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Top 7 Python Features Every Python Developer Should Know

Last updated:
23rd Jun, 2023
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Top 7 Python Features Every Python Developer Should Know


Python has gained a lot of focus in the past few years and the reason for that is the salient features offered by python. It supports object-oriented programming, procedural programming approaches, and provides dynamic memory allocation. Let’s explore them!

Overview of Python

Python a programming language that is easy to read and write. It is high-level and interpreted, which means it can be used for various purposes. Python helps developers to write shorter code by using its syntax and features, and it can be used to create simple or complex applications. Python also supports a wide range of features, including basic support for strings, numbers, and tuples as well as advanced object-oriented concepts. With Python, developers can code without having to make complex low-level decisions.

Benefits of Python Programming Language

Before looking at the characteristics of Python, let’s understand the benefits it provides:

  • Easy to Learn

Python is an easy-to-learn language and has a basic syntax which can be understood by beginners as well. It requires less code to implement the same functionality than other programming languages such as Java, C++, and JavaScript. Plus, it is backed up with a large community of developers constantly improving the language and adding new features daily.

  • Object-oriented Programming

One of the features of Python programming language supports object-oriented programming, which is a great benefit and helps developers to create maintainable applications and define objects that contain data in a structured form. This feature allows Python developers to easily reuse code across multiple projects instead of having to write similar code for each project separately.

  • Simple Syntax

The syntax for Python is simple and easy to understand. It is not like other programming languages that require complex coding structures and long lines of code. Python also provides an interactive environment which makes it much easier for developers to test their code in real-time.

  • Powerful Libraries

Python has a wide range of libraries. These can be used by developers to perform various tasks such as data manipulation, web scraping, string processing, etc. These libraries allow developers to quickly build applications without spending too much time writing the code from scratch.

  • Versatile Language

Python can be used for developing different types of applications such as web apps, desktop applications and mobile applications. This feature makes it a highly versatile language and allows it to be used across multiple platforms with just minor modifications required for each platform.

  • High Performance

Python is a high-performance language and can be used for computationally intensive tasks such as scientific computing, machine learning, etc. It is also well-suited for parallel computing and can scale up to large clusters with ease.

  • Community Support

Lastly, Python has a large and huge community of developers who are constantly helping each other to solve complex coding problems and improving the language on a daily basis. This helps developers to find solutions quickly and helps them become better at their craft.

Next, let’s move on and look at Python features and understand why it is so popular. 

Why Python?

First things first, Python is a high-level, dynamic, and mainly it’s a free open source. Also, Python supports object-oriented programming the same as java, if not we can continue with procedural-oriented programming.

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Easy Peasy and Fun

Python is a high-level language, and easy to learn with good readability when compared to other programming languages. One can learn Python basics in less time because of its developer-friendly environment.

Right from the readability to the syntaxes python is easy, because of its syntax similar to English we can understand the code up to an extent without any prior knowledge of python. Also, python syntax is very simple and short which is one of a unique feature.

Open Source and OOP

Python is free and anyone can download it from their official website. Since it is open-sourced we can get the source code. It also supports object-oriented programming along with the concepts of classes, inheritance, encapsulation.

class OOP: 
    def __init__(self, name): #constructor = name 
    def fun(self): #member function
        print('from constructor,',
class Inherit(OOP): #inheritance in python
    def fun(self): 
        print("function in inherited class")
p=OOP('hey there') #prints "from constructor, hey there" 
p1=Inherit() #prints "function in inherited class"

The above snippet shows the OOP concepts in python.

A class in python is declared using the “class” keyword and unlike in java constructor is not called with the class name instead, it is called with __init__(). And the inheritance is performed by just mentioning the parent class in the parentheses of the child class.

GUI Programming and Extensibility

Python also supports Graphical User Interface programming with modules like Tk, PyQt4, PyQt5, etc. One of the fun features in Python allows you to write some of the Python codes in other languages like c++/java which is known as the extensibility feature. It is also a platform-independent language like java, where we can run the same code on all platforms.

from tkinter import *
master = Tk() 
var1 = IntVar() 
Checkbutton(master, text='type1', variable=var1).grid(row=0, sticky=W) 
var2 = IntVar() 
Checkbutton(master, text='type2', variable=var2).grid(row=1, sticky=W) 

Above snippet is a basic example of GUI programming in python


Tkinter is one of a useful library for GUI programming in python.

