Data scientists, machine learning developers and data engineers are turning decisively to the Python programming language, according to a new study.
An annual usage analysis released this week by O’Reilly Media also found a decided shift towards cloud native design for software, IT infrastructure and DevOps. The study tracked the most popular search terms on O’Reilly’s platform in 2019. The fastest growing search terms were “coding practices,” which jumped nearly 40 percent year-on-year.
Another hot topic as data and applications shift to the cloud was security. A pair of security certifications developed by the industry group CompTIA spiked over the past year, reflecting the need for more security skills as companies move to the cloud. Overall, security registered the strongest growth as a topic search in 2019, jumping nearly 30 percent.
Meanwhile, Python’s growing popularity was fueled by machine learning development. The survey found that Python usage for AI, deep learning and natural language processing projects grew by 9 percent over 2018. Java ranked second in 2019, but usage actually declined slightly year-on-year.
The fastest growing programming language was Dart, developed by Google (NASDAQ: GOOGL) as an object-oriented tool for running applications on multiple platforms. The first stable version was released in December 2019.
“Python has acquired new relevance amid strong interest in AI and ML,” the usage survey authors noted. “Along with R, Python is one of the most-used languages for data analysis.”
Python’s growing popularity for machine learning development came at the expanse of R, which has been declining since 2017. That shift reflects the accelerating pace of AI development as new cloud-based applications are rolled out.
The shift toward cloud-native design also is reshaping software architectures and the infrastructure on which data-driven cloud applications are deployed. Case in point is the shift toward agile micro-services and the embrace of application container tools like the de facto standard Kubernetes cluster orchestrator.
Indeed, Kubernetes was the fourth most-popular search term last year after Python, Java and cloud leader AWS (NASDAQ: AMZN), the usage survey found.
While the search phrase “software architecture” was by far the hottest search topic on the O’Reilly platform, the phrase “enterprise architecture” registered the largest annual increase in searches last year, jumping by more than 50 percent. That growth underscores the scaling of cloud-native applications and services to larger customers.
The survey also identified a growing shift from straightforward data science to the emerging field of “data engineering.” While data management remains a key requirement as volumes continue to soar, data engineering searches grew at the fastest annual rate in 2019, the survey found.
“We’ve seen that popular tools and frameworks usually incorporate data engineering capabilities, either in the form of automated [or] guided self-service features or…an ability to build and orchestrate data engineering pipelines that invoke Python [or] R libraries to run data engineering jobs concurrently or, if possible, in parallel,” the survey found.
Jupyter and other notebooks are among the most popular tools for developing those data pipelines, the authors added.
Taken together, these trends are expected to boost the popularity of Python. “Programming languages come into and go out of vogue, but Python appears poised to keep growing at a steady rate because it’s at once protean, adaptable, and easy to use,” the survey concludes.
“We see this in the widespread use of Python in ML and AI, where it has supplanted R as the lingua franca of data engineering and analysis.”
Recent items:
Is Python Strangling R to Death?
Why Every Python Developer Will Love Ray
