%global _empty_manifest_terminate_build 0
Name:		python-parquery
Version:	0.2.8
Release:	1
Summary:	A query and aggregation framework for Parquet
License:	MIT
URL:		https://github.com/visualfabriq/parquery
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/c9/cc/e4439dafb231f64d0e5735f94e3d57bd5a42a6f4d7c2e6e2502bbaf7d7d0/parquery-0.2.8.tar.gz
BuildArch:	noarch


%description
ParQuery is a query and aggregation framework for parquet files, enabling very fast big data aggregations on any hardware (from laptops to clusters). ParQuery is used in production environments to handle reporting and data retrieval queries over hundreds of files that each can contain billions of records.
Parquet is a light weight package that provides columnar, chunked data containers that can be compressed on-disk. It excels at storing and sequentially accessing large, numerical data sets.
The ParQuery framework provides methods to perform query and aggregation operations on Parquet containers using Pandas. It also contains helpers to use pyarrow for serializing and de-serializing dataframes. It is based on an OLAP-approach to aggregations with Dimensions and Measures.
Visualfabriq uses Parquet and ParQuery to reliably handle billions of records for our clients with real-time reporting and machine learning usage. ParQuery requires pyarrow; for details see the requirements.txt. 

%package -n python3-parquery
Summary:	A query and aggregation framework for Parquet
Provides:	python-parquery
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-parquery
ParQuery is a query and aggregation framework for parquet files, enabling very fast big data aggregations on any hardware (from laptops to clusters). ParQuery is used in production environments to handle reporting and data retrieval queries over hundreds of files that each can contain billions of records.
Parquet is a light weight package that provides columnar, chunked data containers that can be compressed on-disk. It excels at storing and sequentially accessing large, numerical data sets.
The ParQuery framework provides methods to perform query and aggregation operations on Parquet containers using Pandas. It also contains helpers to use pyarrow for serializing and de-serializing dataframes. It is based on an OLAP-approach to aggregations with Dimensions and Measures.
Visualfabriq uses Parquet and ParQuery to reliably handle billions of records for our clients with real-time reporting and machine learning usage. ParQuery requires pyarrow; for details see the requirements.txt. 

%package help
Summary:	Development documents and examples for parquery
Provides:	python3-parquery-doc
%description help
ParQuery is a query and aggregation framework for parquet files, enabling very fast big data aggregations on any hardware (from laptops to clusters). ParQuery is used in production environments to handle reporting and data retrieval queries over hundreds of files that each can contain billions of records.
Parquet is a light weight package that provides columnar, chunked data containers that can be compressed on-disk. It excels at storing and sequentially accessing large, numerical data sets.
The ParQuery framework provides methods to perform query and aggregation operations on Parquet containers using Pandas. It also contains helpers to use pyarrow for serializing and de-serializing dataframes. It is based on an OLAP-approach to aggregations with Dimensions and Measures.
Visualfabriq uses Parquet and ParQuery to reliably handle billions of records for our clients with real-time reporting and machine learning usage. ParQuery requires pyarrow; for details see the requirements.txt. 

%prep
%autosetup -n parquery-0.2.8

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

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

%changelog
* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.2.8-1
- Package Spec generated