Since the creation of Python in 1991 by Guido Van Rossum, it has been evolving and adapting to new technologies. Today, Python is one of the most widely used programming languages. Python's versatility in many areas can be attributed primarily to its simplicity and scalability. It is also an open-source, object-oriented and easy-to-learn programming language. Also, Python is reliable and simple to maintain. It is the preferred language of software engineers, data scientists, automation engineers, game developers, and others. In this blog, I will tell you about the top applications of Python programming. So, let us get started!
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Applications Of Python
Data Science
Data science is an interdisciplinary field. Python is a trusted language for scientific computing tasks. This includes analysis and visualization of large data sets. Python is used in data science because of the active ecosystem of third-party programs, including NumPy to manipulate homogeneous array-based datasets, Pandas to manipulate heterogeneous data and labelled data as well as SciFi and Sci-Kit Learn, which are both useful for computing tasks and machine learning. Data scientists combine statistical techniques with Python programming language in order to interpret and analyze complex data.
Automation
Sometimes tasks are too specific to be handled by standard software. This is where scripting comes in. Python makes it possible to create custom automation that increases efficiency and reduces time. Automation of repetitive tasks like sending emails and voicemails, organizing files and folders, launching applications, filling forms, and so on. Automate repetitive tasks with scripting
Application Development
Python is an excellent choice for web app development. Python is compatible with many other programming languages. It also has some great web frameworks that can help speed up the development process. The Python web frameworks make it simple to create common backend logic. It can help you to manage the databases, map URLs to the codebase, create HTML files and many other things.
AI & Machine Learning
Pre-built Python libraries are why Python is so popular for machine learning and AI development. Python libraries include Numpy for scientific computation, Pybrain to perform machine learning tasks, and Scipy for technical or scientific computing. These are all useful tools for AI and ML development.
There are also Python libraries available for Natural Language & Text Processing. Natural Language Toolkit (NLTK), which contains Python modules, linguistic data, and documentation for R&D in text analytics and natural language processing, is open-source.
There are also some general Python libraries that can be used for Artificial Intelligence. AIMA, SimpleAI and EasyAI are just a few.
Audio/Video Applications
Python is a popular programming language for creating audio/video apps. This is evident in the Spotify app, which was built using Python programming language. PyDub and OpenCV are two examples of python libraries that support the creation of audio/video streaming apps with high-level functionality.
Console Applications
A console program is a computer program designed for text-only interfaces such as the Unix command-line interface. Advanced python libraries are available to help you create console apps.
Desktop GUI
Python is well-known for its large library collection. Similar to the previous areas. There are libraries in Python that can be used to build desktop GUI applications. Camelot and PyGTK are just a few of the incredible libraries and toolkits that you can use to build desktop GUI.
Conclusion
So, you have just finished reading about the applications of Python programming. Python is a general-purpose language that is widely used in data science, web development, console applications, machine learning, etc. Hopefully, after reading this blog, you are now familiar with every important application of Python programming.