A module 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.
Owlready2 is a module for ontology-oriented programming in Python 3, including an optimized RDF quadstore.
- 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 reasoner.
- Tested up to 100 millions of RDF triples (but can potentially support more).
- In addition, the quadstore is compatible with the RDFlib Pyton module, which can be used to perform SPARQL queries.
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;80C:11-28
In case of troubles, questions or comments, please use this Forum/Mailing list: http://owlready.8326.n8.nabble.com
What can I do with Owlready2?
Load an ontology from a local repository, or from Internet:
>>> from owlready2 import * >>> onto_path.append("/path/to/your/local/ontology/repository") >>> onto = get_ontology("http://www.lesfleursdunormal.fr/static/_downloads/pizza_onto.owl") >>> onto.load()
Create new classes in the ontology, possibly mixing OWL constructs and Python methods:
>>> class NonVegetarianPizza(onto.Pizza): ... equivalent_to = [ ... onto.Pizza ... & ( onto.has_topping.some(onto.MeatTopping) ... | onto.has_topping.some(onto.FishTopping) ... ) ] ... def eat(self): print("Beurk! I'm vegetarian!")
Access ontology class, and create new instances / individuals:
>>> onto.Pizza pizza_onto.Pizza >>> test_pizza = onto.Pizza("test_pizza_owl_identifier") >>> test_pizza.has_topping = [ onto.CheeseTopping(), ... onto.TomatoTopping(), ... onto.MeatTopping () ]
Export to RDF/XML file:
Perform reasoning, and classify instances and classes:
>>> test_pizza.__class__ onto.Pizza >>> # Execute HermiT and reparent instances and classes >>> sync_reasoner() >>> test_pizza.__class__ onto.NonVegetarianPizza >>> test_pizza.eat() Beurk! I'm vegetarian !
For more documentation, look at the doc/ directories in the source.
version 1 - 0.2
- Fix sync_reasonner and Hermit call under windows (thanks Clare Grasso)
version 1 - 0.3
- Add warnings
- Accepts ontologies files that do not ends with ‘.owl’
- Fix a bug when loading ontologies including concept without a ‘#’ in their IRI
version 2 - 0.1
- Full rewrite, including an optimized quadstore
version 2 - 0.2
- Implement RDFXML parser and generator in Python (no longer use rapper or rdflib)
- Property chain support
- Add ntriples_diff.py utility
- Bugfixes: - Fix breaklines in literal when exporting to NTriples
version 2 - 0.3
- Add destroy_entity() global function
- Greatly improve performance for individual creation
- When searching, allow to use “*” as a jocker for any object
- Bugfixes: - Fix nested intersections and unions - Fix boolean - Fix bug when removing parent properties - Fix parsing of rdf:ID - Fix multiple loading of the same ontology whose IRI is modified by OWL file, using an ontology alias table - Fix ClassConstruct.subclasses() - Check for properties with multiple incompatible classes (e.g. ObjectProperty and Annotation Property)
version 2 - 0.4
- Add methods for querying the properties defined for a given individuals, the inverse properties and the relation instances (.get_properties(), .get_inverse_properties() and .get_relations())
- Add .indirect() method to obtain indirect relations (considering subproperties, transivitity, symmetry and reflexibity)
- search() now takes into account inheritance and inverse properties
- search() now accepts ‘None’ for searching for entities without a given relation
- Optimize ontology loading by recreating SQL index from scratch
- Optimize SQL query for transitive quadstore queries, using RECURSIVE Sqlite3 statements
- Optimize SQL query for obtaining the number of RDF triples (ie len(default_world.graph))
- Add Artificial Intelligence In Medicine scientific article in doc and Readme
- Bugfixes: - Fix properties loading when reusing an ontology from a disk-stored quadstore - Fix _inherited_property_value_restrictions() when complement (Not) is involved - Fix restrictions with cardinality - Fix doc on AllDisjoint / AllDifferent