%global _empty_manifest_terminate_build 0 Name: python-Owlready2 Version: 0.41 Release: 1 Summary: A package for ontology-oriented programming in Python: load OWL 2.0 ontologies as Python objects, modify them, save them, and perform reasoning via HermiT. Includes an optimized RDF quadstore. License: LGPLv3+ URL: https://bitbucket.org/jibalamy/owlready2 Source0: https://mirrors.nju.edu.cn/pypi/web/packages/39/38/a1d1a8a67c083131599382596a3e8b1a37abd3644cf80dbec15181640c26/Owlready2-0.41.tar.gz BuildArch: noarch %description Owlready2 is a module for ontology-oriented programming in Python 3. It can manage ontologies and knwoledge graphs, and includes an optimized RDF/OWL quadstore. Owlready2 can: - Import OWL 2.0 ontologies in NTriples, RDF/XML or OWL/XML format - Export OWL 2.0 ontologies to NTriples or RDF/XML - Manipulates ontology classes, instances and properties transparently, as if they were normal Python objects - Add Python methods to ontology classes - Perform automatic classification of classes and instances, using the HermiT or Pellet reasoner (included) - Load DBpedia or UMLS (for medical terminology, using the integrated PyMedTermino2 submodule) - Native support for optimized SPARQL queries - Tested up to 1 billion of RDF triples! (but can potentially support more) - In addition, the quadstore is compatible with the RDFlib Python module - Finally, Owlready2 can also be used as an ORM (Object-Relational mapper) -- as a graph/object database, it beats Neo4J, MongoDB, SQLObject and SQLAlchemy in terms of performances Owlready has been created by Jean-Baptiste Lamy at the LIMICS reseach lab. It is available under the GNU LGPL licence v3. If you use Owlready in scientific works, **please cite the following article**: **Lamy JB**. `Owlready: Ontology-oriented programming in Python with automatic classification and high level constructs for biomedical ontologies. `_ **Artificial Intelligence In Medicine 2017**;80:11-28 In case of troubles, questions or comments, please use this Forum/Mailing list: http://owlready.306.s1.nabble.com %package -n python3-Owlready2 Summary: A package for ontology-oriented programming in Python: load OWL 2.0 ontologies as Python objects, modify them, save them, and perform reasoning via HermiT. Includes an optimized RDF quadstore. Provides: python-Owlready2 BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-Owlready2 Owlready2 is a module for ontology-oriented programming in Python 3. It can manage ontologies and knwoledge graphs, and includes an optimized RDF/OWL quadstore. Owlready2 can: - Import OWL 2.0 ontologies in NTriples, RDF/XML or OWL/XML format - Export OWL 2.0 ontologies to NTriples or RDF/XML - Manipulates ontology classes, instances and properties transparently, as if they were normal Python objects - Add Python methods to ontology classes - Perform automatic classification of classes and instances, using the HermiT or Pellet reasoner (included) - Load DBpedia or UMLS (for medical terminology, using the integrated PyMedTermino2 submodule) - Native support for optimized SPARQL queries - Tested up to 1 billion of RDF triples! (but can potentially support more) - In addition, the quadstore is compatible with the RDFlib Python module - Finally, Owlready2 can also be used as an ORM (Object-Relational mapper) -- as a graph/object database, it beats Neo4J, MongoDB, SQLObject and SQLAlchemy in terms of performances Owlready has been created by Jean-Baptiste Lamy at the LIMICS reseach lab. It is available under the GNU LGPL licence v3. If you use Owlready in scientific works, **please cite the following article**: **Lamy JB**. `Owlready: Ontology-oriented programming in Python with automatic classification and high level constructs for biomedical ontologies. `_ **Artificial Intelligence In Medicine 2017**;80:11-28 In case of troubles, questions or comments, please use this Forum/Mailing list: http://owlready.306.s1.nabble.com %package help Summary: Development documents and examples for Owlready2 Provides: python3-Owlready2-doc %description help Owlready2 is a module for ontology-oriented programming in Python 3. It can manage ontologies and knwoledge graphs, and includes an optimized RDF/OWL quadstore. Owlready2 can: - Import OWL 2.0 ontologies in NTriples, RDF/XML or OWL/XML format - Export OWL 2.0 ontologies to NTriples or RDF/XML - Manipulates ontology classes, instances and properties transparently, as if they were normal Python objects - Add Python methods to ontology classes - Perform automatic classification of classes and instances, using the HermiT or Pellet reasoner (included) - Load DBpedia or UMLS (for medical terminology, using the integrated PyMedTermino2 submodule) - Native support for optimized SPARQL queries - Tested up to 1 billion of RDF triples! (but can potentially support more) - In addition, the quadstore is compatible with the RDFlib Python module - Finally, Owlready2 can also be used as an ORM (Object-Relational mapper) -- as a graph/object database, it beats Neo4J, MongoDB, SQLObject and SQLAlchemy in terms of performances Owlready has been created by Jean-Baptiste Lamy at the LIMICS reseach lab. It is available under the GNU LGPL licence v3. If you use Owlready in scientific works, **please cite the following article**: **Lamy JB**. `Owlready: Ontology-oriented programming in Python with automatic classification and high level constructs for biomedical ontologies. `_ **Artificial Intelligence In Medicine 2017**;80:11-28 In case of troubles, questions or comments, please use this Forum/Mailing list: http://owlready.306.s1.nabble.com %prep %autosetup -n Owlready2-0.41 %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-Owlready2 -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Wed Apr 12 2023 Python_Bot - 0.41-1 - Package Spec generated