Python is a general-purpose programming language, meaning it can be used for many different things. Python is used for web development, AI, machine learning, operating systems, mobile application development, and some video games.
A successor to the ABC programming language, Python is a high level, dynamically typed language developed by Guido Van Rossum in the early 1980s. In the intervening years, Python has become a favorite of the tech industry, and it has been used in a wide variety of domains.
The language developed into its modern form in the early 2000s with the introduction of Python 2.0, but its basic operational principles remain the same. Python code is built around the ‘object-oriented’ paradigm, which makes it ideal for writing both large-scale projects and smaller programs.
Python is relatively easy to learn and follows an organized structure which, combined with its versatility and simple syntax, makes it a fantastic programing language for all sorts of projects. If these design features weren’t enough, the fact that it takes its name from Monty Python’s Flying Circus should further indicate that Python development is meant to be as pain-free and enjoyable as possible.
In this article, we’ll go over the most popular uses for Python, and discuss why it is a jewel of open source and an all-around great language to learn.
Uses of Python
Giant websites and platforms such as YouTube and Google rely heavily on Python for critical infrastructure, which has further enhanced its reputation as a solid component in the web developer’s toolkit.
Yes, you can learn to build a quality graphical user interface (GUI) calculator in Python with this tutorial. In fact, this is an excellent introduction to GUI programming and a solid starter project for beginning Pythonistas. Just be aware that it’ll help to have some previous coding experience before you attempt it.
If you want to further expand your knowledge of user interface or user experience design when you’ve finished, consult one of these open source Python GUI frameworks. We’ll talk more about GUI applications later in the article.
You heard that right—Python is so robust that it can be used to build entire operating systems. The object-oriented design of this programming language makes large projects easier to manage, so it’s completely reasonable to attempt a task this daunting with Python. Though building an operating system isn’t generally a popular python undertaking, we thought it was interesting enough to mention.
And speaking of operating systems, Python is compatible with virtually all of them! This means you can build native applications for both Windows and Mac computers with it. From a software development perspective, this is a dream come true.
As mentioned above, Python is an excellent choice for desktop applications with a GUI. The Python Standard Library contains tools for quickly working up simple GUI desktop applications, but you can also code one from start to finish with Python.
Popular applications such as Dropbox and BitTorrent are mostly written in Python, so it’s a proven language for this category of software development. This is what has drawn so much talent to python programming–the fact that something as large as Dropbox can be built almost entirely with one language means that a lot of frustration is removed from the development process.
Python is a go-to for many mobile app developers, and it’s just as useful on iOS and Android as it is on desktop operating systems. There’s a long list of mobile applications built using Python, and it’s getting longer every day. Popular programs like Instagram are mainly written in Python, so clearly it’s a great way to start off in mobile development.
‘AI’ is something of a buzzword these days, but the truth is that it all comes down to algorithms, code, and logic. Given the scope and power of Python, it should come as no surprise that some truly world-class tools exist for generating intelligent behavior in Python.
Arguably the most popular is the ubiquitous machine learning library ‘Scikit-Learn’. Speaking from experience, Sklearn makes the process of building everything from classifiers to regression models orders of magnitude simpler than it otherwise would be.
If neural networks are more your jam, there’s always TensorFlow. Adding in the new(ish) Keras API, building a state-of-the-art neural network is easier than it has ever been.
Whether you’re doing relatively straightforward data analysis or full-on data science, you’d be hard pressed to find a better suite of tools than those provided by Python.
The Pandas library is a quantum-leap improvement over the dusty Excel spreadsheets in which financial analysis was done for so long. If Pandas isn’t fast enough for you, most of the basic vector operations can be one with NumPy. Numpy also offers the ability to do linear algebra, scientific computing, and a host of other highly technical things. It is, therefore, a great tool to learn how to use well.
Why Python is Awesome
Python is an excellent choice if you’re interested in learning how to code. It’s usually best to start with simpler coding languages, and there are few options as straightforward and versatile as Python. This makes it a great choice for a wide range of projects, from simple web applications to entire operating systems.
There’s an enormous number of online resources for learning Python, many of which are free or relatively inexpensive. Picking up Python is a great way to prepare for an intensive coding bootcamp if you want to make a career out of coding. Once you’re ready to learn Python, be sure to click the link below to see how you can turn a little bit of coding knowledge into a lucrative career in technology.