Python was developed in 1980 and was released in1991. Guido van Rossum developed Python. Python is a digital language of high level and general-purpose programming. The Python2.0 was released in 2000 with features like list comprehensions etc. In 2008 Python3.0 was released, but it didn’t have complete backwards-compatibility.
In January 2021, Python was ranked third in the TIOBE index for the most popularized programming language. The Python uses dynamic typing, reference counting and also cycle-detecting garbage collector for managing memory. Dynamic name resolution is also used to bind method and variable names while the program is executed.
There are many real-world applications of Python:
1. Game development
Python has the tools and settings for game development. Python was used to develop the famous game Battlefield 2 in the 2000s. Many other famous titles use Python for their large part of heavy tasks like Sims4, Eve Online, World of Tanks, Civilization IV etc.
The other few titles that use Python are Frets on Fire, Disney’s Toontown Online etc.
2. Web Development
As Python comes with a wide lineup of framework and Content Management System, it is the most famous programming language to develop a website. Web development is one of the most classic applications of Python. The examples of web development frameworks are Flask, Pyramid and Content Management Systems are Django CMS, Wagtail and Plone CMS.
There are many other benefits of using Python for web development, i.e., security, convenience in the development process etc. Python supports other web protocols like HTML, XML and FTP.
3. Artificial Intelligence and Machine Learning
Artificial Intelligence and Machine Learning are one of the main discussed topics of this decade. Python, along with many other programming languages, has increased artificial language and machine learning development.
Python’s stability and security make it a perfect programming language that supports artificial learning and machine learning.
The vast collection of Python libraries helps develop algorithms and models that lead to modern AI and ML’s functioning. Some of the popular libraries for the same are:
- Pandas-Data manipulation and analysis
- Keras -Artificial Neural Networks
- SciPy -scientific and technical computing, etc.
4. Image Processing
As there is an increase in Machine Learning, Deep Learning and Neural Network, pre-processing image tools have also increased. Python offers a host of libraries that simplify most of the Data Scientist’s initial tasks to fulfil the demands.
The popular image processing Python libraries are Scikit-Image, Python Imaging Library etc. Houdini, Blender etc., uses Python for image processing.
5. Desktop GUI
Python offers a large number of options to the developers to make a fully functional GUI. The key to preparing super fast and responsive GUI is Python’s comprehensible syntax and the modular programming approach, making the whole development process more comfortable. There is a long list of tools; some of them are PyQt, Tkinter, etc.
6. Text Processing
Text processing is one of the most common uses of Python. Text processing helps to handle a large amount of text while providing you with the flexibility to structure it at your convenience.
7. Business Application
Business applications differ from average consumer software in many ways.
a. It offers a set of unique features instead of multiple features.
b. They target a very tight-knit group of users.
Python’s best thing is that it provides high performing custom solutions, whichever it is, let it be a consumer application or a business application; Python does it all. The two powerful modular business applications are Odoo and Tryton. All the most critical aspects of the application are its security. Though the very application is developed with security, the security which Python provides has a highlight. Python excels in delivering a scalable application to help a business scale.
8. Operating Systems
Python is one of the programming languages used in developing or strengthening a part of the Linux-based operating system.
Two popular examples of Python’s use are Red Hat Enterprise’s Anaconda Installer and Ubuntu’s Ubiquity Installer.
9. Scientific and Numeric Applications
The collection of scientific tools and Python libraries includes Pandas, SciPy, and Matlotlib, which have helped scientists and researchers conclude many problems and find new things. FreeCAD, Abaqus are examples of numerical scientific applications developed by Python.
The other real-world applications of Python are:
- Data visualization and science
- Embedded applications
- Audio and video applications
- Web scraping applications
- Computer vision, etc.
Python is an extremely useful language that helps in gaining popularity among the developers of various sectors.