Decorators in Python
Decorators in Python are the strengthened designing tools in Python, although the concept of designing is regarded as the complicated one. For a newbie, the concept of decorators is puzzling, as writing a decorators program is very difficult for even an expert. The usage of decorators is straightforward but writing and its implication can make you sweat. To be well-equipped with decorators in Python, you need to have a deep insight into the functional programming concepts. Any redeemable object in Python, that can be used to enhance a function, or a class is a decorator in Python. In a Python decorator, a function or a class is passed to the decorator, and the decorator returns the resultant modified class or a function. The modified functions include calls to the original function. Inculcated in the same concept, the decorators in Python are of two distinct types:
● Function Decorators
● Class Decorators
The Decorators in Python are capable of modifying the behaviour of one function by wrapping it in another part without changing it permanently. The function in a Python decorator is an argument to the another wrapped function.
To Master Python programming language join today for certified Python Training program.
Prerequisites of Learning Decorators
It is essential to know about some concepts and primary elements before learning in detail about the decorators. All the elements in Python are referred by a variable name which acts as an identifier for each object, and function as well. This incorporates the functions, and as well as classes with distinct attributes. It is possible to assign different names to the same function object.
Example:
def star(func):
def inner(*args, **kwargs):
print(“*” * 30)
func(*args, **kwargs)
print(“*” * 30)
return inner
def percent(func):
def inner(*args, **kwargs):
print(“%” * 30)
func(*args, **kwargs)
print(“%” * 30)
return inner
@star
@percent
def printer(msg):
print(msg)
printer(“Hello”)
When two functions refer to the same object, the output produced is the same, even though they have distinct names. It is possible to pass on the function in the form of argument to another function. If you are familiar with the functions of Python, you may know this. When the primary python functions to take other functions as their arguments, then these functions are called higher-order functions.
Example:
Input
def inc(x):
return x + 1
def dec(x):
return x – 1
def operate(func, x):
result = func(x)
return result
Output
>>> operate(inc,3)
4
>>> operate(dec,3)
2
Chaining Decorators in Python
We are now well understood that a decorator in Python is a function that can take another function as an argument, and enlarge its functionality resulting in a modified function with enhanced functionality. When more than one decorator is applied in the interior of the function, then it is named as chaining decorators. While using Python programming, it is possible to implement more than one decorator in a function or class. This chaining of the decorators can be used several times as a building block, as distinctive effects involved in it form complete reusable programming. This accumulation of building blocks of the programming is well known by the name Nested Decorators in Python.
Example:
def star(func):
def inner(*args, **kwargs):
print(“*” * 30)
func(*args, **kwargs)
print(“*” * 30)
return inner
def percent(func):
def inner(*args, **kwargs):
print(“%” * 30)
func(*args, **kwargs)
print(“%” * 30)
return inner
@star
@percent
def printer(msg):
print(msg)
printer(“Hello”)
Output
******************************
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Hello
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
******************************
A function can be forwarded as an argument
A python function interchanges the information with the assistance, or arguments and parameters. A parameter is a term that refers to the declaration of a statement written in a bracket or parentheses. This declarative statement or a definition follows the name of the function. At the same time, the argument is an expression used to apply to the process. This expression is written inside the parentheses.
A function can take up multiple numbers of arguments. The objects, variables, and functions that include the same, or distinctive types can be the modes of the arguments. First-class objects in Python are the functions that play a vital role in python function decorator. The assigning of the argument doesn’t call out for the function. It takes the object of the function and modifies it to a changed name pointing out towards a similar meaning.
Functions can be defined within functions
To clearly understand, and gain in-depth knowledge of working of python decorators, it is necessary to know about the functions and their functionalities. When a function is defined inside a distinct function is stated as a Nested Function. It is a quality of a Nested Function that it is liable to access the variables of enclosing or a non-local scope. To modify the non-local functions, the scopes are to be declared explicitly with the use of a non-local keyboard. These variables in Python are accessible in reading the only format, and thus, require to be modified.
Defining a closure function Python
Sometimes, the resultant data of the function gets linked to the code in the Python, this is called as a Closure in Python language. This value in the non-local scope stays in the memory of the system even if it’s eradicated from the recent name-space. Thus, as a result, the returned function is put into working even if the original function is removed from the data.
We get closure in Python when a nested function has a value that refers to the non-local scope. To create a closure in Python, there are some criteria, that are to be satisfied, that includes the following,
● A nested function that means we must have a function that resides in another function.
● This nested function must be defined to find the value of the enclosing or non-local function.
● The non-local function must be liable to return the nested function.
The benefits of the closure are that it can avoid the use of all-over values, along with data hiding capabilities. You are liable to gain an object defined solution to the given problem. With fewer methods to be implemented in a class, closures can provide you with more diversified solutions.
Functions can return functions as well
Python decorator is capable of returning a function from the given set of the functions. Also, it can store the tasks in the form of substantial stratified assemblage and listings. This is treated generally, similar to any other variable or object. Thus, decorators in Python can define the functions and return the functions.
The function can be assigned to a variable
The resultant value of the function can be assigned to a variable. This value is in the form of an expression and can be passed on to another function as an argument.
Even though the python decorator functions are complex to use, they are well accepted due to their prominent functioning, and varied features. The decorators in the Python can be implemented on a function or even on a class.
Python is the initial step towards future technologies like Data Science, Cloud Computing, DevOps Engineering, Industry Automation and many more. To help you find the best place to learn and shape your future there are a few Python Online Certification courses. Join Today!
