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What Are Some Examples Of How Python Is Used In The Real World?

Updated: Apr 19, 2022

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Python is a programming language that is widely suggested. You've probably heard that it's because it's extremely simple to learn – and you're right! Is Python, on the other hand, genuinely useful? What are some practical uses for Python abilities once you've acquired them?

It's important to remember that Python is a very versatile programming language. It's used for a variety of purposes. The wide real-world use examples we'll discuss here are only the tip of the iceberg!

Data Analytics

Companies in every business are in need of personnel who can interpret the data they collect. Typically, this entails employing Python-savvy data analysts.

Python is widely used for data analysis because of sophisticated libraries such as NumPy and pandas, making data cleaning and analysis operations relatively simple, especially when dealing with large datasets. Other Python libraries help with different data analytics activities, such as web scraping with Beautiful Soup and data visualization with Matplotlib.

Data analysts can use software tools like Jupyter Notebook to build easy-to-repeat analyses or add text and graphics to make their work clear to individuals who don't know how to code.

Example: An e-commerce website wishes to understand its users better. A firm data analyst could use Python to evaluate revenue, identify typical trends, and identify areas for improvement.

Data Science

Python is also widely used in the field of machine learning for more advanced data handling. Popular machine learning algorithms are easily implemented with powerful libraries like scikit-learn and TensorFlow. In contrast, more specialized libraries exist to assist with a wide range of specific machine learning applications, from image recognition to content generation.

Almost anything you see in the news referred to as "AI" is a machine learning implementation. And Python is being used for a lot of machine learning.

Example: The goal of a video streaming platform is to increase user engagement and loyalty. A data science team may use Python to create a prediction model that suggests videos to users based on their viewing history, viewing patterns, and what videos other users with similar viewing habits have watched.


Python is a popular programming language for both hobbyists and experts in robotics. Hobbyists commonly use Python in conjunction with the Raspberry Pi hardware platform, which allows for flexible and economic experimentation. Python is one of the most often used languages in the industry for robotic process automation (RPA), and it's been used to code industrial robot arms that can work together.

Example: For a production plant, a corporation orders several robotic arms. Engineers may program their behaviour in Python, taking advantage of the language's high-level readability to help everyone comprehend what the components are supposed to accomplish.

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Python is excellent for automating repetitive activities, and there are practically endless real-world applications. Python, for example, is a popular DevOps tool because it allows automating systems and processes quick and easy. But it's also commonly used outside of software development to automate everything from sophisticated systems to small, personal tasks like filling out a spreadsheet or replying to emails.

Example: A firm's sales are reported in monthly Excel spreadsheets from each area, which must be manually combined to provide quarterly reports for the entire company. Instead of doing this time-consuming process by hand, an employee creates a Python script that automatically integrates the spreadsheets and generates each quarterly report.

Web Development

Python is an extremely popular language for web app development, as proven by many firms. Python and popular Python web frameworks like Django and Flask were used to create many of the websites you use every day. Although HTML and CSS are used to create the visual parts of many websites, Python is used to power functionality, manage databases, and manage user accounts, among other things.

Example: A business must create a new edition of its website that includes specified features. A web developer may use Python and Django to create the new site, taking advantage of their flexibility and power to provide any particular or bespoke features with the organization need.

Software Development

Python is a popular programming language utilized in a wide range of real-world applications. The distinction between software development and web development is becoming increasingly blurred, as practically all software is now designed to work on the web, even when a desktop programme is available. Dropbox is an excellent example of a modern software development company that does both, and the Dropbox desktop app was built with Python. Spotify has both web and desktop apps, and Python was used to create a lot of the backend services that keep them running.

Python is, of course, utilized by many businesses to create internal software solutions.

Example: A new email client is being developed by a firm. The developers chose Python because it allows them to design web and desktop clients utilizing Python and its libraries.

Game Development

Because of the availability of useful libraries like PyGame, Python is utilized to produce indie video games. (Do you see a pattern here? Whatever your use case is, there are likely already a few Python modules available to assist you.

Python isn't utilized as often in higher-budget games because of its slow pace and large memory utilization. If you want to create a photorealistic 3D world, Python isn't the best language for the job. However, Python is sometimes used to create the systems that run these games.

Example: A small group wants to make a unique indie side-scrolling game. The developers could opt to work using Python because of PyGame's convenience and the relative ease of learning new things in Python.

Artificial Intelligence, Data Science and Machine Learning with Python

Data Engineering

Python is an important language for data engineers because of many Python packages that make it an excellent alternative for data analysts and data scientists. Data engineers use Python to develop pipelines, combine datasets, clean data, work with APIs, and automate other data processes.

Example: A corporation may have a lot of data, but it's housed in various forms and databases, making it difficult for analysts to locate and work with it. A data engineer could use Python to create a pipeline that automates data gathering from numerous sources, merges and cleans the data, and makes it easier to access and filter for analysts.


Python is a popular first language for people who wish to learn programming because it is a high-level, "readable" language with a wide range of practical applications. Python is likely the easiest programming language to learn, thanks to the abundance of tutorials, videos, interactive courses, and other training tools accessible.

Example: A corporation wants its data analysis team to go beyond Excel and SQL's constraints. They chose Python for team training since they know they'll have a lot of learning resources to pick from.

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