Top 14 Applications of Python

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Python Course for Beginners With Certification: Mastering the Essentials
Python Course for Beginners With Certification: Mastering the Essentials
by Rahul Janghu
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Python Course for Beginners With Certification: Mastering the Essentials
Python Course for Beginners With Certification: Mastering the Essentials
by Rahul Janghu
Start Learning
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Python is a widely used general-purpose, high-level programming language. Python has a vast amount of libraries and framework that helps achieve respective tasks.

Let's take a look at top Python Applications in real world. These features of python have encouraged developers all around the globe to create some helpful libraries and frameworks that extend the applications of Python in almost every field. This article explores top 14 Python applications.

1. Web Development

Web development is a huge domain, and Python is one of the most preferred languages.

Python can be used in web development to create the backends for websites.

There are two parts of a website:

  1. Frontend: All the part of the website that is visible to you
  2. Backend: All the behind the scene work that is performed on your request

A simple example to understand this can be Google.

When searching anything on Google, all the results we see are called the Frontend, and the back end does the work that Google does to bring those results. You can only appreciate the backend but cannot see it (unless you work at Google, lol)

The most popular frameworks of Python for creating backends are:

  • Flask
  • Django

Both of these allow the creation of a fully functional website. They are easy to learn as they have great documentation.

Many big websites like Instagram, Netflix, and Spotify use Python to develop their product.

2. Developing Games

Python can be used for game development. It can be used to create both 2D and 3D games. One of the most popular modules for 2D game development is PyGame. It is simple, easy to learn, and has a huge community.

We can use it to create games like Flappy Bird, Tic Tac Toe, Minesweeper, etc.

Here is an example of a minesweeper game made with Pygame.

Not only 2D games, we can also make 3D games. For this, PySoy can be used.

Some famous games that used Python include Battlefield 2, Pirates of the Caribbean Online, The Sims 4, World of Tanks, Vega Strike, etc.

3. Creating GUI Apps

Python can run on almost all platforms, making it a great choice to develop Graphical User Interface (GUI) based applications.

Tkinter, PyQt, and Kivy are some of the most famous libraries for this purpose. Tkinter comes as an inbuilt module with Python by default. The other two can be installed very easily. Some famous applications made with Python are Anki and Dropbox.

4. Performing Complex Calculations

This is yet another field where simple syntax and powerful libraries help.

There is a need for many complex calculations that need to be performed quickly in the research field. Many mathematicians and computer scientists have created libraries like SciPy and NumPy that enable us to do complex mathematical calculations very quickly.

Some of the most famous libraries used for performing complex mathematical calculations are

  • SciPy is used for scientific computation
  • Numpy supports the use of large multidimensional arrays and matrices
  • Pandas is the most famous data analytics library

5. Artificial Intelligence and Machine Learning

AI and ML are buzzwords nowadays with huge potential, and many people are getting into these, and surely Python does not want to lag.

This field includes the use of libraries from different domains because, in AI and ML, there are many tasks like data collection, data analysis, and advanced scientific calculation.

Some most commonly used libraries are:

  • TensorFlow by Google
  • Pytorch by Facebook
  • Keras
  • Scikit Learn

These libraries are extremely powerful, and many big companies use them.

You can easily start learning these by following the official documentation by visiting their website.

6. Software Development

Python has many packages which aim to simplify some task or the other. Python is used for development and as a support language for management and testing.

The most popular tools and libraries for this purpose are SCons, Buildbot, Trac, etc.

7. Business Applications of Python

Python is used in business/enterprise applications. These are very different from standard applications. These applications focus mainly on readability, extensibility, and scalability. Another important point in this domain is the capability to integrate with legacy systems.

Python can handle these things easily with its useful features like performance, flexibility, cross-platform support, and scalability.

Examples of these tools include Oddo and Tryton.

8. Human-Machine Interaction

As everything becomes digital, interacting with machines has become a necessity rather than a skill. It is very easy to find Python being used in different fields for interacting with machines.

The steep learning curve of Python makes it a great choice in fields where programming is not the main skill.

An example of this scenario is that Mechanical Engineers are taught Python, which helps them create and test various complex projects. This includes making a digital circuit, a model of a machine, or making a machine using Raspberry Pi or Arduino.

9. Audio and Video-based Applications of Python

Python has many packages which can be used for multimedia applications. TimPlayer and Cplay have been developed using Python.

Some packages that can be used for this purpose are wave, audioloop, gstreamer, pyglet

10. Inspiration for developing other languages

The popularity and architecture of Python have served as an inspiration for many new programming languages like

  • Cobra
  • CoffeeScript
  • Golang
  • Kotlin
  • Swift

These languages are powerful and have a Python-like syntax.

11. Scraping Websites

Python is the first choice for extracting and handling huge amounts of data from websites. Extracting data from websites may include applications in various fields like research, price comparison, and job listing.

Some popular libraries and frameworks which are commonly used for this purpose are

12. CAD Applications of Python

CAD or Computer Aided Designing uses computers to help create, modify, analyze, and optimize a design. This is heavily used in automobiles, weapons, and the aerospace industry.

Python supports a wide range of CAD applications like Fandango, and FreeCAD.

13. Image Processing and Graphic Design Applications of Python

Python allows us to work with images. We can process the images to make them beautiful or analyze them to extract some useful information.

OpenCV and Pillow are two modules that allow us to do almost anything with the images.

One of the most famous applications of OpenCV is OCR (Optical Character Recognition), which uses Machine Learning to detect written text in images.

14. Writing Scripts

A Python script is a collection of commands stored in a file designed to be executed like a program. The main idea is that this file can be executed from the command line. Generally, a script focuses on accomplishing some specific task.

Python is the most preferred scripting language, thanks to its runtime nature.

Many types of scripts can be written with Python.

Some common use cases are:

  • Scraping websites and saving their data in Excel or any other file type.
  • Automation like sending emails, and converting images.
  • Writing scripts to automate tasks in Adobe Photoshop, and Blender.
  • Performing actions on Excel files.
  • Creating PDFs or editing them.
  • Entering bulk data on a website.
  • Writing tests for your code.

You can write Python scripts wherever you see the opportunity to automate anything.


  • Python is a very versatile language and can handle almost any requirement you throw at it.
  • Some of Python's applications and domains are Web Development, Software Development, Game Development, AI/ML, and so on.
  • The most famous frameworks of Python used for backend development are Flask and Django.
  • Some most commonly used libraries are TensorFlow, Pytorch, Keras and so on.