Python is known for its general-purpose nature that makes it applicable in almost every domain of software development. Python makes its presence in every emerging field. It is the fastest-growing programming language and can develop any application. Here, we are specifying application areas where Python can be applied. Python is the most versatile language in the programming world, and it has applications in various domains. It helps us in taking care of our current programming task as well as lets us focus on the core functionality of Python programming languages. Talking about this Python applications tutorial, it will help both beginners and intermediates in learning and polishing their coding skills.
1) Web Applications
We can use Python to develop web applications. It provides libraries to handle internet protocols such as HTML and XML, JSON, Email processing, request, beautifulSoup, Feedparser, etc. One of Python web-framework named Django is used on Instagram. Python provides many useful frameworks, and these are given below:
- Django and Pyramid framework(Use for heavy applications)
- Flask and Bottle (Micro-framework)
- Plone and Django CMS (Advance Content management)
- Requests – An HTTP client library
- BeautifulSoup – An HTML parser
- Feedparser – For parsing RSS/Atom feeds
- Paramiko – For implementing the SSH2 protocol
- Twisted Python – For asynchronous network programming
We also have a gamut of frameworks available. Some of these are- Django, Pyramid. We also get microframeworks like flask and bottle. We’ve discussed these in our write-up on an Introduction to Python Programming. We can also write CGI scripts, and we get advanced content management systems like Plone and Django CMS.
2) Desktop GUI Applications
The GUI stands for the Graphical User Interface, which provides a smooth interaction to any application. Python provides a Tk GUI library to develop a user interface. Some popular GUI libraries are given below.
- Tkinter or Tk
- Kivy (used for writing multitouch applications )
- PyQt or Pyside
Most binary distributions of Python ship with Tk, a standard GUI library. It lets you draft a user interface for an application. Apart from that, some toolkits are available:
- Kivy – for writing multitouch applications
- Qt via pyqt or pyside
And then we have some platform-specific toolkits:
- Microsoft Foundation Classes through the win32 extensions
3) Console-based Application
Console-based applications run from the command-line or shell. These applications are computer program which are used commands to execute. This kind of application was more popular in the old generation of computers. Python can develop this kind of application very effectively. It is famous for having REPL, which means the Read-Eval-Print Loop that makes it the most suitable language for the command-line applications.
Python provides many free library or module which helps to build the command-line apps. The necessary IO libraries are used to read and write. It helps to parse argument and create console help text out-of-the-box. There are also advance libraries that can develop independent console apps.
4) Software Development
Python is useful for the software development process. It works as a support language and can be used to build control and management, testing, etc.
- SCons – for build-control
- Buildbot, Apache Gump – for automated and continuous compilation and testing
- Roundup, Trac – for project management and bug-tracking.
- The roster of Integrated Development Environments
5) Scientific and Numeric
This is the era of Artificial intelligence where the machine can perform the task the same as the human. Python language is the most suitable language for Artificial intelligence or machine learning. It consists of many scientific and mathematical libraries, which makes easy to solve complex calculations.
- SciPy – A collection of packages for mathematics, science, and engineering.
- Pandas– A data-analysis and -modeling library
- IPython – A powerful shell for easy editing and recording of work sessions. It also supports visualizations and parallel computing.
- Also, NumPy enables us to deal with complex numerical calculations.
Implementing machine learning algorithms require complex mathematical calculation. Python has many libraries for scientific and numeric such as Numpy, Pandas, Scipy, Scikit-learn, etc. If you have some basic knowledge of Python, you need to import libraries on the top of the code.
6) Business Applications
Business Applications differ from standard applications. E-commerce and ERP are an example of a business application. This kind of application requires extensively, scalability and readability, and Python provides all these features. Oddo is an example of the all-in-one Python-based application which offers a range of business applications. Python provides a Tryton platform which is used to develop the business application.
7) Audio or Video-based Applications
Python is flexible to perform multiple tasks and can be used to create multimedia applications. Some multimedia applications which are made by using Python are TimPlayer, cplay, etc. The few multimedia libraries are given below.
- QT Phonon
8) 3D CAD Applications
The CAD (Computer-aided design) is used to design engineering related architecture. It is used to develop the 3D representation of a part of a system. Python can create a 3D CAD application by using the following functionalities.
- Fandango (Popular )
9) Enterprise Applications
Python can be used to create applications that can be used within an Enterprise or an Organization. Some real-time applications are OpenERP, Tryton, Picalo, etc.
10) Image Processing Application
Python contains many libraries that are used to work with the image. The image can be manipulated according to our requirements. Some libraries of image processing are given below.
In this topic, we have described all types of applications where Python plays an essential role in the development of these applications. In the next tutorial, we will learn more concepts about Python.
11. Artificial Intelligence and Machine Learning
The IT industry went far beyond science fiction ideas, and our future is moving towards Artificial Intelligence. People are keen to move to technologies where machines can mimic human behaviors, and machines are automating most of the human work. There is also a need to process and analyze huge volumes of data. Statistically speaking that Python is the most popular language for Artificial intelligence and Machine Learning. The several libraries and frameworks for Artificial intelligence are listed below.
Programming in Python is easy when you compare it with other languages. It has easy syntax and it offers concise solutions for implementing all types of functionalities. This is the main reason why Python can be applied in prototyping stages of software development. With many functionalities to offer, Python lets you develop a prototype of applications faster. Many organizations and firms use Python at the prototyping stage of a project.
13. Database Access
With Python, you have:
- Custom and ODBC interfaces to MySQL, Oracle, PostgreSQL, MS SQL Server, and others. These are freely available for download.
- Object databases like Durus and ZODB
- Standard Database API
Other Python Applications
These are some of the major Python Applications. Apart from what we just discussed, it still finds use in more places:
- Console-based Applications
- Audio or Video-based Applications
- Applications for Images
- Enterprise Applications
- 3D CAD Applications
- Computer Vision (Facilities like face-detection and color-detection)
- Machine Learning
- Web Scraping (Harvesting data from websites)
- Artificial Intelligence
- Data Analysis (The Hottest of Python Applications)
Now we know Python is everywhere and we have seen this in DataFlair’s Python Applications article. Moreover, we learned that the applications of Python lets us develop a web application without too much trouble; it helps to draft a user interface for an application.
And not so surprising that Python finds its place in the scientific community. We have also seen its application in education and business. We have learned how Python slack in network programming as well as we have thrown light on some more Python applications.