Closed ocefpaf closed 8 years ago
Hi! This is the friendly conda-forge-admin automated user.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe
) and found it was in an excellent condition.
Thanks for the ping. Sorry, I think I missed the other ones. Also, make sure to get rid of libgcc
, as well.
Thanks for the ping. Sorry, I think I missed the other ones. Also, make sure to get rid of libgcc, as well.
Those I am not so sure due to the libgomp
issue...
Ah! Does this need libgomp
?
We can inspect the binaries to find out. :smile:
We can inspect the binaries to find out. :smile:
I will need to solve a fortran problem first! I thought that was already in the docker image.
Ok, so if they need gomp
or gfortran
we definitely need gcc
for OS X. Though Linux should be ok.
Yeah, I think we should just leave this one alone. Most users won't have gfortran. So, let's just close this one out.
Ok, so if they need
gomp
orgfortran
we definitely needgcc
for OS X. Though Linux should be ok.
So we need to go back to libiconv
(pynio
dependency) and compile that with conda's gcc
for OS X?
No, that shouldn't be necessary.
libiconv
is just C (maybe some C++ too). It doesn't use Fortran or OpenMP.
libiconv
is just C (maybe some C++ too). It doesn't use Fortran or OpenMP.
I thought that they should be compiled with the same gcc
to play nice together. Just made the change. Let's see how it goes.
So, that is a problem I have seen with C++ code particularly when using C++11 features. A good example might be Boost and VIGRA.
The problem I saw with libiconv
IIRC was that we built with gcc
, but didn't include libgcc
as a run time requirement. It looked like there were a few other packages like that in the PR (where libiconv
was added). That being said, we have tried to avoid using gcc
from Continuum and use the system compiler instead. So, I figured we should just remove it in that case.
This case seems different as we need gfortran
and it isn't provided on either Linux or Mac so we should install Continuum's gcc
for both. If we are using OpenMP, we should be able to use the system compiler on Linux, but will need Continuum's gcc
on Mac. Otherwise, we should try to use system compilers only. Does this make sense?
Pynio does not seem to like this. I am getting a segfault.
Bye...
/Users/travis/miniconda3/conda-bld/test-tmp_dir/run_test.sh: line 3: 1417 Abort trap: 6 nosetests
TESTS FAILED: pynio-1.5.0beta-np110py27_1
Have you seen this failure locally?
Have you seen this failure locally?
Yes, but it goes away when I re-build everything with conda's gcc
...
I was meaning the HDF5 issue that we are seeing here.
I was meaning the HDF5 issue that we are seeing here.
Nope. But I know what that is: gdal
is downgrading netcdf
:unamused:
(I really should go back to the netCDF recipe!)
I cannot figure out the reason for the hdf5 mismatch. I pinned gdal
and the log shows only hdf5 1.8.15
as expected :unamused:
It is late and I will get back to this tomorrow.
......Warning! ***HDF5 library version mismatched error***
The HDF5 header files used to compile this application do not match
the version used by the HDF5 library to which this application is linked.
Data corruption or segmentation faults may occur if the application continues.
This can happen when an application was compiled by one version of HDF5 but
linked with a different version of static or shared HDF5 library.
You should recompile the application or check your shared library related
settings such as 'LD_LIBRARY_PATH'.
You can, at your own risk, disable this warning by setting the environment
variable 'HDF5_DISABLE_VERSION_CHECK' to a value of '1'.
Setting it to 2 or higher will suppress the warning messages totally.
Headers are 1.8.16, library is 1.8.15
Edit: it is hdfeos5
!
I can confirm it is hdfeos5
. I won't pin hdf5 everywhere. I guess it is better just to get netcdf done.
Everything works when I pin against older build that were compiled against the older hdf5
. I won't merge this as the new netcdf
should fix this for good.
(The failure is the lack of np111
for some packages.)
Don't use conda's
gcc
.Ping @jakirkham: this is the last one!