12-05, 16:30–18:30 (UTC), Sprints
Zoom Link: https://numfocus-org.zoom.us/j/88260275885?pwd=RW9FKYZs4uzjJHRgNn7CGOL1sVgAaH.1
Ever wanted to contribute to open source but weren't sure where to start?
In this event, we'll contribute to Narwhals, a lightweight compatibility layer between dataframes. You'll be mentored by the project's developers, and by the end of the session, you'll very likely have submitted your own pull request!
There will be plenty of issues to work on, for both beginner and advanced contributors.
Narwhals is a lightweight and extensible compatibility layer between dataframe libraries. It's currently used by Altair, Plotly, Py-Shiny, Marimo, Vegafusion, and more. And in this session, you'll learn how you (yes, you!) and contribute to it!
If you're new to open source, then we will guide you through the whole process:
- forking a repository on GitHub
- setting up a virtual environment to contribute with
- running tests locally
- making and testing your changes, opening a pull request
If you're an experienced contributor, then we will have more advanced issues on-hand for you to challenge yourself with!
Anyone interested in contributing to open source is encouraged to attend!
Narwhals is a pure-Python project and so is very easy to set up - nonetheless, anyone wishing to get started before the session can follow the contributing guide at https://github.com/narwhals-dev/narwhals/blob/main/CONTRIBUTING.md
By the end of this sprint, you'll not only have contributed to Narwhals but also gained confidence to explore and contribute to other open-source projects. Let's code, collaborate, and make an impact—together!
Several Narwhals developers will be leading the sprint together
No previous knowledge expected
Marco is the author of Narwhals, and also core contributor to Polars and pandas and works at Quansight Labs as Senior Software Engineer. He also consults and trains clients professionally on Polars. He has also written the first Polars Plugins Tutorial and has taught Polars Plugins to clients.
He has a background in Mathematics and holds an MSc from the University of Oxford, and was one of the prize winners in the M6 Forecasting Competition (2nd place overall Q1).