Data and Clojure: Using Clojure for more than software development
Clojure is rarely anyone's first choice for data science, but could that change? In this talk we'll have a look at what's been happening over the last couple of years in Clojure's data science community, also known as scicloj. The community has been busy building tools and slowly but consistently reaching out to broader audiences, particularly people who have data to work with who aren't already Clojure developers, or even software developers at all. These new library and tooling developments over the last couple years along with the concerted community effort to reach new audiences and publish resources for them make this a unique and exciting time for Clojure as a language expanding beyond general purpose software development. Some questions I'll answer in the talk are: - What does the Clojure ecosystem currently look like? - What makes a language a "good fit" for data science? - Is Clojure a viable option for data science? - What is the community focusing on over the coming months? - How is Clojure's story for data science relevant to Clojure's growth more broadly as a language? - What are some of the main issues with Clojure's current data science ecosystem? - What is different now from previous "Clojure for data science" reports? We'll see that Clojure can offer data scientists some unique ways to solve problems, and has become much more accessible and usable for them thanks to recent developments. We can learn from other data-focused languages that reaching out to non-software-developers is a great way to expand a tech community, in terms of being inclusive and welcoming people from more diverse backgrounds. Opening up the language to be more accessible to this world of programmers is an exciting time for Clojure's growth beyond software development.