Python is one of the most widely used high-level programming languages for data science and coding. Nearly every development related to Data Science can be programmed with Python, an open-source, general-purpose programming language. It also includes structural, object-oriented, and functional programming features.
Python has a user-friendly syntax that is great for writing readable code used for complex software development processes for smooth running test-driven application development, data analytics, and machine learning. It runs on every operating system, such as Windows, iOS, and Linux.
This makes it an ideal programming language for developing various applications, including gaming apps, web apps, enterprise-level applications, image processing, text processing, etc.
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The Most Popular Python Applications
Python as a programming language has received exponential fame in the world of Machine learning, artificial intelligence, and data science.
We have compiled a list of some of the top Python applications widely used in the real world below:-
1. Python Web Application
There are many options available for web development, such as Django, Flask, Pyramid, and Bottle for developing web frameworks. Python web application is additionally used for advanced content management systems such as Django CMS and Plone. These web frameworks come with standard libraries and modules that help in simplifying multiple tasks related to database interaction, content management, and internet protocol interfacings such as HTTP, XML, SMTP, JSON, IMAP, FTP, and POP.
Python web frameworks are popular for high security, flexibility, and scalability, and the package index has valuable libraries such as Requests, Paramiko, BeautifulSoup, Twisted Python, and Feedparser.
2. Scientific and Numeric Applications
Python has an impressive library base that has become an integral part of numeric and scientific computing. It provides the skeletal framework for scientific and computational data processing applications. Some of the most widely used Python packages for numeric and scientific computation are –
- Pandas (data analytics library)
- SciPy (scientific numeric library)
- IPython (command shell)
- Natural Language Toolkit (Mathematical And text analysis)
- Numeric Python (Fundamental numeric package)
3. Game Development
The numerous Python extensions or libraries are beneficial in developing interactive games. For example, PySoy and PyGame are two Python-based libraries widely used in game development. This programming language made the development of popular games such as Frets on Fire, Battlefield 2, World of Tanks, Vega Strike, etc., possible.
Game designers also use Python for developing tools to simplify specific actions like dialog tree creation, level design, or even tools that help export these tasks into formats used by primary game engines. The scripting language of game engines is also built on Python.
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4. Artificial Intelligence and Machine Learning
AI and ML projects and models are not the same as traditional software models because the required tools, technologies, and skillset are entirely different from conventional software projects.
A stable, flexible, and secure language equipped with tools for handling multiple unique requirements is necessary for AI and ML development. Therefore, Python is considered one of the most favored languages used in Data Science. It is a simple and consistent language known for its platform independence and resourceful libraries, making it a perfect tool for developing AI and ML applications.
The most common Python packages used for AI and ML are:
- Pandas for general-purpose data analysis
- SciPy for advanced computing
- Keras, Scikit-learn, and TensorFlow
- Seaborn for data visualization
- NumPy for high-performance data analysis and scientific computing
5. Software Development
Python applications and packages are widely used in software development. It is involved in complex applications involving scientific computing and developing web and desktop applications. Python is used by software developers mainly as a support language for build control, management, and testing.
6. Python GUI Programming
Python’s English-like syntax makes it an easy-to-use programming language that also features a flexible architecture and can run on several operating systems. Its rich text processing tools make Python one of the best choices for developing desktop-based GUI applications. Python GUI programming additionally offers numerous frameworks and toolkits for making desktop application development easier.
7. Enterprise-level/Business Applications
Enterprise-level applications or software are quite different from traditional applications. They must have high readability, extensibility, and scalability features. Business applications developed with Python are designed as per the needs of any organization and not individual customers. These applications, therefore, should be capable of combining with legacy systems such as non-web apps and existing databases. Business applications made with Python can be customized to cater to the needs of an organization’s operating model.
8. Education programs and training courses
Python is a beginner-friendly programming language with a straightforward syntax similar to the English language. Therefore, it is easy to learn and an excellent choice for beginner-level enthusiasts. Its simplicity and easy learning curve are why it is a widely-used programming language in educational programs at both beginner and advanced levels. It is one of the best introductory languages for beginners, but it is also used by professional coders and developers worldwide.
9. Language Development
Python’s module architecture and the entire design have inspired the development of multiple new programming languages like Swift, Boo, Cobra, CoffeeScript, and OCaml. These are relatively new languages that share numerous similarities with Python-based on syntax, object model, and indentation.
10. Operating Systems
In programming, it is well-known that multiple robust operating systems are developed by using Python. It is most popular in the use of Linux distributions. Python is coded inside systems like Fedora, Red Hat Enterprise’s Anaconda Installer, Ubuntu’s Ubiquity Installer, etc. Python is generally integrated with the C programming language to develop and design operating systems.
Conclusion
Therefore, we can easily conclude that Python has a plethora of applications. Almost every field today uses Python for its simplicity and versatility.
As a budding programming enthusiast, learning this high-level programming language is crucial. And what better than Python to start your developer’s journey? It is a versatile language that finds application in multiple use cases. If you wish to master Python for data science, check out upGrad’s Advanced Certificate Program in Data Science.
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