{"categories":[{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/20"},{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/10"}],"enrichment":{"capability":"Owlready2 is a Python module for ontology-oriented programming that loads, manipulates, and reasons over OWL 2.0 ontologies and RDF knowledge graphs, with an embedded optimized quadstore and support for HermiT/Pellet reasoners.","skillfed_tags":["ontology-reasoning","knowledge-graphs","semantic-web"],"use_cases":["Load and programmatically manipulate biomedical ontologies (UMLS, SNOMED CT) for terminology mapping and knowledge extraction.","Build semantic knowledge graphs by creating OWL classes and instances in Python, then export to standard RDF/XML formats.","Query and reason over large RDF datasets using SPARQL and automatic classification with HermiT or Pellet reasoners.","Use as a graph database alternative for ontology-backed object storage with semantic reasoning capabilities.","Integrate OWL-based domain models into Python applications while maintaining OWL 2.0 compliance and reasoning."],"what_it_does":"Owlready2 is a Python framework for working with OWL 2.0 ontologies and RDF knowledge graphs as if they were native Python objects. It provides transparent manipulation of ontology classes, instances, and properties, automatic reasoning and classification via embedded reasoners, and an optimized quadstore backend that can handle large-scale RDF datasets. The package supports multiple serialization formats (NTriples, RDF/XML, OWL/XML), SPARQL querying, and can be used as an object-relational mapper for graph-based data storage.\n\nThe module is designed for knowledge representation and semantic reasoning tasks, particularly in biomedical and scientific domains. It includes built-in support for medical terminologies through PyMedTermino2, allows mixing OWL constructs with Python methods on classes, and integrates with RDFlib. The main constraint is that it distributes as source code only, requiring compilation during installation.","worth_installing":"Yes, with conditions. Owlready2 is production-stable, actively maintained, and solves a specific problem\u2014ontology-oriented programming in Python. The copyleft LGPL-3.0-or-later license is acceptable for most open-source projects but requires review for proprietary use. High install friction (source-only distribution requiring compilation) is a real barrier; ensure your environment has a C compiler and development headers. If you need OWL/RDF manipulation, semantic reasoning, or knowledge graph management in Python, it is worth the setup cost."},"id":"owlready2","links":{"html":"https://skillfed.io/packages/owlready2","md":"https://skillfed.io/packages/owlready2.md","pypi":"https://pypi.org/project/owlready2/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-06-22","license_spdx":"LGPL-3.0-or-later","license_treatment":"copyleft","name":"owlready2","python_support":"supports_current","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."},"popularity":{"monthly_downloads":96791,"position":13193,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.51"}