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We could not get ATLAS shared libraries on Mac (while the static ATLAS
libraries are built and can be used successfully on Mac). So, the
pipeline now builds OpenBLAS, which both Numpy and Scipy can use on Mac
and GNU/Linux.
We also added FFTW as a dependency of Numpy. Altough Numpy is not linking to
FFTW for some reason. However, since FFTW is a low level library used by
many programs, we have kept it as a dependency of Numpy anyway for now.
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The Makefile that build the shared libraries comes from Arch Linux so it
does not work easily on Mac. But the full ATLAS build goes successfully
for static libraries. For now we are disabling shared libraries on Mac.
Python was built explicity with `clang' on Mac.
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Until now, we were simply using the host's GCC for Mac systems. But we
found that except for a single step (to fixing `rpath'), it works on
Mac!!! So, GCC is now part of the Mac build as well.
However, we are still having some problems in building ATLAS on Mac. It
works on GNU/Linux, but not in Mac. So for the time being (just
temporarily), we are avoiding ATLAS (and thus Scipy) on Mac systems. We
just filed an issue on the ATLAS discussion list to hopefully fix the
problem soon.
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In this commit we add `h5py' Python package.
We also include `setuptools' as a main dependency of Python because with the
previous commit it (as well as `pip') is no longer installed with Python.
Numpy version also has been incremented.
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Numpy needs ATLAS as shared libraries. So we also need to build Python with
shared libraries. We also need to define site.cfg for numpy and scipy so we
define a master template:
`reproduce/config/pipeline/dependency-numpy-scipy.cfg'
Also `Openssl' did not have rpath so we added with this commit.
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An initial installation of atlas is now included in the pipeline,
but we are still trying to make it compile and build smoothly. In
the process, we found that GCC also needs some modifications
(for example rpath issues).
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To ensure that we have all the necessary Python dependencies, I done an
offline build and noticed that several packages were also necessary for the
`./configure' step to finish (`libffi', `asn1crypto', `cffi', `jeepney',
`pycparser' and `secretstorage'). With this commit they are added.
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Until now, we were only resetting the Python environment variables in the
actual processing Makefiles, not in the Makefile that build Python and its
modules. They are now added there also.
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Until this commit, we had some of the python packages intalled
but they did not work properly because of the `PYTHONPATH' variables.
That is, the pipeline's `python' was the `python' of the system
instead of the pipeline's `python'.
With this commit this issue has been fixed by setting the correct
`PYTHONPATH'. In this commit we also modify the installation of
`bzip2' because `CMake' was complaining about some libraries built
statically.
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Until now the installation of Python and its packages (numpy, astropy,
astroquery, etc.) were done in the same `makefile'.
With this commit the installation of Python and its packages have been
split and now it is independent of the other programs. The installation
of all Python packages needs to be written explicitely because pip is
not used anymore.
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As matplotlib is a general package for plotting and it is widely
used in science, we have added it to the pipeline.
When installing a dependency of matplotlib `python-dateutil', we
found a conflict in the download of the tarball. This is because
the name has a dash (-) in the middle. In addition, the name starts
with 'python', so it is the same as the python itself. Now it is
possible to install any package with any name, just adding an elif
in before the URL direction.
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All dependencies for building astroquery package have been done.
Until nowthe Python dependencies were built in the same Makefile
as the high level libraries and programs. But, because astroquery
has many dependencies we split the Python and Python packages
installation in a new Makefile.
The installation of differents packages are done using Python and
not pip, because we found some problems when doing it with pip.
Apparently there are some interferences between the packages
installed by the pip of the system and the pip installed as part
of Python in the pipeline.
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