92 lines
3.0 KiB
RPMSpec
92 lines
3.0 KiB
RPMSpec
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#
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# spec file for package python-pandas
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#
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# Copyright (c) 2016 SUSE LINUX 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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Name: python-pandas
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Version: 0.19.0
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Release: 0
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Summary: Make working with "relational" or "labeled" data both easy and intuitive
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License: BSD-3-Clause
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Group: Development/Libraries/Python
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Url: http://pandas.pydata.org/
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Source0: https://files.pythonhosted.org/packages/source/p/pandas/pandas-%{version}.tar.gz
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BuildRequires: fdupes
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BuildRequires: gcc-c++
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BuildRequires: python-Cython
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BuildRequires: python-dateutil
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BuildRequires: python-devel
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BuildRequires: python-numpy-devel >= 1.7.0
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BuildRequires: python-pytz
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BuildRequires: python-setuptools
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Requires: python-dateutil
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Requires: python-numpy >= 1.7.0
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Requires: python-pytz
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Recommends: python-Bottleneck
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Recommends: python-Jinja2
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Recommends: python-beautifulsoup4
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Recommends: python-blosc
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Recommends: python-boto
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Recommends: python-html5lib
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Recommends: python-lxml
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Recommends: python-matplotlib
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Recommends: python-numexpr >= 2.1
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Recommends: python-openpyxl
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Recommends: python-scipy
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Recommends: python-statsmodels
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Recommends: python-SQLAlchemy
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Recommends: python-statsmodels
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Recommends: python-tables >= 3.0.0
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Recommends: python-xarray
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Recommends: python-xlrd
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Recommends: python-xlsxwriter
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Recommends: python-xlwt
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Recommends: xclip
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BuildRoot: %{_tmppath}/%{name}-%{version}-build
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%description
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pandas is a Python package providing fast, flexible, and expressive data
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structures designed to make working with "relational" or "labeled" data both
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easy and intuitive. It aims to be the fundamental high-level building block for
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doing practical, real world data analysis in Python. Additionally, it has
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the broader goal of becoming the most powerful and flexible open source data
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analysis / manipulation tool available in any language.
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%prep
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%setup -q -n pandas-%{version}
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%build
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CFLAGS="%{optflags} -fno-strict-aliasing" python setup.py build
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%install
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python setup.py install --root %{buildroot} --prefix=%{_prefix}
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rm -r %{buildroot}%{python_sitearch}/pandas/tests
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%fdupes %{buildroot}%{python_sitearch}
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# Fix python-bytecode-inconsistent-mtime
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pushd %{buildroot}%{python_sitearch}
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%py_compile .
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popd
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%files
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%defattr(-,root,root)
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%doc LICENSE doc/README.rst RELEASE.md
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%{python_sitearch}/pandas/
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%{python_sitearch}/pandas-%{version}-py*.egg-info
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%changelog
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