Tuesday, January 26, 2021

Quansight Labs Blog: Python packaging in 2021 - pain points and bright spots

At Quansight we have a weekly "Q-share" session on Fridays where everyone can share/demo things they have worked on, recently learned, or that simply seem interesting to share with their colleagues. This can be about anything, from new utilities to low-level performance, from building inclusive communities to how to write better documentation, from UX design to what legal & accounting does to support the business. This week I decided to try something different: hold a brainstorm on the state of Python packaging today.

The ~30 participants were mostly from the PyData world, but not exclusively - it included people with backgrounds and preferences ranging from C, C++ and Fortran to JavaScript, R and DevOps - and with experience as end-users, packagers, library authors, and educators. This blog post contains the raw output of the 30-minute brainstorm (only cleaned up for textual issues) and my annotations on it (in italics) which capture some of the discussion during the session and links and context that may be helpful. I think it sketches a decent picture of the main pain points of Python packaging for users and developers interacting with the Python data and numerical computing ecosystem.

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