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@@ -0,0 +1 @@ +/pyhdfe-0.1.2.tar.gz diff --git a/python-pyhdfe.spec b/python-pyhdfe.spec new file mode 100644 index 0000000..7313d3c --- /dev/null +++ b/python-pyhdfe.spec @@ -0,0 +1,104 @@ +%global _empty_manifest_terminate_build 0 +Name: python-pyhdfe +Version: 0.1.2 +Release: 1 +Summary: High dimensional fixed effect absorption with Python 3 +License: MIT +URL: https://github.com/jeffgortmaker/pyhdfe +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/15/70/b16abf377dbe2abb91cc867c3fb4d1fe7633af217975910d84071bd861c0/pyhdfe-0.1.2.tar.gz +BuildArch: noarch + +Requires: python3-numpy +Requires: python3-scipy +Requires: python3-sphinx +Requires: python3-ipython +Requires: python3-astunparse +Requires: python3-sphinx-rtd-theme +Requires: python3-nbsphinx +Requires: python3-jinja2 +Requires: python3-docutils +Requires: python3-pytest +Requires: python3-pytest-xdist + +%description +The PyHDFE package has been tested on `Python <https://www.python.org/downloads/>`_ versions 3.6 through 3.9. The `SciPy instructions <https://scipy.org/install/>`_ for installing related packages is a good guide for how to install a scientific Python environment. A good choice is the `Anaconda Distribution <https://www.anaconda.com/products/distribution>`_, since, along with many other packages that are useful for scientific computing, it comes packaged with PyHDFE's only required dependencies: `NumPy <https://numpy.org/>`_ and `SciPy <https://scipy.org/>`_. +You can install the current release of PyHDFE with `pip <https://pip.pypa.io/en/latest/>`_:: + pip install pyhdfe +You can upgrade to a newer release with the ``--upgrade`` flag:: + pip install --upgrade pyhdfe +If you lack permissions, you can install PyHDFE in your user directory with the ``--user`` flag:: + pip install --user pyhdfe +Alternatively, you can download a wheel or source archive from `PyPI <https://pypi.org/project/pyhdfe/>`_. You can find the latest development code on `GitHub <https://github.com/jeffgortmaker/pyhdfe/>`_ and the latest development documentation `here <https://pyhdfe.readthedocs.io/en/latest/>`_. + +%package -n python3-pyhdfe +Summary: High dimensional fixed effect absorption with Python 3 +Provides: python-pyhdfe +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-pyhdfe +The PyHDFE package has been tested on `Python <https://www.python.org/downloads/>`_ versions 3.6 through 3.9. The `SciPy instructions <https://scipy.org/install/>`_ for installing related packages is a good guide for how to install a scientific Python environment. A good choice is the `Anaconda Distribution <https://www.anaconda.com/products/distribution>`_, since, along with many other packages that are useful for scientific computing, it comes packaged with PyHDFE's only required dependencies: `NumPy <https://numpy.org/>`_ and `SciPy <https://scipy.org/>`_. +You can install the current release of PyHDFE with `pip <https://pip.pypa.io/en/latest/>`_:: + pip install pyhdfe +You can upgrade to a newer release with the ``--upgrade`` flag:: + pip install --upgrade pyhdfe +If you lack permissions, you can install PyHDFE in your user directory with the ``--user`` flag:: + pip install --user pyhdfe +Alternatively, you can download a wheel or source archive from `PyPI <https://pypi.org/project/pyhdfe/>`_. You can find the latest development code on `GitHub <https://github.com/jeffgortmaker/pyhdfe/>`_ and the latest development documentation `here <https://pyhdfe.readthedocs.io/en/latest/>`_. + +%package help +Summary: Development documents and examples for pyhdfe +Provides: python3-pyhdfe-doc +%description help +The PyHDFE package has been tested on `Python <https://www.python.org/downloads/>`_ versions 3.6 through 3.9. The `SciPy instructions <https://scipy.org/install/>`_ for installing related packages is a good guide for how to install a scientific Python environment. A good choice is the `Anaconda Distribution <https://www.anaconda.com/products/distribution>`_, since, along with many other packages that are useful for scientific computing, it comes packaged with PyHDFE's only required dependencies: `NumPy <https://numpy.org/>`_ and `SciPy <https://scipy.org/>`_. +You can install the current release of PyHDFE with `pip <https://pip.pypa.io/en/latest/>`_:: + pip install pyhdfe +You can upgrade to a newer release with the ``--upgrade`` flag:: + pip install --upgrade pyhdfe +If you lack permissions, you can install PyHDFE in your user directory with the ``--user`` flag:: + pip install --user pyhdfe +Alternatively, you can download a wheel or source archive from `PyPI <https://pypi.org/project/pyhdfe/>`_. You can find the latest development code on `GitHub <https://github.com/jeffgortmaker/pyhdfe/>`_ and the latest development documentation `here <https://pyhdfe.readthedocs.io/en/latest/>`_. + +%prep +%autosetup -n pyhdfe-0.1.2 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-pyhdfe -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Mon Apr 10 2023 Python_Bot <Python_Bot@openeuler.org> - 0.1.2-1 +- Package Spec generated @@ -0,0 +1 @@ +3e7c31393bd2ec393e987630678cd096 pyhdfe-0.1.2.tar.gz |