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
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.