What’s next for the ever-popular programming language?
In 1989, Guido van Rossum was reading the published scripts of Monty Python’s Flying Circus while working on a language which would one day become something of a Holy Grail for Software Engineers.
It’s been three decades since Python first appeared. Users loved it for its simplicity, readability and English-like commands that made coding quicker and easier. 30 years later, it is one of the most commonly used programming languages in existence, this year beating Java for the first time in RedMonk’s language popularity rankings. In the last 20 years, it has rarely dropped out of the top 10 on the TIOBE index.
Python’s continued popularity is one of the reasons we chose to specialise in hiring Python-based Software Engineers at develop. At last count, there were 8.2 million developers around the world who prefer to work in Python. But these candidates aren’t just working on the legacy systems supported by Python – they are often coding at the cutting edge of new and emerging technologies.
Data scientists are increasingly using Python to collect and analyse new information. Part of this is down to the number of available libraries; currently 72,000 and growing. These libraries are high-performing and can easily handle large volumes of data. In 2018, 68 per cent of data scientists said they use Python daily.
This is partly because Python is so widely used in other areas of the organisation – Facebook, for example, chose to use Python for data analysis because of the business’ familiarity with the language. Organisations such as Google, NASA and CERN all reportedly use
Python for data science.
The language is also thought to be used by Uber, with Python helping engineers to create dynamic pricing models. YouTube also used the language for its real-time analytics. One particularly interesting case study is ForecastWatch.com, which collects more than 36,000 weather forecasts every day for over 800 US cities. These are later compared with actual climatological data, to determine the accuracy of the forecasts. ForecastWatch.com is a pure Python solution, proving its extensibility for a number of practical uses.
Linked to data science is machine learning (ML). The basic purpose of machine learning is to use data to make machines more intelligent. Python’s simplicity makes it straightforward for engineers working in ML to quickly validate an idea, because it is easy to understand. Python has packages upon packages which are able to quickly make sense of large volumes of raw, unstructured and incomplete data. These require no more than a basic understanding of Python functionality and if engineers would rather build these from scratch, that’s perfectly possible too.
Companies who prioritise speed of development, such as Spotify, use Python in their ML efforts. The business even built its own Python package, Luigi, which now powers its Radio and Discover features. Amazon chose to work with Python because of its scalability and ability to manage big data. Like Spotify, Amazon also uses other languages alongside Python, proving its compatibility.
Big brands, big opportunities
Python is widely used by some of the biggest household names. The list includes Instagram, Spotify, Amazon, Disney, YouTube, Quora, Reddit, NASA, Nokia, Uber, Pinterest, Google, Dropbox, Yahoo!, IBM, CERN… and that is by no means exhaustive. The widespread popularity of the language means there are plenty of opportunities for Software Engineers, and its use in new and emerging technologies means that there will only be more in the future.
At develop, we’re teaching all of our Python consultants to code in Python, because we want them to truly understand the roles they are working on. We’re heavily investing in this language, because we see the impact Python can have in the future. If you’d like to discuss your next opportunity in Python, please do get in touch via our website or give us a call on 020 7733 0430.