Hi, On Mon, Apr 25, 2016 at 2:25 PM, Christian Aichinger <caichin...@ubimet.com> wrote: > Hi! > The addition of the Linux Wheels broke the build process of several of our > Debian packages, which rely on NumPy installed inside virtualenvs. The > problem stems from the pre-compiled shared libraries included in the Wheels, > details are in <https://github.com/numpy/numpy/issues/7570>. > > I'm bringing this up here because these changes have implications that may > not have been fully realized before. > > The Wheel packages are great for end users, they make NumPy much more easily > installable for average people. Unfortunately, they are precisely the wrong > thing for anyone re-packaging NumPy (e.g. shipping it in a virtualenv inside > RPM or Debian packages). For that use-case, you typically want to build NumPy > yourself.[1] You could rely on this happening before, now a `--no-binary` > argument for pip is needed to get that behavior. Put another way, the > addition of the Wheels silently invalidated the assumption that a `pip > install numpy` would locally compile the package. > > In the perfect world, anyone re-packaging NumPy would specify `--no-binary` > if they want to enforce local building. However, currently, --no-binary is > not in widespread use because it was never necessary before. > > I fully agree that the Wheels have great value, but adding them for old > releases (back to 1.6.0 from 2011) suddenly changes the NumPy distribution > for people who explicitly pinned an older version to avoid surprises. It > invites downstream build failures (as happened to us) and adds > externally-built shared objects in a way that people won't expect. > > I would propose to only add Wheels for new releases and to explicitly mention > this issue in the release notes, so people are not blind-sided by it. I > realize that this would be a painfully slow process, but silently breaking > previously working use-cases for old releases seems worse to me (though it is > difficult to estimate how many people are negatively affected by this).
There's more discussion of this issue over on https://github.com/numpy/numpy/issues/7570 Cheers, Matthew _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
