Panic not. Your agency team aren’t talking about snakes when they keep dropping ‘python’ references into your conference calls. Python is actually a programming language which, much like it’s reptilian namesake, has slowly and stealthily made its way into the top three global programming languages, as measured by the world wide TIOBE index which measures the number of lines of code written in a language. Python took the number three spot in the ratings in September 2018 for the first time in the twenty eight years since its release.
Python is a popular, multi purpose programming language, invented in the late eighties (initially as a hobby language) and released in 1991 by the Dutch programmer Guido van Rossum, and named after the British comedy series Monty Python. Comedy aside, Python is designed to be highly readable, meaning developers spend less time memorising syntax. For example, it often makes use of English language keywords where other languages use punctuation, and white space in place of curly brackets, making it instantly easier to visually and mentally process code, especially for beginners. The strict writing rules mean that the majority of code written in Python looks similar, making it easy to share within the development community. This user friendliness also means that Python is now one of the most popular languages to be taught in schools and colleges, meaning that a new generation of developers are coming into the workplace already very familiar with the Python language.
Another one of Python’s greatest strengths is its large library, which supports many protocols and formats, and contains an extremely wide variety of functionality, covering everything from multimedia and graphics to databases to scientific computing.
So why should you care? Well, these days Python is used to power an extremely wide variety of projects, from fast moving global social platforms like Facebook and Instagram, to 3D animations and compositors, and even security and machine learning. But it’s main applications are web development, machine learning applications and data visualisation.
If you’re talking Python mid-project with an agency it’s likely you’re in the process of a new web app build. If you’re a startup business in a hurry, you’ll be pleased to hear that Python powered frameworks like Django can enable fast, scalable development by bringing together most commonly used sets of components, taking web builds from concept to completion at high speeds, without compromising on security or scalability. Some of the world’s largest sites rely on Django and Python power to quickly and flexibly scale, and if it’s good enough for the likes of Facebook and Pinterest, you know that your precious web build is in good hands.
But don’t let all this talk of ease and social media networks fool you into thinking Python can’t handle anything more academic or scientific. One of the other great strengths of Python, and possibly another reason for its increasing popularity) are its machine learning libraries. Machine learning is one of the fastest growing areas of development, not entirely surprising when we remember that we’re not just talking about the AI of science fiction and futuristic predictions, but also the everyday product recommendations and ‘you might like’ features, (remember that YouTube makes use of Python server-side) necessary these days on almost every customer facing site. Machine learning which powers facial recognition software is also the smarts behind entertaining diversions like SnapChat Filters.
Python is also very useful for automating simple tasks, especially on smaller projects, which for startups where time and budget are critical can be very helpful, freeing up precious developer and client resource time for other challenges. But it’s also more than capable of handling complex data visualisation and data analysis, again making use of its excellent library resources. All of which means that whatever the scale of your venture, your new Python project is likely to be on time, on budget and easily supported.