Top 16 Python applications in the real world

by Alex
Top 16 Python applications in the real world

The pleasure of writing Python code lies in the ability to create short, concise, and readable classes that express a large amount of logic in a small amount of code, rather than hundreds of lines that bore the reader. Guido van Rossum Technology around us has changed in almost every aspect in the last few years. We live in a world where software is at the top of the list, and there’s a line of code behind almost every service. The travel industry, banking, education, research, and the military are just a few of those that rely on software. Every piece of software is written in some sort of programming language. And the number of the latter is only growing. However, one of the most popular in the world today is Python. In this material we will consider examples of real applications working in this language.

Real Python Applications

Python has changed a lot since Gwino van Rossum created it in 1991. It is a dynamic, interpreted, high-level programming language that can be used to create a wide variety of applications. It has a smooth learning curve and clear syntax. Python can be used for web applications, video games, Data Science, machine learning, real world software, embedded applications, and more.

1. Web Development

Surely all developers know what web development is. It is the quintessential application of Python. This language also highlights the wide variety of frameworks and content management systems (CMS) that make the developer’s life easier. Some of the most popular solutions include Django, Flask, Pyramid and Bottle. Among CMSs, Django CMS, Plone CMS and Wagtail stand out. Web development in Python offers benefits such as improved security, scalability and ease of use. The language also supports out-of-the-box protocols such as HTML, XML, email protocols, and FTP. Python has one of the largest collections of libraries that make life easier and better for developers. For a list of sites that use python go to

2. Game Development

Similar to web development, Python has a ton of tools and libraries for game development. By the way, did you know that the once popular Battlefield 2 was written in this programming language? Such libraries as PyGame, Pycap, Construct, Panda3D, PySoy and PyOpenGL are used for game development. Also with the help of Python were developed such projects as Sims 4, World of Tanks, Civilization IV and EVE Online. One can also remember Mount & Blade, Doki Doki Literature Club, Frets on Fire and Disney’s Toontown Online.

3. Artificial intelligence and machine learning

According to GitHub, Python is in second place among the languages used for machine learning. Artificial Intelligence and Machine Learning are very popular topics today. We make a lot of decisions with them today. Python has been partly responsible for this growth in popularity in the industry. The stability and security of the language has made it ideal for the computation-intensive applications that AI and ML can’t do without. And its broad collection of libraries helps with model and algorithm development. Here are the most popular libraries:

  • SciPy for scientific and technical computing.
  • Pandas for data analysis and manipulation.
  • Keras for neural networks.
  • TensorFlow for machine learning, especially for deep neural networks.
  • NumPy for complex mathematical functions and calculations.
  • Scikit-Learn for working with different machine learning models.

4. GUI for desktop applications

Sometimes you can do without a full-fledged interface, but for most projects today a GUI is important. And Python has a lot of solutions for that, too. And the accessible syntax and modular structure allow you to create fast and responsive interfaces, making the development process itself enjoyable. Some of the most popular libraries and frameworks include PyQt, Tkinter, Python GTK+, wxWidgets, and Kivy.

5. Image Processing

Due to the growing popularity of machine learning, deep learning, and neural networks, the role of tools for (pre)image processing has also grown. Python fully meets this demand. Some of the most popular tools in Python include OpenCV, Scikit-Image, and Python Imaging Library (PIL). Notable applications using Python include GIMP, Corel PaintShop, Blender, and Houdini.

6. Text Processing

Text processing is almost the most common use case for Python. It goes hand in hand with NLP (natural language processing), but we won’t dive into that topic now. Text processing allows you to handle large amounts of text, giving you structure flexibility. You can easily sort lines, extract specific text, format paragraphs, and so on.

7. Business applications

Business applications are different from ordinary consumer software in many ways. First, they offer a limited set of features instead of dozens or even hundreds of capabilities. Second, they have a specific target group (most often a specific organization). Python is perfectly suited for developing such high-loaded applications. For example, Python has been used to create Odoo and Tryton. Another important part of any application is security. Although almost all programs are built with security in mind, Python’s security capabilities are very important for business solutions. Python also allows you to write scalable code.

