2026-07-13 –, Intro
The command line is the most powerful, composable, and underappreciated tool in a data scientist's arsenal. In this hands-on tutorial, attendees will go from "what is a terminal?" to confidently wielding a curated, Python-centric toolkit of modern CLI tools purpose-built for data work. We'll cover shell fundamentals, pipes and composability, then dive into a wide variety of CLI tools like bat, pandoc, and visidata. We will also look at uv for environment management, gh for GitHub workflows, and GitHub Copilot CLI for AI-powered terminal workflows. To get hands on with these new tools, attendees will learn to build their own CLI with Click, Rich, and tqdm. Attendees will leave with a ton of new tools in their toolbox, as well as the skills to build beautiful CLI tools of their own!
Data scientists spend most of their time in Jupyter notebooks and IDEs, but some of the fastest, most reproducible workflows happen at the command line. Shell pipelines can clean, filter, and summarize data in seconds. Modern CLI tools bring syntax highlighting, fuzzy search, and even AI assistance directly to the terminal. Yet many practitioners never learn these skills because the command line feels intimidating or outdated.
This tutorial bridges that gap. We start from first principles: what a CLI actually is, why the Unix philosophy of small composable tools matters for data work and rapidly build up to a practical, Python-centric toolkit. But we don't stop at using CLIs, attendees will build their own. Using Click, Rich, and tqdm, each participant will create a polished command-line tool that automates a real task they do regularly (batch file processing, git review summaries, dataset downloads, log analysis, and more).
No CLI experience, basic Python knowledge for building your own CLI
Sarah has spent most of their career developing technology in the lab, from virtual reality hardware to satellites. They got her PhD in Physics by starting plasma fires with lasers, Python, and Jupyter Notebooks. They have also written tech books for folks of all ages, including ABCs of Engineering and Learn Quantum Computing with Python and Q#. As a Core AI Advocate at GitHub and a Python Software Foundation Fellow, they find all kinds of new ways to build and break OSS tools for data science and machine learning. When not at their split ergo keyboard, they love boating in the Seattle area, laser cutting everything, and playing with their German Shepard, Chewie.