Python’s status as the primary language for AI and machine learning projects, from its extensive data-handling capabilities to its flexibility and portability, is well-founded. Just how well-founded can be seen in new user data from Snowflake.
The cloud data provider reported that, year on year, use of Python grew 571% in Snowpark, Snowflake’s set of libraries which securely deploy and process non-SQL code. In other words, it will not be a surprise to see Python, Scala and Java at the top of this list, but the numbers are what makes it interesting: Scala saw a 387% increase, compared with Java at 131%.
Alongside this, the report noted that usage of the most popular AI/ML open source Python libraries in Snowpark has increased by 335%. Scikit-learn saw a 474% uptick, while XGBoost, focused on gradient boosting, saw an increase of 357%.
From Snowflake’s perspective, the company was keen to note that the increase went beyond shifting existing work to its platform, but a net increase in experimentation with advanced AI. The research also found that enterprises were increasingly getting value out of their unstructured data; up 123% from a user analysis over six months.
“Given that Python in particular is the language of choice for many developers, data engineers and data scientists, its fast-growing adoption suggests that these unstructured data workflows are not just for building data pipelines, but also involve AI applications and ML models,” the report noted. “Python skills will be increasingly essential to development teams as they venture into advanced AI.”
Snowflake also explored how its community of developers in Streamlit were utilising large language models (LLMs). Between April and January, the company noted that 20,076 developers were working on 33,143 LLM-powered apps, including apps which were still in development. Almost two thirds (65%) of 1500 survey respondents said these were work projects.
Among developer concerns from working with LLMs, based on a survey of 980 users, were trust, cited by 36% of respondents, privacy (28%), cost (19%) and being able to learn the requisite skills (17%).
You can read the full report here (email required).
See also: PyPI suspends registrations amid malware attack
Photo by Steve Johnson on Unsplash
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