Does being in conda-forge mean the package will eventually make it to the mainline conda repo?
I just have memories (admittedly from when dinosaurs walked the earth) of upgrading a package from rpmforge and having it brick my Linux machine. And I still sometimes see a conda-forge install change a bunch of packages I don't want it to and (as a result) break a ton of pickled results. But if you can control the dependencies then it might be ok ? Would there also be a pip install option ? Building from GitHub master is... Challenging. On Oct 18, 2018 8:46 AM, "Greg Landrum" <greg.land...@gmail.com> wrote: Um, guys, there are some interesting side conversations starting here, but can we please keep this thread on the "is it ok for me to stop doing builds on the RDKit channel" question? This is important to me (and possibly the community), so I'd like the keep the discussion as simple and uncluttered as possible. Thanks, -greg On Thu, Oct 18, 2018 at 5:26 PM Markus Sitzmann <markus.sitzm...@gmail.com> wrote: > Hmm, isn't that the problem with any build/dependency automation tool and > hard to fix in a generic way? If you are really very dependent on a > specific version of a software you have to be very careful with the > environment it sits in while you do "carefree" updates only in a carefree > environment :-) (and environment management got a lot easier the recent > years) > > Markus > > On Thu, Oct 18, 2018 at 4:43 PM Greg Landrum <greg.land...@gmail.com> > wrote: > >> >> >> On Thu, Oct 18, 2018 at 2:21 PM Eric Jonas <jo...@ericjonas.com> wrote: >> >>> Greg, I'm all for anything that makes the release process on developers >>> easier; my main question is : With conda-forge, how hard is it to install >>> just _one_ package without having everything else (say numpy, pandas, etc) >>> upgraded to the latest conda-forge version? I've had situations in the past >>> where i'm like "oh I'd just like the latest ___" and suddenly everything in >>> my conda env has been upgraded to the bleeding edge. >>> >> >> That's a great question, and it's one I don't really know the answer to. >> >> On my PC (I'm on the train, and this is what I have with me), here's what >> I did: >> - create a new conda environment that includes an rdkit-channel RDKit >> install >> - uninstall the RDKit from that >> - install the RDKit from the conda-forge channel >> >> Here's what ends up getting changed: >> >> ## Package Plan ## >> >> environment location: C:\Users\glandrum\Anaconda3\envs\py36_tmp >> >> added / updated specs: >> - rdkit >> >> >> The following NEW packages will be INSTALLED: >> >> boost: 1.67.0-py36_vc14_0 conda-forge [vc14] >> boost-cpp: 1.67.0-vc14_0 conda-forge [vc14] >> pycairo: 1.16.3-py36_vc14_0 conda-forge [vc14] >> rdkit: 2018.03.4-py36h857267b_1000 conda-forge >> >> The following packages will be UPDATED: >> >> certifi: 2018.10.15-py36_0 --> >> 2018.10.15-py36_1000 conda-forge >> jpeg: 9b-hb83a4c4_2 --> 9b-vc14_2 >> conda-forge [vc14] >> tk: 8.6.8-hfa6e2cd_0 --> 8.6.8-vc14_0 >> conda-forge [vc14] >> >> The following packages will be DOWNGRADED: >> >> icu: 58.2-ha66f8fd_1 --> 58.2-vc14_0 >> conda-forge [vc14] >> libpng: 1.6.35-h2a8f88b_0 --> 1.6.34-vc14_0 >> conda-forge [vc14] >> libtiff: 4.0.9-h36446d0_2 --> 4.0.9-vc14_0 >> conda-forge [vc14] >> pillow: 5.3.0-py36hdc69c19_0 --> >> 5.2.0-py36h08bbbbd_0 >> pixman: 0.34.0-hcef7cb0_3 --> 0.34.0-vc14_2 >> conda-forge [vc14] >> vc: 14.1-h0510ff6_4 --> 14-0 >> conda-forge >> zlib: 1.2.11-h8395fce_2 --> 1.2.11-vc14_0 >> conda-forge [vc14] >> >> >> That's a fair amount of change, but is less than what I thought might >> happen (I was worried about numpy+pandas+... being updated). >> So that's one data point. What's your take? >> >> >> I will try the same thing on my Mac and Linux boxes tomorrow if no one >> else has done it by then. >> >> -greg >> >> >> _______________________________________________ >> Rdkit-discuss mailing list >> Rdkit-discuss@lists.sourceforge.net >> https://lists.sourceforge.net/lists/listinfo/rdkit-discuss >> >
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