Python is the most versatile programming language amongst developers today. Since Python is reliable and easy to maintain, it becomes the go-to language for software engineers, data scientists, automation engineers, game developers, etc.
One might ask, What are the key areas where Python has its best applications? While Python is utilized in different domains for distinct reasons. In the upcoming segment, we will discuss 7 application areas of Python programming language.
1. Data Science
Data science is an interdisciplinary domain that comprises of three distinct and overlapping areas:
- How to model and summarize data like a statistician
- How to design and use algorithms to store, process, and visualize data like a computer scientist
- How to formulate the right questions and put answers in the right context like a domain expert
Python is an entrusted language for scientific computing tasks, including analysis and visualization of large data sets. The use cases of Python in data science stems from the large and active ecosystem of third-party packages, such as NumPy for manipulation of homogeneous array-based data, Pandas for manipulation of heterogeneous and labeled data, SciPi for computing tasks, Sci-Kit Learn for machine learning, etc. So, a data scientist combines statistical techniques with Python programming language to analyze and interpret complex data.
2. Automation
There are times when tasks are too niche to have standard software for it. That is when scripting comes into play. Python allows developers to script custom automation and bring efficiency in tasks in less time. Automating repetitive tasks such as sending emails & voicemails, organizing files & folders, launching programs, filling out forms, etc. can be automated through scripting.
3. Application Development
Python is a favourable choice for web application development. Python integrates well with other programming languages and has some amazing web frameworks that boost the application development cycle. Python web frameworks basically make it easy to build common backend logic. For example, it helps to deal with the databases, map URLs with the codebase, generate HTML files, and more.
4. AI & Machine Learning
Python’s pre-built libraries are the reason why it is preferred for AI & machine learning development. Numpy for scientific computation, Pybrain for machine learning tasks, Scipy for technical and scientific computing are some of the python libraries that make it a supportive technology for AI and ML development.
Moreover, there are python libraries for Natural Language & Text Processing. The Natural Language Toolkit (NLTK) contains open-source Python modules, linguistic data & documentation for R&D in natural language processing and text analytics.
In addition to this, there are some general python libraries for Artificial Intelligence. AIMA, SimpleAI, EasyAI, pyDatalog are a few of them.
5. Audio/Video Applications
Python is a sought-after programming language for creating audio/video applications. An example of this is the Spotify app that’s built using Python programming language. Some of the python libraries such as PyDub, OpenCV support building audio/video streaming apps with high-level functionality.
6. Console Applications
A console application is a computer program that’s designed for the text-only interfaces, such as the command-line interface of Unix, DOS operating system. For building console applications, there are advanced python libraries that help in the development of fully-fledged apps for the command-line interface.
ALSO READ: Top 10 Apps Built Using Python
7. Desktop GUIPython is known for its huge collection of libraries. Just like the areas mentioned above. Python has libraries for building desktop GUI applications as well. Camelot, Kivy, PyGTK are some of the amazing libraries and tool-kits available for building desktop GUI.
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