Top 10 Python Applications in the Real World You Need to Know
Dynamic Typing, Built-In Data Structures, Powerful Libraries, Frameworks, Community Support are just some of the reasons which make Python an attractive language for rapidly developing any sort of application. In this article, we will see some of the areas where Python excels in application development.
The following topics are to be covered in this article of Python Applications:
- Introduction to Python
- Python Applications
- Web Development
- Game Development
- Machine Learning and Artificial Intelligence
- Data Science and Data Visualization
- Desktop GUI
- Web Scraping Applications
- Business Applications
- Audio and Video Applications
- CAD Applications
- Embedded Applications
Introduction to Python
Python is free and simple to learn. Its primary features are that it is high-level, dynamically typed and interpreted. This makes debugging of errors easy and encourages the rapid development of application prototypes, marking itself as the language to code with. Python was developed in 1989 by Guido Van Rossum and emphasizes on the DRY (Don’t Repeat Yourself) principle and readability.
With that out of the way, let’s jump straight into the Python Applications. :)
Python Applications
Python supports cross-platform operating systems which makes building applications with it all the more convenient. Some of the globally known applications such as YouTube, BitTorrent, DropBox, etc. use Python to achieve their functionality.
1. Web Development
Python can be used to make web-applications at a rapid rate. Why is that? It is because of the frameworks Python uses to create these applications. There is common-backend logic that goes into making these frameworks and a number of libraries that can help integrate protocols such as HTTPS, FTP, SSL etc. and even help in the processing of JSON, XML, E-Mail and so much more.
Some of the most well-known frameworks are Django, Flask, Pyramid. Why use a framework? The , scalability, convenience that they provide is unparalleled compared to starting the development of a website from scratch.
2. Game Development
Python is also used in the development of interactive games. There are libraries such as PySoy which is a 3D game engine supporting Python 3, PyGame which provides functionality and a library for game development. Games such as Civilization-IV, Disney’s Toontown Online, Vega Strike etc. have been built using Python.
3. Machine Learning and Artificial Intelligence
Machine Learning and Artificial Intelligence are the talks of the town as they yield the most promising careers for the future. We make the computer learn based on past experiences through the data stored or better yet, create algorithms which makes the computer learn by itself. The programming language that mostly everyone chooses? It’s Python. Why? Support for these domains with the libraries that exist already such as Pandas, Scikit-Learn, NumPy and so many more.
Learn the algorithm, use the library and you have your solution to the problem. It is that simple. But if you want to go the hardcore way, you can design your own code which yields a better solution, which still is much easier compared to other languages.
4. Data Science and Data Visualization
Data is money if you know how to extract relevant information which can help you take calculated risks and increase profits. You study the data you have, perform operations and extract the information required. Libraries such as Pandas, NumPy help you in extracting information.
You can even visualize the data libraries such as Matplotlib, Seaborn, which are helpful in plotting graphs and much more. This is what Python offers you to become a Data Scientist.
5. Desktop GUI
Python can be used to program desktop applications. It provides the Tkinter library that can be used to develop user interfaces. There are some other useful toolkits such as the wxWidgets, Kivy, PYQT that can be used to create applications on several platforms.
You can start out with creating simple applications such as Calculators, To-Do apps and go ahead and create much more complicated applications.
6. Web Scraping Applications
Python can be used to pull a large amount of data from websites which can then be helpful in various real-world processes such as price comparison, job listings, research and development and much more.
Python has a library called BeautifulSoup which can be used to pull such data and be used accordingly. Here’s a full-fledged guide to learn Web scraping with Python.
7. Business Applications
Business Applications are different than our normal applications covering domains such as e-commerce, ERP and many more. They require applications which are scalable, extensible and easily readable and Python provides us with all these features. Platforms such as Tryton can be used to develop such business applications.
8. Audio and Video Applications
Python can be used to develop applications that can multi-task and also output media. Video and audio applications such as TimPlayer, Cplay have been developed using Python libraries and they provide better stability and performance compared to other media players.
9. CAD Applications
Computer-Aided Designing is a very complicated application to make as many things have to be taken care of. Objects and their representation, functions are just the tip of the iceberg when it comes to something like this. Python makes this simple too and the most well-known application for CAD is Fandango.
10. Embedded Applications
Python is based on C which means that it can be used to create Embedded C software for embedded applications. This helps us to perform higher-level applications on smaller devices which can compute Python.
The most well-known embedded application could be the Raspberry Pi which uses Python for its computing. It can be used as a computer or like a simple embedded board to perform high-level computations.
Python has a variety of applications where it can be used. No matter what field you take up, Python is rewarding. So I hope you have understood the Python Applications and what sets Python apart from every other programming language.
If you wish to check out more articles on the market’s most trending technologies like Artificial Intelligence, DevOps, Ethical Hacking, then you can refer to Edureka’s official site.
Do look out for other articles in this series which will explain the various other aspects of Python and Data Science.
1. Machine Learning Classifier in Python
2. Python Scikit-Learn Cheat Sheet
4. Python Libraries For Data Science And Machine Learning
9. OOPs Interview Questions and Answers
10. Resume For A Python Developer
11. Exploratory Data Analysis In Python
12. Snake Game With Python’s Turtle Module
14. Principal Component Analysis
15. Python vs C++
16. Scrapy Tutorial
17. Python SciPy
18. Least Squares Regression Method
19. Jupyter Notebook Cheat Sheet
20. Python Basics
23. Python Decorator
25. Mobile Applications Using Kivy In Python
26. Top 10 Best Books To Learn & Practice Python
27. Robot Framework With Python
28. Snake Game in Python using PyGame
29. Django Interview Questions and Answers
30. What is Socket Programming in Python
31. Hash Tables and Hashmaps in Python
32. Python 3.8
34. Python Tutorial
Originally published at https://www.edureka.co on October 10, 2019.
