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.
Cheers,
- Jonathan Helmus
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