Top 12 Python Use Cases and Applications
Python has grown to be one of the most loved programming languages since its launch in 1991. It is a versatile language that can be used for web development, data analysis, machine learning, and more.
Every business faces a lot of challenges when they want to choose the right and best high level programming language for their next big projects while keeping end-to-end functionality, efficient runtime, scalability, and versatility in mind.
However, hitting that sweet spot of efficiency, functionality, and versatility has gotten a lot easier in the previous decade(s).
This is probably because of the emergence of the Python programming language – the modern holy grail of data science, machine learning, web scraping, and all of the above. Python is a simple programming language that anyone can learn easily and is secure, scalable and supports a rich set of pre-built libraries.
Top 12 Use Cases of Python
Python aids in the rapid development of web applications that are both scalable and secure. This is made possible and easier with the availability of web frameworks like Django, Pyramid and Flask. These frameworks offer easy integration with various protocols like HTTPS, SSl, etc and also support JSON and XML.
Example: Instagram is a popular social media platform that is built entirely on Python. The back-end of the website is powered by Django, which allows for seamless user interactions and quick response times. And few other brand using Python are Disqus, YouTube, Eventbrite, Dropbox
Data Science Implementations
Data science is a relatively new field that has gained significant importance in recent years and Python is the go-to choice for developers working on Data Science.
Unlike Java, Python offers many libraries to handle Data science projects like Pandas, NumPy, etc. Additionally, Python also offers data libraries like Matplolib, Seaborn, etc for rich data visualizations. Data science is one of the most lucrative career prospects in the technology industry today and for anyone who wants to start with Data science should know Python first.
Example: NASA uses Python to process and analyze data from space missions. The PyMars library was developed specifically for analyzing data from the Mars Rover mission.
Python is extremely popular in the field of machine learning or AI. Despite the age-old language, Python has evolved to fit into multiple new technologies.
Python is a stable language that can handle the huge set of computations required for building complicated machine learning modules. Sensorflow, Numpy, Keras, Scikit-learn are some of the popular libraries offered by Python to work on machine learning and artificial intelligence projects.
Python is versatile as it supports multiple use cases. Apart from normal web development to complex AI, Python also aids in Game development.
Python libraries like PySoy and PyGame enable 3D game development. No matter what field you are in, Python already has a library for you to get started easily.
Example: Civilization IV, one of the most popular strategy games of all time, was built using Python. The game engine was built using Python, which allowed for easy modding and customization by players. And few other brand using it for gamification are Disney’s Toontown Online, Vega Strike
Internet of things
One of the standout features of Python is its ability to connect with hardware devices easily. Whether it comes to IoT or Robotics, Python can be useful.
Python can also be used for embedded systems programming due to its lightweight nature and ease of use. Some popular embedded systems frameworks built on Python include MicroPython and CircuitPython. These frameworks provide developers with a range of tools and features for building embedded systems quickly and easily.
Example: Raspberry Pi, a popular single-board computer, can be programmed using Python. The Raspberry Pi Foundation provides developers with a range of libraries and tools for building custom embedded systems using Python.
Web Scraping Applications
With Python, developers can extract huge volumes of data from multiple websites by entering the URLs. Some of the popular libraries for web scraping in Python are Selenium and PythonRequest. Python easily ranks no.1 choice for developing web scraping applications.
Desktop GUI Applications
So far, we’ve been talking about Python mainly as the backend but we can develop rich frontend applications using Python. Tkinter library in Python can be used for designing user interfaces. Python toolkits like PyQT, Kivy, PyGUI, etc. helps in designing UI applications across platforms.
Example: Dropbox, a popular cloud storage service, was built using Python. The desktop application is built using wxPython, which allows for seamless file synchronization and sharing.
Python can be used to develop complex and huge enterprise-level applications since it is both scalable and secure. Python is largely used for database handling and it supports multiple database requests simultaneously. The most important functionalities of Python like readability and scalability make it a top choice for ERP applications. Python offers a simple and easy-to-understand syntax which makes it easily readable.
Tryton is a Python platform that enables the development of business softwares and ERP.
Odoo is an open-source ERP framework provided by Python that is used by more than 7 million users worldwide to develop ERP applications.
Python offers an easy to integrate Python SDK which is used to develop and integrate with third party applications using API. Python offers various libraries which makes connecting and working APIs a breeze.
Image Recognition and text processing
Developers can also use Python to develop image recognition softwares and also help in text processing. Python supports both 2D and 3D image generation and animation using packages like Blender, Houdini, 3ds Max, Lightwave, etc.
Eg: Inkscape, GIMP, Paint Shop
Python can also be used for robotics programming due to its versatility and ease of use. Some popular robotics frameworks built on Python include ROS and PyRobot. These frameworks provide developers with a range of tools and features for building complex robots quickly and easily.
Example: NASA uses Python for robotics programming in its space exploration missions. The Mars Rover was programmed using Python, which allowed for easy customization and modification of the robot’s behavior.
Python is widely used in scientific research due to its vast array of libraries and tools. Some popular scientific libraries built on Python include SciPy, SymPy, and Matplotlib. These libraries provide developers with a range of tools and features for analyzing and visualizing scientific data quickly and easily.
Example: CERN, the European Organization for Nuclear Research, uses Python extensively in its scientific research projects. The PyROOT library was developed specifically for analyzing data from particle physics experiments.
Python is one of the popular programming languages used in the development of education programs and online courses. It is a beginner-friendly programming language with a simple learning curve and a wide variety of resources.
As mentioned earlier, Python is a highly ‘readable’ language and is widely used for developing online courses.
The Bottom Line:-
From web apps, enterprise apps to gaming apps, the application of Python programming language now ranges to a wide variety of applications. As more industries continue to adopt Python, it is clear that this language will continue to play an important role in shaping the future of technology. TAFF has been using Python since our inception to develop various applications in the field of Data Science, ERP, IoT, etc for various clients.
At TAFF, we have an expert team of Python developers who are there to help you build a Python app. Feel free to get in touch with us for your Python-based requirements.