It’s not surprising that Python is one of the most popular programming languages. It’s relatively easy to learn. It’s fast, and it’s flexible. This chart, from the Economist.com, shows the rapid growth of interest in Python, compared to its peers. In this article, StackOverflow made the argument that Python has a substantial claim to being the fastest-growing dominant programming language.
While most widely known, and likely used, for operations scripting and web development, Python has grown to become the developer’s Swiss Army Knife: from essential scripting and automation to data science and machine learning. For instance, Netflix relies heavily on Python. Dropbox, as well, is written mainly in a customized version of Python. So are many popular applications and services.
Today, cross-platform development tools provider ActiveState published a report that highlighted the Top 10 Python Use Cases. The company claims 97 percent of the Fortune 1000 as customers. The report is based on the top uses cases implemented by industry.
The report shows how the use of Python has grown over the past two decades. A few of the use cases particularly stood out as digitally transformative. One U.S.-based multinational financial services corporation sought, using an optimized version of Python, to accelerate their digital transformation efforts, including mining vast amounts of digital customer and prospect behavioral data into more actionable information.
Using Python, the financial services provider kicked-off several data science and machine learning efforts to analyze the data they’d been collecting.
“The customer was able to combine their transactional data with social media data,” the report stated. As a result, the financial company was better able to identify new sales opportunities. For example, the capabilities helped it anticipate when a customer was preparing for a vacation. Those customers were then offered related services, such as travel insurance and foreign currency exchange.
Healthcare is primed for disruption, especially by using artificial intelligence and machine learning to transform how diagnoses are made and to predict disease progression. One California-based medical center turned to deep neural networks, using an optimized version of Python using Pytorch and Scikit-Learn to predict death dates for patients with terminal illnesses.
“Each patient’s EHR was input to the DNN, including current diagnosis, medical procedures and prescriptions,” the ActiveState report said.
According to StackOverflow 2018 Developer Survey, Python was the most desired language to learn by developers for the second year in a row.