If you’ve ever written even a single line of Python code, you’ve already worked with a Python object: whether you realized it or not.
Objects lie at the heart of Python programming, and give it the ability to be not only elegant in nature, but flexible in design. Right from data to functions to classes – Python considers them all as objects.
But what does that exactly mean? And how does that affect how you work with the programming language?
In this guide, let’s help you figure out exactly that.
This will also serve as an important foundation before you embark on any data science course.
What is a Python Object?
A very straightforward and yet powerful feature that is at the heart of the Python design is that everything is an object in Python. However, when you ask what is object in Python, then by very simple means it can be interpreted as follows:
A Python object is a container that bundles two essential components:
- State: This refers to the data the object holds, often called attributes.
- Behavior: These are the actions the object can perform, known as methods.
So, creating a variable in Python automatically creates an instance of a class. And that is precisely what a Python object is!
Take this simple line of code:
x = 5
On the surface, it looks like x is just holding a number. But under the hood, x is a fully-formed Python object of the built-in int class. That means it comes with several built-in methods and properties you can use. For example:
print(x.bit_length()) # Output: 3
In this case., bit_length is a method of int class. The approach is to determine the number of bits necessary to effectively present the number in its form of binary representation. You can observe the fact how even the lowest-level entities of the world of programming, i.e. the variables, turn out to be the objects in Python under the hood.
This leads us to an important conceptual answer to the question, “Is Python object oriented?”
Let’s take a closer look at that question – is Python object oriented?
Watch:#49 Python Tutorial for Beginners | Class and Object
Is Python Object-Oriented?
The simple answer is – yes, Python is object-oriented.
The complex answer is – it’s object-oriented in its own unique, flexible way. Unlike some strictly object-oriented languages like Java or C++, Python supports multiple paradigms. These include procedural, functional, and object-oriented programming (OOP).
Because of this, it’s safe to say that Python is object-oriented, but not only that!
What makes Python especially powerful is that OOP is built into its core. Here’s how:
- You define and work with you own classes and objects.
- You can reuse existing classes and use their code using inheritance.
- Your Python objects are capable of being private and hiding their internal state from the global environment through encapsulation.
- Your Python objects can have varied behaviors as per your context and the class they’re being used with, even if they share the same method name..
Here’s a quick OOP example:
class Car:
def __init__(self, brand):
self.brand = brand
def drive(self):
print(f”{self.brand} is driving!”)
my_car = Car(“Toyota”)
my_car.drive() # Output: Toyota is driving!
In this case, my_car is a Python object of class Car. You’ve just built a mini data model using object-oriented principles!
Why Are Python Objects Important?
Python objects are important because they quite literally form the backbone of the language and everything you do based on it.
- All things are objects: Integers, lists, functions, modules, classes themselves are all objects.
- Efficiency in memory: All objects are accessed through references, rather than through copies, which speeds up and makes memory efficient.
- Customizability: through classes, you can specify the exact types of objects you wish to deal with, making it possible to write reusable, modular programs.
So, no matter your field of work. As long as you’re operating on Python, you are working with Python objects to manage complexity with ease!
Watch: OOPs in Python | Understanding OOPs Concepts
Object Lifecycle in Python
Every object in Python has a lifecycle:
- Creation: when created out of a class.
- Usage: the calling of methods or accessing data.
- Destruction: the object is no longer being referred to and is cleaned-up by the garbage collector of Python.
Here’s a quick summary of the types of objects available in Python.
| Type | Description | Examples | Use Cases |
| Built-in Objects | Predefined types provided by Python. Ready to use with built-in functionality. | int, float, bool, str, list, dict, set | Arithmetic, text manipulation, data storage, iteration |
| User-defined Objects | Custom objects created using class. Reflect complex or real-world structures. | class Account, class ReportGenerator | Modeling financial systems, data structures, AI models |
Understanding this cycle helps you manage memory and debugging more effectively, especially when building larger applications.
Final Thoughts
The real power of Python appears when you begin doing more than writing scripts; you have to think in objects. Knowing the nature, behaviour, usage, as well as development of Python objects will not only better your skills as a coder, it will open the door to the world of highly proficient fields of work such as data analytics, automation, and financial analysis.
If you’re looking to expand your understanding and knowledge of Python, and see work on its real-world applications, check out the Postgraduate Financial Analysis Program. This state-of-the-art data science course, developed by Imarticus, provides you with the appropriate theoretical and practical knowledge to get going in the world of data science!
Frequently Asked Questions (FAQs)
1. What is a Python object and how is it different from a variable?
In Python, an object is an instance of a class which has attributes (data) and functions (methods). A variable is simply just a pointer of an object.
2. Is Python object-oriented or something else?
Python is object-oriented at its core, but differs from traditional object-oriented programming languages. Python is more flexible than them, in that it also supports alternative paradigms like procedural and functional.
3. Are functions and classes also Python objects?
True, everything is an object in Python, even functions and even classes themselves. It is possible to pass them as arguments, or even in other functions by defining them.
4. How do I know which Python object I’m working with?
You can call the inbuilt function type() along with the object name to get the type of the object. So, type (41) will return class int, and so on.
5. Why is understanding Python objects important in data science?
Data in Python is nearly always organized as an object – such as DataFrame in Pandas or Array in NumPy. An understanding of how Python works behind its objects enables you to create better, faster, and readable code.