Python developer (2022 guide)

What Is Python Used For?

BrainStation’s Python Developer career guide can help you take the first steps toward a lucrative career in web development and data science. Read on to learn more about Python’s different applications.

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Python’s simple syntax and emphasis on readability makes it an easy and convenient programming language to use in a multitude of scenarios and instances.

Quite often, Python is used as a “scripting language” for web applications, meaning it can automate specific series of tasks and improve efficiency. As a result, Python is often used in software applications, the shells of operating systems, webpages, and games.

The language is also used in scientific and mathematical computing, and even in AI projects. Python has been successfully embedded in numerous software products, including visual effects compositor Nuke, 3D modellers, and animation packages.

What is Python?

Python is an interpreted, object-oriented, high-level programming language with easy to learn syntax that emphasizes readability. In fact, Python was designed for readability, with a syntax that is similar to a math-infused version of the English language.

Python is an open source, cross-platform language, meaning it can be run on Mac, Windows, Linux, and Raspberry Pi.

Compared to most languages, Python is straightforward to learn and to use. Its functions can be carried out with simpler commands and less text than most competing languages. And this might explain why it’s soaring in popularity with coding bootcamp students, Developers, and tech companies alike.

Apart from this, Python differs from other programming languages in a few ways, including using new lines to complete a command (as opposed to semicolon or parentheses) and whitespace to define the scope of loops, functions, and classes (as opposed to the curly brackets used in other languages)

Developers love Python because it gives their productivity a huge boost. With no compilation step, the edit-test-debug cycle is incredibly fast.

Debugging Python programs is straightforward: a bug or bad input won’t cause a segmentation fault. Instead, when the interpreter discovers an error, it raises an exception. When the program doesn’t catch the exception, the interpreter prints a stack trace. A source level debugger allows inspection of local and global variables, evaluation of arbitrary expressions, setting breakpoints, stepping through the code a line at a time, and more.

The debugger is written in Python itself, testifying to Python’s power.

Uses of Python

From web development to data science, machine learning, and more, the number of potential real-world applications and uses of Python is endless.

Python’s ease of use and features have made it a versatile programming language for a range of tasks and projects, including:

  • Server-side web development
  • Software development
  • Creating workflows
  • Connecting database systems
  • Big data and complex mathematics
  • Rapid prototyping
  • System scripting

Python is one of those invisible forces with a presence in our mobile devices, web searches and gaming (and beyond). Python is used by Netflix, Facebook, Wikipedia, Google, Yahoo! and NASA, among many other top companies.

Let’s take a closer look at some of the most popular uses of Python.

Websites and applications

Many of the world’s most popular websites have been created using Python, and it is often used to automate tasks when developing web applications, making the process more efficient.

Python is a powerful tool for Web Developers, thanks to its huge index of libraries and the fact that it offers useful frameworks (including Django and Pyramid), micro-frameworks like Flask and Bottle, and advanced content management systems.

Its breadth of libraries and web frameworks, meanwhile, lend itself to back-end web development, especially with its ability to simplify the debugging process and repurpose large chunks of code.

Data science

Python is widely used in scientific and mathematical computing, and perhaps unsurprisingly, has become a popular language amongst Data Scientists, who use it for scientific research and computing large amounts of data. There is a long list of scientific libraries Developers can use within Python and is a great language for parsing data.

Data Scientists will also find Python helpful in machine learning. From speech recognition to automating financial services, Python can access specific machine learning libraries and frameworks that allow for working with AI.

Internet of Things (IoT)

The Internet of Things (IoT) became a buzzword a few years ago and is now a system commonly used for tech devices. Essentially, the IoT is a system of computers and mechanical devices that are able to access a digital network and transfer data. Anything from security systems, thermostats, printers, and other household appliances can be part of the IoT.

Python’s ability to work with data-heavy systems makes it a great language for the IoT, as it can streamline the IoT development process and run code on browsers when working with data networks. Last, but not least, while Developers have to program on their computers and then transfer this to a machine (or thing in the IoT), Python allows you to directly access the device to test your code solutions.

Benefits of Python

Python’s readability and cross-platform adaptability gives it a number of benefits, including:

  • Versatility. Python can be used in web development, data science, scripting, and more. Python focuses on code readability. The language is versatile, neat, easy to use and learn, readable, and well-structured.
  • Readable and maintainable code. Similarities with the English language make it beginner-friendly. The learning curve is very mild and the language is feature-rich. Python is dynamically typed, which makes it friendly and faster to develop with.
  • Less code required to complete projects. Python’s syntax allows Developers to write programs with fewer lines than other programming languages.
  • Compatibility with major platforms, including Windows, Mac, Linux, and more.
  • In-depth libraries, including Pandas and NumPy. You can find a library for basically anything you could imagine: from web development, through game development, to machine learning.
  • Faster prototyping. It can speed up prototyping as it runs on an interpreter system, allowing code to be executed as soon as it is written.
  • Open source tools and frameworks, with a dynamic, community to boot. You can download Python for free and begin writing code in a matter of minutes. And some of the smartest minds in the IT world are contributing both to the language itself and to its support forums.

There are a number of reasons for Python’s increasing popularity, including its intuitive nature, wide range of applications, and rich array of features.

First, Python has relatively easy syntax and readability, which makes learning the language much easier for beginners. This relative ease means that Developers can spend more time on implementation, and less on building complex programs. Second, Python is a general-purpose programming language, with great analytical capabilities and a range of libraries (including Matplotlib, Numpy, and Pandas, among others), which makes it suitable for a number of applications, including back-end development, application development, data science, machine learning, and notably, artificial intelligence, to name a few.

Python features like one-liners and its dynamic type system allow Developers to write far fewer lines of code for tasks that require more lines of code in other languages. This makes Python a very easy-to-learn programming language even for beginners and newbies. For instance, Python programs are slower than Java, but they also take much less time to develop, since Python codes are three to five times shorter than Java codes.

Finally, Python is free and open source, and perhaps more importantly, a cross-platform language, meaning it can be run on Mac, Windows, Linux, and Raspberry Pi.