Feedback on PurlDB Popularity Scoring Proposal

[hiyasanghvi]

Hi @JonoYang @pombredanne @AyanSinhaMahapatra @tdruez @TG1999 & ,

I'm Hiya, a GSoC 2026 applicant working on a proposal to improve package popularity scoring in PurlDB.

Before drafting the proposal, I explored the codebase and implemented a working prototype:

• Built and ran PurlDB locally using Docker
• Implemented a ranking pipeline that computes popularity scores and stores them for real packages
• Identified the version-fragmentation issue (e.g., requests==2.28.0 vs 2.31.0 being treated separately) and handled normalization at the package level
• Explored integration points for exposing scores via API and scheduler jobs

Repository: https://github.com/hiyasanghvi/purldb

I’ve shared my draft proposal here:https://github.com/hiyasanghvi/purldb/blob/main/PURLdb_GSOC_proposal.pdf

I’d really appreciate feedback on one key point:

→ Does the current approach (version-collapsed scoring + heuristic ranking) align with PurlDB’s long-term direction, or should I design this with ML-based ranking in scope from the beginning?

Thanks for your time!

[AyanSinhaMahapatra]

@hiyasanghvi you don't have contributions which have some amount of working, tested code, and this is key for us to be able to even consider a proposal for GSoC as this is the strongest way of you showing us you can finish the proposed project. You have a single contribution which is on docs and scripts, and this is not enough, without this we are not able to provide any feedback on your proposal.

https://github.com/aboutcode-org/aboutcode/wiki/GSOC-2026#your-contributions

[hiyasanghvi]

Hi, thank you for your feedback. I understand that my contributions are currently not sufficient. I had my final exams recently, which limited my ability to contribute earlier. However, I have now started working on code contributions and will be submitting PRs shortly. Please let me know if there are any specific issues I should focus on. I would really appreciate your guidance.

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