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“Pixi: Package management that doesn't stop at Python packages.”
with Ruben ArtsPixi is a cross-platfrom cross-language package manager that is build on top of the conda-ecosystem and integrates well with PyPI. It provides a workflow similar to other modern packages managers like uv, yarn, cargo but for every language on every OS. In this presentation you'll learn the basic usage of Pixi and where it really shines. More info can be found on https://pixi.sh
Meet Ruben Arts
Ruben is a robotics engineer that has mostly focused on developer experiences. He has moved from robotics to Prefix.dev to help solve developer workflows at large. At Prefix.dev he focuses on community building and outreach to create connections and figure out how to improve the tools to help even more users.
Recent Events
#46 Build your castle, dig your moat: AI sovereignty, provenance and compliance
Dawn Wages — April 29, 2026
Recording Coming Soon!
Your intelligent application is your castle, and your security practices are the moat that protects it. Inside your castle, you must aim for full visibility into what you’re running and why, with freedom to iterate without vendor rate limits or surprise API changes. Your moat creates your security perimeter, ensuring no proprietary data leaves your castle and enforcing best practices including data provenance, cryptographically signed models, evaluation tools, build pipelines and reproducible environments.
Build on your infrastructure, answer to your requirements, scale on your terms.
In this Python Exchange you’ll learn…
- What AI sovereignty actually means for your stack and your business
- How to evaluate self-hosted, local LLMs
- Overview of supply chain security controls for data and code artifacts – provenance, signatures and compliance measures, opacity and trust signals
#45 Diátaxis in practice - and in the wild
Daniele Procida — March 25, 2026
You let ideas loose and then they have a very interesting life of their own!
It’s nearly ten years since I first began writing and talking about the ideas that shaped the Diátaxis documentation approach. In that time, I’ve seen Diátaxis adopted widely, including in contexts I had not even anticipated. I’m aware of hundreds of software projects that use it.
I now have a much stronger sense of how it’s interpreted and used, especially when those ideas are picked up by people that I haven’t met or spoken to.
The lessons learned from seeing what happens when people get hold of those ideas have helped me understand the problems it’s actually solving - not always the ones I’d expected. It has also given me insight into the aspects of the framework that are liable to be misunderstood, or interpreted too rigidly.
Watch on Youtube#44 From Visualization to Conversational Data Exploration with HoloViz
Philipp Rüdiger — February 25, 2026
We will look at how the evolution of HoloViz reflects broader trends in the Python ecosystem over the last decade. We start in the early days of interactive data visualization, when tools like Bokeh and Plotly challenged static plotting and made it possible to explore large datasets dynamically in Python. HoloViz emerged in this moment, focused on composable, high-level abstractions that treated interactivity as a core part of data analysis.
We then move into the shift from notebooks to data applications, even before frameworks like Dash and Streamlit emerged, we created Panel as a way to quickly share analyses with other users. Panel was developed to bridge analysis and application building, allowing Python users to structure, deploy, and share interactive workflows without splitting their codebase or leaving the open-source scientific stack. This transition marked a turning point for HoloViz, transforming it from a set of visualization tools into a platform for building production data apps.
The conversation closes with the current wave of change driven by large language models. As “vibe coding” has emerged as an alternative way to quickly prototype applications, we discuss how HoloViz and Panel in particular are staying relevant. Additionally, we take a look at the latest HoloViz project, Lumen, providing an approach to make analysis more accessible without sacrificing structure, transparency, or trust. We discuss how HoloViz is responding by combining conversational interfaces with auditable, Python-based execution that remains fully extensible and open source, and what this transition means for the project as the Python ecosystem continues to evolve.
Watch on YoutubeAbout Us
At Don’t Use This Code, we want to create a unique opportunity to see Python succeed and thrive within the National Labs! We propose creating a new resource for scientists, researchers, and technical staff to support their use of Python and to build a strong, lasting community for Python users within the Department of Energy National Labs. Disclaimer: The Python Exchange is an independent group of Python enthusiasts who wish to see the use of Python and open-source computing thrive within the National Lab system. This group is not sponsored by or affiliated with the Department of Energy.