8. Educational and training programs

Python is a great entry point for anyone who wants to learn about the world of modern programming. All thanks to the language’s maximally simple syntax, which is very similar to English. Python is also quicker to learn than other languages. That’s why this language is one of the main candidates to be the first programming language. There are a lot of learning resources to get basic knowledge of Python, but among the most popular are Coursera, edX, Udemy, Python Institute and Harvard.

9. Audio and video applications

Python’s efficiency allows you to use it for audio and video applications. There are plenty of tools and libraries for this. Signal processing, audio control, and sound recognition are all available with libraries such as Pyo, pyAudioANalysis, Dejavu, and others. For video, there is Scikit-video, OpenCV and SciPy. These can be used to manage videos and prepare them for use in other applications. Spotify, Netflix and YouTube are written in Python.

10. Parsing

There’s an incredible amount of information on the Internet. And with web parsers, data on websites can be collected by storing it in one place. They can then be used by researchers, analysts, or organizations for a variety of tasks. Python has libraries such as PythonRequest, BeautifulSoup, MechanicalSoup, Selenium and others. Parsers are used for price tracking, analytics, analysis in social media, machine learning projects, and any other project where there are large amounts of data.

11. Data Science and Data Visualization

Data plays a key role in today’s world. They help you understand people, their tastes, and collect and analyze interesting observations. This is all an important part of Data Science. This field requires defining a problem, collecting data, processing it, examining it, analyzing it, and visualizing it. The Python ecosystem includes solutions such as TensorFlow, PyTorch, Pandas, Scikit-Learn, NumPy, SciPy, and many others. Visualization is important when data needs to be presented to a team or share holders. Python has Plotly, Matplotlib, Seaborn, Ggplot, Geoplotlib, and others for this purpose.

12. Scientific and mathematical applications

We’ve already identified that Python has libraries for scientific and mathematical computing, including AI, ML, and Data Science. But even if you don’t take those areas, the language comes in handy for high-level mathematical functions, for example. Worth mentioning are tools such as Pandas, IPython, SciPy, Numeric Python, Matplotlib and others. Applications such as FreeCAD and Abaqus have been created with Python.

13. Software Development

Python is not only suitable for web development, scientific development, creating games or embedded systems. Basically, it is a universal solution for any type of software. All this is possible because Python provides high speed of execution, good compatibility, excellent community support, and a huge number of libraries. Python has been used to create Roundup, Buildbot, SCons, Mercurial, Orbiter, and Allura. Often developers use Python as an auxiliary language for project management, build control, and testing.

14. Operating Systems

Operating systems are the brain of any computer. Python, for example, runs operating systems built on Linux. At least parts of such systems. Examples include Ubiquity Installer from Ubuntu, Anaconda Installer from Red Hat Enterprise. The language was also used to create Gentoo Linux and the package management system Portage in Google Chrome OS. In general, the combination of Python and C offers huge advantages in designing and developing operating systems.

15. CAD applications

CAD (computer aided design) applications are mainly used in the automotive, aerospace and architectural industries. They help engineers and designers design products with millimeter-accuracy. In the Python environment, these applications include FreeCAD, Fandango, PythonCAD, Blender and Vintech RCAM. They provide features such as macro writing, workbenches, robot simulation, sketching, multi-format import/export support, technical drawing modules, and more.

16. Built-in applications

One of the most impressive features of Python is the work on embedded hardware. These are devices that are designed to do a limited set of things. Embedded software is that which is responsible for running such devices. Among the most popular applications are MicroPython, Zerynth, PyMite, and EmbeddedPython. Examples of embedded devices include digital cameras, smartphones, Raspberry Pi, industrial robots, and others that can run with Python. Not everyone knows this, but Python can be used as an abstraction layer where C or C++ runs at the system level.

Other Python applications

  • Console Applications
  • Computer Vision
  • Robotics
  • Language Development
  • Automated Testing
  • Automation
  • Data analysis


Python is an advanced and versatile programming language that is quickly gaining popularity among developers in a variety of industries. It can be applied to almost any field thanks to its wide range of libraries. If you’re just getting familiar with programming in general, this material should have convinced you to choose Python as your first language. Thankfully, it’s easy to learn today with the abundance of books, courses, GitHub repositories, popular tools, and libraries.

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