automatic import of python-parqueryopeneuler20.03

3 files changed, 83 insertions, 0 deletions

diff --git a/.gitignore b/.gitignore
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+/parquery-0.2.8.tar.gz
diff --git a/python-parquery.spec b/python-parquery.spec
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+%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
diff --git a/sources b/sources
new file mode 100644
index 0000000..7d3bf6f
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+66a937da4b46700fb7f3949e6dc8e137  parquery-0.2.8.tar.gz