Re: Challenges packaging Python for a Linux distro - at Python Language Summit
FWIW, if might come handy in the future, my 4c:
> * What do we provide for scientific / data scientist use cases?
- https://snapshot.debian.org/ is the unique service allowing to "go
back in time" or just "freeze" the environment given a date.
Very handy for reproducibility, collab, etc.
Not possible AFAIK on pypi or even conda unless researcher prepared a
full exhaustive list of frozen package==version@build
nd_freeze from neurodebian-freeze assists in making use of that
feature. I just stick it at the top of my Dockerfile/Singularity file
recipes to make container itself as reproducible as possible, so later
on I could add another component less likely affecting already
existing ones.
- wider arch support for extensions and non-python libraries/tools.
ppc64el is gaining some momentum AFAIK in sci computing
- better guarantees to achieve desired installation goal.
examples of pip/conda failing to resolve depends are more numerous
AFAIK.
- integration and downstream testing at package build time and via
https://ci.debian.net/
anyone who cares to not only "get it running" but have some assurance
of correct operation (not junk-in-junk-out) should appreciate that.
pypi has no concerns on that at all. conda is doing quite good job
and does allow for some downstream testing. But it remains "more
fluid", unlike a clear cut releases of debian with better guarantees
for correct operation
--
Yaroslav O. Halchenko
Center for Open Neuroscience http://centerforopenneuroscience.org
Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755
WWW: http://www.linkedin.com/in/yarik
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