is over, using them is very simple. This can greatly increase the positive impact of the code you develop. It might even make you a master.

in conclusion

Decorators are an incredible feature that can be used for a variety of purposes. It's not just "a function or class that takes a function or class and returns a function or class".

No matter what method you use to learn to build decorators, you'll probably be excited about what you can achieve using them and how it will (no kidding) change the way you write Python code forever!

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source:tutorialspoint.com
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