%global _empty_manifest_terminate_build 0 Name: python-splicer Version: 0.2.1 Release: 1 Summary: the world is a database now you can query it with SQL License: UNKNOWN URL: http://github.com/trivio/splicer Source0: https://mirrors.nju.edu.cn/pypi/web/packages/d6/88/fa02e80958597b9430a61d229f536f2fa54828cb2ce41c4d9973c8c7ca33/splicer-0.2.1.tar.gz BuildArch: noarch %description ``splicer`` makes the entire world look like a SQL database. It is a python module for working with data from disparate sources using commands to those familiar with SQL. It aims to make quick one off queries and ETL scripts more declarative rather than procedural. Inspired by projects like BigQuery, Postgres Foreign Data Wrappers and Multicorn, except no database is required. ``splicer`` enables: * Analysts to create Datasets linking various foreign tables together along with User Defined Functions written in python. Once defined, the datasets can be queried via SQL Select statements to create new Views of the Data. * Extension Developers to create extensions that make various data sources REST endpoints, log files, NoSQL Servers, traditional Databases, CSV Files to behave like tables. ``splicer`` will take advantage of these various sources' capabilities where appropriate and will compensate for sources that lack basic features. For example if a database supports joins and you want to query two tables within that database, ``splicer`` will have that system perform the join for you. If however you're working with a less sophisticated source, like plain files, ``splicer`` will perform the operations for you locally. Enough reading! [Try it out][1] [1]: https://splicer.readthedocs.org/en/latest/install.html#installation "Installing Splicer" %package -n python3-splicer Summary: the world is a database now you can query it with SQL Provides: python-splicer BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-splicer ``splicer`` makes the entire world look like a SQL database. It is a python module for working with data from disparate sources using commands to those familiar with SQL. It aims to make quick one off queries and ETL scripts more declarative rather than procedural. Inspired by projects like BigQuery, Postgres Foreign Data Wrappers and Multicorn, except no database is required. ``splicer`` enables: * Analysts to create Datasets linking various foreign tables together along with User Defined Functions written in python. Once defined, the datasets can be queried via SQL Select statements to create new Views of the Data. * Extension Developers to create extensions that make various data sources REST endpoints, log files, NoSQL Servers, traditional Databases, CSV Files to behave like tables. ``splicer`` will take advantage of these various sources' capabilities where appropriate and will compensate for sources that lack basic features. For example if a database supports joins and you want to query two tables within that database, ``splicer`` will have that system perform the join for you. If however you're working with a less sophisticated source, like plain files, ``splicer`` will perform the operations for you locally. Enough reading! [Try it out][1] [1]: https://splicer.readthedocs.org/en/latest/install.html#installation "Installing Splicer" %package help Summary: Development documents and examples for splicer Provides: python3-splicer-doc %description help ``splicer`` makes the entire world look like a SQL database. It is a python module for working with data from disparate sources using commands to those familiar with SQL. It aims to make quick one off queries and ETL scripts more declarative rather than procedural. Inspired by projects like BigQuery, Postgres Foreign Data Wrappers and Multicorn, except no database is required. ``splicer`` enables: * Analysts to create Datasets linking various foreign tables together along with User Defined Functions written in python. Once defined, the datasets can be queried via SQL Select statements to create new Views of the Data. * Extension Developers to create extensions that make various data sources REST endpoints, log files, NoSQL Servers, traditional Databases, CSV Files to behave like tables. ``splicer`` will take advantage of these various sources' capabilities where appropriate and will compensate for sources that lack basic features. For example if a database supports joins and you want to query two tables within that database, ``splicer`` will have that system perform the join for you. If however you're working with a less sophisticated source, like plain files, ``splicer`` will perform the operations for you locally. Enough reading! [Try it out][1] [1]: https://splicer.readthedocs.org/en/latest/install.html#installation "Installing Splicer" %prep %autosetup -n splicer-0.2.1 %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-splicer -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue Apr 25 2023 Python_Bot - 0.2.1-1 - Package Spec generated