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%global _empty_manifest_terminate_build 0
Name: python-ph
Version: 1.1.5
Release: 1
Summary: ph - the tabular data shell tool
License: MIT
URL: https://github.com/pgdr/ph
Source0: https://mirrors.aliyun.com/pypi/web/packages/e5/a4/323f30fbe76846de859abe24a50b453378f206e0faccae65e1df49817ccc/ph-1.1.5.tar.gz
BuildArch: noarch
%description
## Raison d'être
Using the _pipeline_ in Linux is nothing short of a dream in the life of the
computer super user.
However the pipe is clearly most suited for a stream of lines of textual data,
and not when the stream is actually tabular data.
Tabular data is much more complex to work with due to its dual indexing and the
fact that we often read horizontally and often read vertically.
The defacto format for tabular data is `csv`
([comma-separated values](https://en.wikipedia.org/wiki/Comma-separated_values),
which is not perfect in any sense
of the word), and the defacto tool for working with tabular data in Python is
Pandas.
This is a shell utility `ph` (pronounced _phi_)
that reads tabular data from
[_standard in_](https://en.wikipedia.org/wiki/Standard_streams#Standard_input_(stdin))
and allows
you to perform a pandas function on the data, before writing it to standard out
in `csv` format.
The goal is to create a tool which makes it nicer to work with tabular data in a
pipeline.
To achieve the goal, `ph` then reads csv data, does some manipulation,
and prints out csv data. With csv as the invariant, `ph` can be used in
%package -n python3-ph
Summary: ph - the tabular data shell tool
Provides: python-ph
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-ph
## Raison d'être
Using the _pipeline_ in Linux is nothing short of a dream in the life of the
computer super user.
However the pipe is clearly most suited for a stream of lines of textual data,
and not when the stream is actually tabular data.
Tabular data is much more complex to work with due to its dual indexing and the
fact that we often read horizontally and often read vertically.
The defacto format for tabular data is `csv`
([comma-separated values](https://en.wikipedia.org/wiki/Comma-separated_values),
which is not perfect in any sense
of the word), and the defacto tool for working with tabular data in Python is
Pandas.
This is a shell utility `ph` (pronounced _phi_)
that reads tabular data from
[_standard in_](https://en.wikipedia.org/wiki/Standard_streams#Standard_input_(stdin))
and allows
you to perform a pandas function on the data, before writing it to standard out
in `csv` format.
The goal is to create a tool which makes it nicer to work with tabular data in a
pipeline.
To achieve the goal, `ph` then reads csv data, does some manipulation,
and prints out csv data. With csv as the invariant, `ph` can be used in
%package help
Summary: Development documents and examples for ph
Provides: python3-ph-doc
%description help
## Raison d'être
Using the _pipeline_ in Linux is nothing short of a dream in the life of the
computer super user.
However the pipe is clearly most suited for a stream of lines of textual data,
and not when the stream is actually tabular data.
Tabular data is much more complex to work with due to its dual indexing and the
fact that we often read horizontally and often read vertically.
The defacto format for tabular data is `csv`
([comma-separated values](https://en.wikipedia.org/wiki/Comma-separated_values),
which is not perfect in any sense
of the word), and the defacto tool for working with tabular data in Python is
Pandas.
This is a shell utility `ph` (pronounced _phi_)
that reads tabular data from
[_standard in_](https://en.wikipedia.org/wiki/Standard_streams#Standard_input_(stdin))
and allows
you to perform a pandas function on the data, before writing it to standard out
in `csv` format.
The goal is to create a tool which makes it nicer to work with tabular data in a
pipeline.
To achieve the goal, `ph` then reads csv data, does some manipulation,
and prints out csv data. With csv as the invariant, `ph` can be used in
%prep
%autosetup -n ph-1.1.5
%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-ph -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 1.1.5-1
- Package Spec generated
|
