Understanding Python Decorators, with Examples

This article will help you understand the concept of decorators in Python programming and how to use them best. We will cover what Python decorators are, what their syntax looks like, how to recognize them in a script or framework, and how to apply them yourself.

The function decorator in Python is just a function that takes another function as an argument, extending the function of the decorated function without changing its structure. The decorator wraps another function, enhances its behavior, and then returns it.

The decorator concept in Python helps keep the code DRY (Don't Repeat Yourself). Function decorators avoid unnecessary duplication in the code base, because some duplicate code snippets can be combined to form a function decorator. As you advance in development with Python, decorators can help with analysis and documentation. They are also critical to setting up verification and runtime checking.

In what follows, I assume you have a basic understanding of Python functions and programming, and you have at least Python 3.8 installed on your device.

Key Points

• A Python decorator is a function that takes another function as an argument, which enhances its functionality without changing its structure. They help keep code DRY (don't repeat yourself) by avoiding unnecessary duplication and can be used for analysis, logging, validation, and runtime checking.
• In Python, a decorator function is defined by an external function that receives function parameters and a nested function that wraps the decorating function inside the external function. Decorators are easily identified by the "@" prefix before the decorator function. Parameters can be passed to the wrapper function and then to the decorated function.
• Decorators can be chained in Python, meaning that a function can be decorated with multiple decorators. This is done by stacking one decorator on top of another. Practical use cases for Python decorators include time logging, memory, and built-in Python decorators like @classmethod, @staticmethod, and @property.

Things to know before delving into Python decorators

In Python, functions are first-class citizens, meaning they can receive parameters or be passed as parameters. In order to fully grasp the concept of a decorator, you need to know the following points.

The

function is an object, which means it can be assigned to another variable

def greet():
    print("Hello John")

greet_john = greet
greet_john()
>>>
Hello John

Always remember that in Python everything is an object. The same way you assign a value to a variable, a function can also be assigned to a variable if necessary. This is important when you learn about decorators.

Function can return

from another function

def greet():
    def greeting_at_dawn():
        print("Good morning")

    return greeting_at_dawn

salute = greet()
salute()
>>>
Good morning

Inner functions in Python can be returned from external functions. This is part of the functional programming concept you will encounter.

Functions can be passed as parameters of another function

def greet_some(func):
    print("Good morning", end=' ')
    func()

def say_name():
    print("John")

greet_some(say_name)
>>>
Good morning John

The function that receives function parameters is called a higher order function.

Be sure to keep the above points in mind when learning to implement decorators and use them effectively in Python programs.

Python decorator operation mechanism

A simple decorator function starts with function definition, decorator function, and then nested functions within external wrapper functions.

Always keep the following two points in mind when defining a decorator:

1. To implement a decorator, define an external function that receives function parameters.
2. Nest a wrapper function in the external decorator function, which also wraps the decorator function.

The following is what the most basic decorator function looks like in the following code snippet:

def greet():
    print("Hello John")

greet_john = greet
greet_john()
>>>
Hello John

View the code above, the external function increase_number (also known as a decorator) receives the function parameter func. increase_by_one is a wrapper function that contains the decorated get_number function. The decorator is assigned to another variable. This is what the decorator syntax means when using Python decorator. However, there is an easier way to represent a decorator.

It is easy to recognize a simple decorator function when it starts with the @ prefix and combines the decorating function below it. The previous example can be refactored as follows:

def greet():
    def greeting_at_dawn():
        print("Good morning")

    return greeting_at_dawn

salute = greet()
salute()
>>>
Good morning

These examples show that the decorator extends the functionality of its function parameters.

