Hi everyone,
I’m Saurav Singla, and I’m a candidate in the inaugural Python Packaging Council (PPC) election.
My background spans AI, data science, research, education, and building technology for real-world production environments. A theme that has shaped much of my work is bridging research and production—helping good ideas move from experimentation into reliable, practical systems, while bringing production learnings back into the wider technical community.
I have also contributed through peer-reviewed research, technical writing, education, and my book Machine Learning for Finance. I created the course Data Analysis for Business and Finance, which has reached more than 21,000 learners.
For the Packaging Council, I’m particularly interested in making Python packaging simpler, more predictable, and easier to adopt across research, education, and production environments.
Areas I would like to contribute to include:
- Improving the packaging experience for users.
- Strengthening communication between packaging maintainers and the broader Python community.
- Creating clearer pathways for real-world feedback to inform packaging decisions.
- Supporting transparent, sustainable, and collaborative governance.
- Reducing friction when research prototypes need to become reproducible and production-ready applications.
I see the PPC as an opportunity to strengthen the connection between the people who build Python’s packaging infrastructure and the diverse community that depends on it.
I’m happy to answer questions about my candidacy, priorities, experience, or what I would like to contribute to the Packaging Council.
Official candidate page:
LinkedIn:
https://www.linkedin.com/in/sauravsingla008/
Ask me anything.
— Saurav Singla