Pavithra is a Developer Advocate at Quansight, where she works to support the PyData community. She also contributes to the Bokeh and Dask projects; and has helped administrate Wikimedia’s outreach programs in the past. In her spare time, she enjoys a good book and hot coffee. :)
While most scientists aren't at the scale of black hole imaging research teams that analyze Petabytes of data every day, you can easily fall into a situation where your laptop doesn't have quite enough power to do the analytics you need.
In this hands-on tutorial, you will learn the fundamentals of analyzing massive datasets with real-world examples on actual powerful machines on a public cloud provided by the presenters – starting from how the data is stored and read, to how it is processed and visualized.
Bokeh is a library for interactive data visualization. You can use it with Jupyter Notebooks or create standalone web applications, all using Python. This tutorial is a complete guide to Bokeh, where we start with a basic line plot and step-by-step make our way to creating a dashboard with several interacting components. This tutorial will be helpful for scientists who are looking to level-up their analysis and presentations, and tool developers interested in adding custom plotting functionally or dashboards.
Communities are at the heart of open source software and are fundamental to our projects’ long-term success. The Python ecosystem has several mature projects, that have spent years working on community initiatives. Newer projects can learn from their experiences and build stronger foundations to foster healthy communities.
In this talk, we share a set of practices for community-first projects, including repository management, contributor pathways, and governance principles. We’ll also share real examples from our own journey transitioning a company-backed OSS project, Nebari (https://nebari.dev/), to be more community-oriented.