On Thu, Apr 14, 2016 at 1:47 PM, Jonathan Helmus <jjhel...@gmail.com> wrote: > > > On 4/14/16 3:11 PM, Matthew Brett wrote: >> >> 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 > > > Yes, both the wheel and conda numpy packages give errors when there is not a > compiler. These errors clear when gcc is installed. Looks like the wheels > are fine, just forgot about a compiler.
Thanks for checking. I think the problem is fixed here: https://github.com/numpy/numpy/pull/7549 Cheers, Matthew _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
