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Last time I tried (maybe 1-2 years ago), there were some errors when building the doc with napoleon and it was not immediately obvious how to fix them. Googling at the time, it was not immediately clear what the differences were between napoleon and numpy-doc. There may also be small differences in the doc output that are hard to spot given the size of the scikit-learn documentation.
I would be in favour of waiting for 0.20 before merging a PR that switches to napoleon, so that quirks can be spotted in the dev doc until the 0.21 release.
numpydoc has seen some fixes by @jnothman and @amueller semi-recently (maybe a few months ago) so maybe they have some informed opinion.
I would be in favour of waiting for 0.20 before merging a PR that switches to
napoleon, so that quirks can be spotted in the dev doc until the next release.
I'm also not clear on the differences between the two feature-wise (their documentations are not too explicit about this point), I have used both in the past.
However, another point to consider that is that numpydoc had extensive contributions by Joel (and other scikit-learn developers) while, unless I am mistaken no one contributed to sphinx.ext.napoleon too much.
So this would mean replacing a working and well known dependency, by another one which potentially will require more maintenance work. The end result is that new contributors will not need to install numpydocs when they run tests or build docs locally, but is that worth the effort?
Is there a long-term reason that Napoleon would get less maintenance than
numpydocs if projects switch to it? It's embedded in sphinx, so it will
get a lot of exposure. Of course, it's a question of community dynamics,
and there is a lot of social in there.
I have tried to maintain numpydoc, but I acknowledge that it's very hacky.
We only recently adopted the numpydoc dependency rather than a vendored and
tweaked version.
After 0.20, it would be worth considering Napoleon, but we'll have to be
careful to check for feature parity.
What is the original reason to bring this up? Only that napoleon is included in sphinx? Or that we think it actually works better, or is better maintained?
Based on how other project have managed similar issues (matplotlib#5743, astropy-sphinx#5) and the effort put in #21350, I believe this one can be closed.
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lesteve commentedon Jul 5, 2018
Last time I tried (maybe 1-2 years ago), there were some errors when building the doc with napoleon and it was not immediately obvious how to fix them. Googling at the time, it was not immediately clear what the differences were between napoleon and numpy-doc. There may also be small differences in the doc output that are hard to spot given the size of the scikit-learn documentation.
I would be in favour of waiting for 0.20 before merging a PR that switches to napoleon, so that quirks can be spotted in the dev doc until the 0.21 release.
numpydoc has seen some fixes by @jnothman and @amueller semi-recently (maybe a few months ago) so maybe they have some informed opinion.
GaelVaroquaux commentedon Jul 5, 2018
rth commentedon Jul 5, 2018
I'm also not clear on the differences between the two feature-wise (their documentations are not too explicit about this point), I have used both in the past.
However, another point to consider that is that numpydoc had extensive contributions by Joel (and other scikit-learn developers) while, unless I am mistaken no one contributed to sphinx.ext.napoleon too much.
So this would mean replacing a working and well known dependency, by another one which potentially will require more maintenance work. The end result is that new contributors will not need to install
numpydocswhen they run tests or build docs locally, but is that worth the effort?GaelVaroquaux commentedon Jul 5, 2018
jnothman commentedon Jul 5, 2018
jorisvandenbossche commentedon Jul 6, 2018
What is the original reason to bring this up? Only that napoleon is included in sphinx? Or that we think it actually works better, or is better maintained?
GaelVaroquaux commentedon Jul 6, 2018
cmarmo commentedon Jan 17, 2022
Based on how other project have managed similar issues (matplotlib#5743, astropy-sphinx#5) and the effort put in #21350, I believe this one can be closed.
GaelVaroquaux commentedon Jan 17, 2022
Sounds good with me. I'm closing it.