acb14efbdb
1 OBS-URL: https://build.opensuse.org/request/show/260050 OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/python-numpy?expand=0&rev=43
139 lines
4.8 KiB
RPMSpec
139 lines
4.8 KiB
RPMSpec
#
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# spec file for package python-numpy-doc
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#
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# Copyright (c) 2014 SUSE LINUX Products GmbH, Nuernberg, Germany.
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#
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# All modifications and additions to the file contributed by third parties
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# remain the property of their copyright owners, unless otherwise agreed
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# upon. The license for this file, and modifications and additions to the
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# file, is the same license as for the pristine package itself (unless the
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# license for the pristine package is not an Open Source License, in which
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# case the license is the MIT License). An "Open Source License" is a
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# license that conforms to the Open Source Definition (Version 1.9)
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# published by the Open Source Initiative.
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# Please submit bugfixes or comments via http://bugs.opensuse.org/
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#
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%define modname numpy
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Name: python-numpy-doc
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%define docname numpydoc
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Version: 1.9.1
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Release: 0
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%define docvers 0.4
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Url: http://www.numpy.org/
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Summary: Documentation for python-numpy
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License: BSD-3-Clause
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Group: Development/Libraries/Python
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Source: https://pypi.python.org/packages/source/n/numpy/numpy-%{version}.tar.gz
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# PATCH-FIX-OPENSUSE numpy-buildfix.patch -- openSUSE-specific build fixes
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Patch0: numpy-buildfix.patch
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# PATCH-FIX-OPENSUSE numpy-1.9.0-remove-__declspec.patch -- fix for spurious compiler warnings that cause build failure
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Patch1: numpy-1.9.0-remove-__declspec.patch
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BuildRoot: %{_tmppath}/%{name}-%{version}-build
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BuildRequires: blas-devel
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BuildRequires: lapack-devel
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BuildRequires: python-Sphinx
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BuildRequires: python-devel
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BuildRequires: python-matplotlib
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BuildRequires: python-numpy-devel
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BuildRequires: python-numpydoc
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BuildRequires: texlive-latex
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BuildRequires: zip
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%if 0%{?suse_version}
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BuildRequires: fdupes
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BuildRequires: gcc-fortran
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%if 0%{?suse_version} <= 1110
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%{!?python_sitelib: %global python_sitelib %(python -c "from distutils.sysconfig import get_python_lib; print(get_python_lib())")}
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%else
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BuildArch: noarch
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%py_requires
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%endif
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%else
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BuildRequires: gcc-gfortran
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%endif
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%description
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NumPy is a general-purpose array-processing package designed to
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efficiently manipulate large multi-dimensional arrays of arbitrary
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records without sacrificing too much speed for small multi-dimensional
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arrays. NumPy is built on the Numeric code base and adds features
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introduced by numarray as well as an extended C-API and the ability to
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create arrays of arbitrary type which also makes NumPy suitable for
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interfacing with general-purpose data-base applications.
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There are also basic facilities for discrete fourier transform,
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basic linear algebra and random number generation.
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This package provides the documentation for NumPy
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%package html
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Summary: HTML documentation for python-numpy
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Group: Development/Libraries/Python
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Recommends: python-numpy = %{version}
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%description html
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NumPy is a general-purpose array-processing package designed to
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efficiently manipulate large multi-dimensional arrays of arbitrary
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records without sacrificing too much speed for small multi-dimensional
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arrays. NumPy is built on the Numeric code base and adds features
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introduced by numarray as well as an extended C-API and the ability to
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create arrays of arbitrary type which also makes NumPy suitable for
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interfacing with general-purpose data-base applications.
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There are also basic facilities for discrete fourier transform,
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basic linear algebra and random number generation.
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This package provides the HTML documentation for NumPy
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%package pdf
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Summary: PDF documentation for python-numpy
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Group: Development/Libraries/Python
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Recommends: python-numpy = %{version}
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%description pdf
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NumPy is a general-purpose array-processing package designed to
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efficiently manipulate large multi-dimensional arrays of arbitrary
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records without sacrificing too much speed for small multi-dimensional
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arrays. NumPy is built on the Numeric code base and adds features
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introduced by numarray as well as an extended C-API and the ability to
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create arrays of arbitrary type which also makes NumPy suitable for
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interfacing with general-purpose data-base applications.
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There are also basic facilities for discrete fourier transform,
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basic linear algebra and random number generation.
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This package provides the PDF documentation for NumPy
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%prep
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%setup -q -n numpy-%{version}
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%patch0 -p1
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%patch1 -p1
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%build
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# make the documentation
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cd doc
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make dist PYVER=%{py_ver}
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%install
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# install the documentation
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cd doc
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mkdir -p %{buildroot}%{_docdir}/python-numpy/{html,pdf}
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tar -xzf build/dist.tar.gz -C %{buildroot}%{_docdir}/python-numpy/html
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mv %{buildroot}%{_docdir}/python-numpy/html/*.pdf %{buildroot}%{_docdir}/python-numpy/pdf/
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%fdupes %{buildroot}%{_docdir}/python-numpy/html/
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%fdupes %{buildroot}%{_docdir}/python-numpy/pdf/
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%files html
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%defattr(-,root,root)
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%{_docdir}/python-numpy/html/
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%files pdf
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%defattr(-,root,root)
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%{_docdir}/python-numpy/pdf/
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%changelog
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