%global _empty_manifest_terminate_build 0
Name:		python-py-heat
Version:	0.0.6
Release:	1
Summary:	pprofile + matplotlib = Python program profiled as an awesome heatmap!
License:	MIT
URL:		https://github.com/csurfer/pyheat
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/6b/e3/776c6f4f18eafbc39b44ad47160414077bfd64183cfd2c5b61ea43dd12b6/py-heat-0.0.6.tar.gz
BuildArch:	noarch


%description
|pypiv| |pyv| |Licence| |Build Status| |Coverage Status| |Thanks|
Profilers are extremely helpful tools. They help us dig deep into code,
find and understand performance bottlenecks. But sometimes we just want
to lay back, relax and still get a gist of the hot zones in our code.
    A picture is worth a thousand words.
So, instead of presenting the data in tabular form, if presented as a
heatmap visualization, it makes comprehending the time distribution in
the given program much easier and quicker. That is exactly what is being
done here !

%package -n python3-py-heat
Summary:	pprofile + matplotlib = Python program profiled as an awesome heatmap!
Provides:	python-py-heat
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-py-heat
|pypiv| |pyv| |Licence| |Build Status| |Coverage Status| |Thanks|
Profilers are extremely helpful tools. They help us dig deep into code,
find and understand performance bottlenecks. But sometimes we just want
to lay back, relax and still get a gist of the hot zones in our code.
    A picture is worth a thousand words.
So, instead of presenting the data in tabular form, if presented as a
heatmap visualization, it makes comprehending the time distribution in
the given program much easier and quicker. That is exactly what is being
done here !

%package help
Summary:	Development documents and examples for py-heat
Provides:	python3-py-heat-doc
%description help
|pypiv| |pyv| |Licence| |Build Status| |Coverage Status| |Thanks|
Profilers are extremely helpful tools. They help us dig deep into code,
find and understand performance bottlenecks. But sometimes we just want
to lay back, relax and still get a gist of the hot zones in our code.
    A picture is worth a thousand words.
So, instead of presenting the data in tabular form, if presented as a
heatmap visualization, it makes comprehending the time distribution in
the given program much easier and quicker. That is exactly what is being
done here !

%prep
%autosetup -n py-heat-0.0.6

%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-py-heat -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Tue May 30 2023 Python_Bot <Python_Bot@openeuler.org> - 0.0.6-1
- Package Spec generated