Dawn Wages
Dawn Gibson Wages is the Director of Community & Developer Relations at Anaconda. From her early work as Research Developer at Wharton Computing and Instructional Technology, then working with Python developer experience at Microsoft to her current role, she has been consulting on Python developer experiences across the ecosystem -- speaking to thousands of developers in the process. She co-hosts the Sad Python Girls Club podcast and served as Chair of the Python Software Foundation Board.
Dawn is a member of the Wagtail CMS core team, has organized DjangoCon US sponsorship efforts and Django Girls workshops, and mentors through Djangonaut Space. She's founder of At The Root, which developed the first Anti-Racist Ethical Source License.
A frequent conference speaker on Python development topics, Dawn is currently writing "Domain-Driven Django," exploring architecture patterns for Django applications. Her work focuses on gathering insights from the Python ecosystem to improve developer tooling and experiences.
When she is not engaging in Python, she's chilling at home in Philadelphia with her wife and dogs.
Session
Most data science projects start with a simple notebook—a spark of curiosity, some exploration, and a handful of promising results. But what happens when that experiment needs to grow up and go into production?
This talk follows the story of a single machine learning exploration that matures into a full-fledged ETL pipeline. We’ll walk through the practical steps and real-world challenges that come up when moving from a Jupyter notebook to something robust enough for daily use.
We’ll cover how to:
- Set clear objectives and document the process from the beginning
- Break messy notebook logic into modular, reusable components
- Choose the right tools (Papermill, nbconvert, shell scripts) based on your workflow—not just the hype
- Track environments and dependencies to make sure your project runs tomorrow the way it did today
- Handle data integrity, schema changes, and even evolving labels as your datasets shift over time
And as a bonus: bring your results to life with interactive visualizations using tools like PyScript, Voila, and Panel + HoloViz