Read: Python Applications in Real World

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In the previous feature extensible we came to know that other language codes can be used in python. And now, there is something called Embeddable which allows us to put python code in other languages source code like c++. Now, this is an interesting feature that enables the users/developers to harmonize scripting capabilities in other language source codes.

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Library Support and Dynamically Typed

Python has a wide range of library support which is one of the reasons for a spotlight on python in the data science domain. Libraries like matplotlib, seaborn, NumPy, TensorFlow, Pandas, etc are a few of the main libraries for data science in python.

One of the beautiful features of python is it is a dynamically typed language, where we don’t need to specify the type of a variable at the time of declaring it. Which makes it stand out of all other programming languages.


Here the variable ‘n’ is initialized without specifying the data type and later the same variable is used for storing a variable, this is known as the dynamically typed feature and the print statement is as simple as “print()” unlike other programming languages.

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Also Read: Python Project Ideas & Topics

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Built-In Data Structures

Python contains a fair number of built-in data structures like lists that are equivalent to arrays, dictionaries to store key-value pairs, tuples to create immutable arrays. It also has predefined availability of stack and queue in the collections library.

print(dictionary) #prints {"key1":"value1","key2":"value2","key3":"value3"}

The above snippet demonstrates data structures in python.

Lists in python are mutable and can contain entries of different data types which is a unique feature and it also has some predefined methods like sum(), len(), min(), max(), etc. Tuples are a unique data structure in python which are immutable and has all the methods which are supported by lists.

And finally, dictionaries are used to maintain entries of the type key-value pairs, where the datatype of keys and values need not be the same which is an excellent feature in python. Dictionaries also have predefined methods like values(), keys(), etc.

Interpreted Language

Languages like c/c++/java need the code to be compiled before the execution, which internally converts the main code into machine-level code also known as byte code. But in python, there is no need for compiling the code before running.

Meaning that Python has no need to perform gymnastics like connecting to other libraries or packages for compiling.

Sequential execution is the method followed by Python while execution, which is why it is said to have an Interpreted feature and a developer-friendly environment. But the line-by-line execution makes it a little slow when compared to java/c++. However, it can be ignored before the features and library support provided by Python.

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We have seen some of the salient features, libraries offered in python. Also, we have discussed what made python stand out from other languages. So cheers all you now is learning python is simple and essential, start exploring, and have fun with the features of python.

It would worth every second of your hour if you go for the extra mile for the language which has features like object orientation, extensibility, embeddable, Interpreting, readable, portable, and of course easy. 

If you are curious to learn about python, data science, check out IIIT-B & upGrad’s PG Diploma in Data Science which is created for working professionals and offers 10+ case studies & projects, practical hands-on workshops, mentorship with industry experts, 1-on-1 with industry mentors, 400+ hours of learning and job assistance with top firms.


Rohit Sharma

Blog Author
Rohit Sharma is the Program Director for the UpGrad-IIIT Bangalore, PG Diploma Data Analytics Program.

Frequently Asked Questions (FAQs)

1What professions can people get into after learning Python?

Python is one of the most widely used programming languages and is opted by many companies and businesses. After learning Python, one can choose a career in Machine Learning, Data Analysis, Web Development, Mobile Application Development, Desktop Application Development, Automation, and the Internet of Things. All of these fields make direct or indirect use of Python. The job profiles in these fields are Software Engineer, Python Developer, Research Analyst, Data Analyst, Data Scientist, or Software Developer.

2Which industries use Python the most?

Many industries use Python since it is easy to learn and use. Most insurance companies make use of Python along with machine learning to provide business insights. The retail and banking industry uses Python for flexible data transformation and manipulation. Python is also used to meet the software system deadlines in the aerospace industry. The finance industry uses Python and data mining to discover cross-sell possibilities, and the business services industry uses Python to get API access to financial data. The hardware industry uses Python for network administration automation, and the healthcare industry uses it to predict illness prognosis. Along with this, Python is used for web development and for updating old applications with software.

3What is the average salary of professionals learning Python?

The compensation is determined by the level of your skills and experience in the industry. The greater the experience, the greater will be the income. Being one of the most in-demand languages, businesses are searching for exceptional individuals who are good at Python. It gives beginners a competitive advantage, while it is the most excellent method for expert developers to build up and provide add-on services to clients or attract high-profile corporations with outstanding compensation. The average salary for python professionals with 1-3 years of experience is nearly 2-9 LPA. With increased experience, the salary of python learners goes up, and professionals with 4-8 years experience can earn up to 8-24 LPA. Professionals who have more than eight years of experience in Python earn more than 16 LPA.

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