Decorator function with parameters

In some cases, you may need to pass parameters to the decorator. The solution to this problem is to pass the argument to the wrapper function and then pass it to the decorated function. See the following example:

def greet_some(func):
    print("Good morning", end=' ')
    func()

def say_name():
    print("John")

greet_some(say_name)
>>>
Good morning John

Passing parameters to internal or nested functions makes them more powerful and robust because it provides more flexibility to manipulate decorated functions. Any number of parameters (*args) or keyword parameters (**kwargs) can be passed to the decorated function. *args allows collection of all positional parameters, while **kwargs is used for all keyword parameters required during a function call. Let's look at another simple example:

def increase_number(func):
    def increase_by_one():
        print("incrementing number by 1 ...")
        number_plus_one = func() + 1
        return number_plus_one
    return increase_by_one

def get_number():
    return 5

get_new_number = increase_number(get_number)
print(get_new_number())
>>>
incrementing number by 1 ...
6

In the example above, *args takes the positional parameters as tuples to form an iterable object, while **kwargs forms a keyword parameter dictionary.

Multiple decorators or chain calls in Python

When using function decorator in Python projects, there are several options to explore. Another use case is to link a decorator (two or more) to a function. A function can be decorated with multiple decorators (multiple decorators), which is achieved by stacking one decorator on top of another, in the order irrelevant. Regardless of the order in which multiple decorators are stacked, you will get the same output as shown in the following example:

def increase_number(func):
    def increase_by_one():
        print("incrementing number by 1 ...")
        number_plus_one = func() + 1
        return number_plus_one
    return increase_by_one

@increase_number
def get_number():
    return 5

print(get_number())
>>>
incrementing number by 1 ...
6

Practical use cases for Python decorator

A very popular way to use decorators in Python is as a time logger. This helps programmers understand how long it takes to execute a function to measure efficiency.

Memorization is another cool way to use decorators in Python. When the calculation is performed later, the results from repeated calls to the function can be easily remembered without any changes. You can simply use the decorator to memorize the function.

Built-in Python decorators like @classmethod, @staticmethod, and @property are very popular in Python's OOP decorator mode.

Conclusion

Python decorators enforce the DRY principles of software engineering because they are used as reusable code. Think about how many Python functions you can refactor into decorators. In this article, we explore different forms of decorators. There are also class decorators, although we don't cover them here.

Decorators make it easier to add additional functionality to simple functions, methods, or classes without changing their source code while keeping the code DRY. Try decorating functions yourself to better understand the decorator pattern.

FAQs about JavaScript Decorators

What is a JavaScript decorator?

JavaScript Decorator is a design pattern and a feature introduced in ECMAScript 2016 (ES6) and later versions of JavaScript. It allows you to modify or enhance the behavior of a function, method, or class by applying comments or metadata to it. Decorators are commonly used in various JavaScript libraries and frameworks, such as Angular and MobX. Decorators are usually implemented as functions that wrap or "decorate" objective functions or classes. They are used to add functionality or change the behavior of a target without changing its core code. Decorators can be applied to functions, methods, or classes, and they are indicated by the @ symbol followed by the name of the decorator.

Why do we need JavaScript decorator?

Decorators in JavaScript are a valuable addition to the language for the following reasons: They promote modularity and code reusability by allowing developers to separate cross-cutting concerns from the core logic of functions and methods. This promotes a cleaner code base by reducing confusion and enhancing readability, making the code easier to maintain and understand. Decorators play an important role in adhering to the principle of separation of concerns, as they allow you to separate aspects such as security, logging, and configuration from core application logic. Decorators bring consistency to your code base by ensuring that specific behaviors or policies are applied consistently to functions and methods. They provide a flexible way to configure and customize the behavior of functions, allowing for easy changes or extension of functionality without modifying core code. By supporting aspect-oriented programming (AOP), decorators help systematically address cross-cutting concerns, resulting in cleaner, more organized code. Decorators are also increasingly adopted by third-party libraries and frameworks, making them a must-have skill for efficient use of modern JavaScript tools. All in all, decorators improve code organization, readability, maintainability, and scalability, making them valuable assets for JavaScript developers.

What is the difference between a Python decorator and a JavaScript decorator?

Python and JavaScript decorators share the concept of modifying function or method behavior, but differ in syntax and usage. Python uses the @decorator_function syntax and can be applied to functions and classes for various purposes. JavaScript decorator uses the @decorator syntax and is mainly used for classes, methods, and properties. Python decorators are more versatile, while JavaScript decorators are class-centric and were introduced as part of ECMAScript 2016.

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