> (we've had a few recent issues with libgfortran accidentally missing as a requirement of scipy).
On this topic, you may be able to get some milage out of adapting pypa/auditwheel, which can load up extension module `.so` files inside a wheel (or conda package) and walk the shared library dependency tree like the runtime linker (using pyelftools), and check whether things are going to resolve properly and where shared libraries are loaded from. Something like that should be able to, with minimal adaptation to use the conda dependency resolver, check that a conda package properly declares all of the shared library dependencies it actually needs. -Robert On Sat, Feb 6, 2016 at 3:42 PM, Michael Sarahan <msara...@gmail.com> wrote: > FWIW, we (Continuum) are working on a CI system that builds conda > recipes. Part of this is testing not only individual packages that change, > but also any downstream packages that are also in the repository of > recipes. The configuration for this is in > https://github.com/conda/conda-recipes/blob/master/.binstar.yml and the > project doing the dependency detection is in > https://github.com/ContinuumIO/ProtoCI/ > > This is still being established (particularly, provisioning build > workers), but please talk with us if you're interested. > > Chris, it may still be useful to use docker here (perhaps on the build > worker, or elsewhere), also, as the distinction between build machines and > user machines is important to make. Docker would be great for making sure > that all dependency requirements are met on end-user systems (we've had a > few recent issues with libgfortran accidentally missing as a requirement of > scipy). > > Best, > Michael > > On Sat, Feb 6, 2016 at 5:22 PM Chris Barker <chris.bar...@noaa.gov> wrote: > >> On Fri, Feb 5, 2016 at 3:24 PM, Nathaniel Smith <n...@pobox.com> wrote: >> >>> On Fri, Feb 5, 2016 at 1:16 PM, Chris Barker <chris.bar...@noaa.gov> >>> wrote: >>> >> >> >>> >> > If we set up a numpy-testing conda channel, it could be used to >>> cache >>> >> > binary builds for all he versions of everything we want to test >>> >> > against. >>> >> Anaconda doesn't always have the >>> > latest builds of everything. >> >> >> OK, this may be more or less helpful, depending on what we want to built >> against. But a conda environment (maybe tied to a custom channel) really >> does make a nice contained space for testing that can be set up fast on a >> CI server. >> >> If whoever is setting up a test system/matrix thinks this would be >> useful, I'd be glad to help set it up. >> >> -Chris >> >> >> >> >> >> -- >> >> Christopher Barker, Ph.D. >> Oceanographer >> >> Emergency Response Division >> NOAA/NOS/OR&R (206) 526-6959 voice >> 7600 Sand Point Way NE (206) 526-6329 fax >> Seattle, WA 98115 (206) 526-6317 main reception >> >> chris.bar...@noaa.gov >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@scipy.org >> https://mail.scipy.org/mailman/listinfo/numpy-discussion >> > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion > > -- -Robert
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