Welcome, coding enthusiasts! Today, we are going to unravel the often-misunderstood concept in the world of Python programming – Python Closures. This tutorial aims to make you grasp this concept with ease, as we simplify and demonstrate it with engaging examples and neat code snippets.
If you have been dabbling in python but have often stumbled upon the term ‘Closure’ with only a vague idea of what it represents, then you are at the right place. Buckle up because we are about to make your python journey much smoother!
Table of contents
What is a Python Closure?
A Python closure is a function object that has access to variables from its enclosing lexical scope, even when the function is called outside that scope. This means, a closure function can remember and have access to variables that were present in the environment where it was created.
What are Closures used for?
Closures come handy in implementing data hiding and encapsulation, a crucial principle in object-oriented programming. They can also be utilized to code decorators, a powerful tool in Python used for modifying or enhancing functions without changing their source code.
Why learn about Closures?
Understanding closures in Python leads to cleaner, more efficient code. It can broadly enhance your understanding of how functions and variables interact in a Python environment. Furthermore, deeper awareness of closures is essential if you dream of becoming a seasoned Python developer – it’s a concept you can’t afford to skip!
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Python Closure – The Basics
Let’s begin with the basics! A Python closure requires a nested function (function within a function), reference to the variable from the outer function in the nested function, and the outer function must return the nested function.
def outer_function(text):
message = text
def inner_function():
print(message)
return inner_function
my_func = outer_function('Hello, World!')
my_func()In this example, outer_function is the outer enclosing function that takes one parameter text. It defines another function inner_function within its body that doesn’t take any parameters and simply prints the value of the variable message. Notice how outer_function returns the inner_function?
What do you think will happen when we call my_func()? Yes, it prints ‘Hello, World!’ But wait, weren’t we calling inner_function() outside its scope, yet it still had access to the variable message? That’s our closure!
Python Closure with Parameters
What if we want to use parameters within our inner function? Easy-peasy. Here’s how:
def outer_function(text):
message = text
def inner_function(name):
print(f'{message}, {name}!')
return inner_function
my_func = outer_function('Hello')
my_func('John')In this code, inner_function now takes an additional parameter name. When we call my_func(‘John’), it prints ‘Hello, John!’. The inner function still has access to message from the enclosing function’s environment.
Global Variables and Python Closure
Python closure not only provides access to variables from its immediate lexical scope, but also to variables from global scope:
global_var = 'Hello, World!'
def outer_function():
def inner_function():
print(global_var)
return inner_function
my_func = outer_function()
my_func()Here, there aren’t any local variables in the outer_function. The nested function inner_function refers to the global variable, and still gets access to it when we call my_func().
Python Closures with Objects
Python closure can also interact with objects. Let’s delve into this with an example:
class Greeting:
def __init__(self, message):
self.message = message
def create_closure(self):
def inner_function(name):
print(f'{self.message}, {name}!')
return inner_function
Object_Greet = Greeting('Hello')
my_func = Object_Greet.create_closure()
my_func('John')In this example, the function create_closure within the class Greeting is a closure function that has access to the class object variable message even from outside the function’s scope.
Python Closure – Modify Outer Function Variables
You can modify variables from the outer function within a closure in Python with the use of the nonlocal keyword:
def outer_function(text):
message = text
def inner_function(name):
nonlocal message
message += ', ' + name
print(message)
return inner_function
my_func = outer_function('Hello')
my_func('John')The nonlocal keyword allows us to assign values to non-global variables referenced in the enclosing scope. Therefore, when we call my_func(‘John’), it prints ‘Hello, John’.
Python Closure – Why use it?
We see closures being used in Python’s built-in decorators like @property, @staticmethod, and @classmethod, among others. Being part of Python’s syntactic sugar, closures are incredibly useful to understand when using any type of function decorators.
Python Closure – Lasting Effects
Beyond the scope of the function, closures can persist their internal state. Because of this, they are widely used to create object factories or function factories. In the example below, we have created a very simplistic function factory:
def power_factory(n):
def nth_power(x):
return x ** n
return nth_power
square = power_factory(2)
cube = power_factory(3)
print(square(5))
print(cube(5))Here, we curate functions for calculating the square and the cube of a number using the power_factory function, thereby creating function factories.
Closures – they aren’t as complicated as they first seem, are they? From understanding the basics, using parameters, global variables, interacting with objects, modifying outer function variables, to understanding the applicability and lasting effects of Python closures, we hope that this post paves the way for you to write cleaner, more efficient Python code!
Happy coding!
Where to Go Next?
You’ve now got a firm grasp on Python Closures. Armed with this understanding, higher-level concepts in Python such as decorators will now become simpler. But don’t let your journey stop here. Python has a vast ocean of potential and is used extensively in web development, data science, artificial intelligence, machine learning, and much more.
How do you continue exploring these paths? We, at Zenva, have curated the ideal roadmap for you – our Python Mini-Degree. It’s an expansive, comprehensive program designed to take you from Python beginner to Python pro, equipping you with the ability to develop a multitude of projects and applications.
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The Python Mini-Degree offered by Zenva Academy is a collection of varied Python courses – all geared towards helping you understand and master Python coding, right from the basics to the subtle nuances. The program covers a wide array of topics with engaging, practical, project-based courses that accommodate different skill levels.
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Final Thoughts
We hope you enjoyed our tutorial on Python Closures. It’s now your turn to apply this knowledge and start creating. Remember, the secret to getting ahead is getting started. So dive into learning, keep coding, create your own amazing projects, and have fun in the process!
Your Python programming journey is only beginning. Let’s conquer the Python world, one step at a time!
Conclusion
Understanding concepts like Python Closures can truly transform your journey with Python. It paves the way for cleaner, more efficient, and more advanced code and gives you an edge in your professional journey. As with any other programming concept, the best way to master Python closures is to practise, practise, and practise.
Why not get started right away? Immerse yourself in our Python Mini-Degree and get hands-on experience with Python and its many applications— whether it is web development, data analysis, artificial intelligence or game creation. Equip yourself with this powerful language and prepare to take the tech world by storm. Happy programming!
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