R in Production by Hadley Wickham
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Abstract: In this talk, we delve into the strategic deployment of R in production environments, guided by three core principles to elevate your work from individual exploration to scalable, collaborative data science. The essence of putting R into production lies not just in executing code but in crafting solutions that are robust, repeatable, and collaborative, guided by three key principles:
* Not just once: Successful data science projects are not a one-off, but will be run repeatedly for months or years. I'll discuss some of the challenges for creating R scripts and applications that run repeatedly, handle new data seamlessly, and adapt to evolving analytical requirements without constant manual intervention. This principle ensures your analyses are enduring assets not throw away toys.
* Not just my computer: the transition from development on your laptop (usually windows or mac) to a production environment (usually linux) introduces a number of challenges. Here, I'll discuss some strategies for making R code portable, how you can minimise pain when something inevitably goes wrong, and few unresolved auth challenges that we're currently working on.
* Not just me: R is not just a tool for individual analysts but a platform for collaboration. I'll cover some of the best practices for writing readable, understandable code, and how you might go about sharing that code with your colleagues. This principle underscores the importance of building R projects that are accessible, editable, and usable by others, fostering a culture of collaboration and knowledge sharing.
By adhering to these principles, we pave the way for R to be a powerful tool not just for individual analyses but as a cornerstone of enterprise-level data science solutions. Join me to explore how to harness the full potential of R in production, creating workflows that are robust, portable, and collaborative.
Bio: Hadley is Chief Scientist at Posit PBC, winner of the 2019 COPSS award, and a member of the R Foundation. He builds tools (both computational and cognitive) to make data science easier, faster, and more fun. His work includes packages for data science (like the tidyverse, which includes ggplot2, dplyr, and tidyr)and principled software development (e.g. roxygen2, testthat, and pkgdown). He is also a writer, educator, and speaker promoting the use of R for data science. Learn more on his website, hadley.nz.
Mastodon: fosstodon.org/@hadleywickham
Presented at the 2024 New York R Conference (May 17, 2024)
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