On Thu, Apr 14, 2016 at 12:57 PM, Matthew Brett <matthew.br...@gmail.com> wrote: > On Thu, Apr 14, 2016 at 12:25 PM, Jonathan Helmus <jjhel...@gmail.com> wrote: >> >> >> On 4/14/16 1:26 PM, Matthew Brett wrote: >>> >>> Hi, >>> >>> On Thu, Apr 14, 2016 at 11:11 AM, Benjamin Root <ben.v.r...@gmail.com> >>> wrote: >>>> >>>> Are we going to have to have documentation somewhere making it clear that >>>> the numpy wheel shouldn't be used in a conda environment? Not that I >>>> would >>>> expect this issue to come up all that often, but I could imagine a >>>> scenario >>>> where a non-scientist is simply using a base conda distribution because >>>> that >>>> is what IT put on their system. Then they do "pip install ipython" that >>>> indirectly brings in numpy (through the matplotlib dependency), and end >>>> up >>>> with an incompatible numpy because they would have been linked against >>>> different pythons? >>>> >>>> Or is this not an issue? >>> >>> I'm afraid I don't know conda at all, but I'm guessing that pip will >>> not install numpy when it is installed via conda. >> >> Correct, pip will not (or at least should not, and did not in my tests) >> install numpy over top of an existing conda installed numpy. Unfortunately >> from my testing, conda will install a conda version of numpy over top of a >> pip installed version. This may be the expected behavior as conda maintains >> its own list of installed packages. >>> >>> So the potential difference is that, pre-wheel, if numpy was not >>> installed in your conda environment, then pip would build numpy from >>> source, whereas now you'll get a binary install. >>> >>> I _think_ that Python's binary API specification >>> (pip.pep425tags.get_abi_tag()) should prevent pip from installing an >>> incompatible wheel. Are there any conda experts out there who can >>> give more detail, or more convincing assurance? >> >> I tested "pip install numpy" in conda environments (conda's equivalent to >> virtualenvs) which did not have numpy installed previously for Python 2.7, >> 3.4 and 3.5 in a Ubuntu 14.04 Docker container. In all cases numpy was >> installed from the whl file and appeared to be functional. Running the >> numpy test suite found three failing tests for Python 2.7 and 3.5 and 21 >> errors in Python 3.4. The 2.7 and 3.5 failures do not look concerning but >> the 3.4 errors are a bit strange. >> Logs are in >> https://gist.github.com/jjhelmus/a433a66d56fb0e39b8ebde248ad3fe36 > > Thanks for testing. For: > > docker run -ti --rm ubuntu:14.04 /bin/bash > > apt-get update && apt-get install -y curl > curl -LO https://bootstrap.pypa.io/get-pip.py > python3 get-pip.py > pip install numpy nose > python3 -c "import numpy; numpy.test()" > > I get: > > FAILED (KNOWNFAIL=7, SKIP=17, errors=21) > > This is stock Python 3.4 - so not a conda issue. It is definitely a > problem with the wheel because a compiled numpy wheel on the same > docker image: > > apt-get update && apt-get install -y curl python3-dev > curl -LO https://bootstrap.pypa.io/get-pip.py > python3 get-pip.py > pip install --no-binary=:all: numpy nose > python3 -c "import numpy; numpy.test()" > > gives no test errors. > > It looks like we have some more work to do...
Actually, I can solve these errors by first doing: apt-get install gcc I think these must be bugs in the numpy tests where numpy is assuming a functional compiler. Does the conda numpy give test errors when there is no compiler? Cheers, Matthew _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
