owlrl
A simple implementation of the OWL2 RL Profile, as well as a basic RDFS inference, on top of RDFLib. Based mechanical forward chaining.
Decision gist · record as of 2026-08-14
Yes. OWL-RL is actively maintained, has low install friction, no security vulnerabilities, and solves a specific and well-defined problem in semantic web reasoning. The unclear license treatment warrants a quick review of LICENSE.txt, but the package is suitable for projects that need OWL2 RL or RDFS inference on rdflib graphs.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires RDFLib 7.6.0 or newer.
- Low friction: pure Python wheel with a single runtime dependency (rdflib).
- Actively maintained with last commit 2026-08-06.
License · maintenance · safety
W3C-20150513 (unclear) — Licensed under W3C-20150513 (W3C© SOFTWARE NOTICE AND LICENSE). License treatment is marked unclear; review LICENSE.txt before use in proprietary or commercial contexts to confirm compatibility with your project.
last release 2026-07-08 (37 days) · last repo commit 2026-08-06 · 177 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,112,524 downloads/mo, #4,354 on PyPI
Alternatives
Verify before relying
pip install owlrl
from owlrl import DeductiveClosure
from rdflib import Graph
g = Graph()
g.parse('data.ttl')
DeductiveClosure(g).expand()- Performance characteristics and scalability limits for large RDF graphs.
- Whether the forward-chaining approach is suitable for real-time or streaming inference workloads.
- Specific OWL2 RL axioms and RDFS rules that are fully implemented versus those with known limitations.
- Performance impact of optional integration with PyOxigraph compared to native rdflib stores.
What it is and what it does
OWL-RL is a Python library that performs logical inference on RDF graphs according to the OWL2 RL Profile and RDFS specifications. It sits on top of rdflib and uses forward-chaining rules to derive new triples from existing ones, expanding your graph with inferred knowledge. The library is designed for semantic web applications where you need to apply standardized reasoning rules to RDF data—for example, inferring that if A is a subclass of B and B is a subclass of C, then A is a subclass of C.
The package includes command-line tools for transforming RDF files and optional integration with PyOxigraph for compatibility with in-memory stores. It requires rdflib 7.6.0 or newer and supports Python 3.9 through 3.13, with no known security vulnerabilities.
Use it for
- Expand an RDF knowledge graph with inferred triples derived from OWL2 RL rules and RDFS semantics.
- Build semantic web applications that need to apply standardized reasoning to linked data.
- Validate or enrich RDF data by deriving implicit relationships and classifications.
- Convert or transform RDF files using the command-line owlrl script with inference applied.
- Integrate reasoning into an application already using rdflib for graph management.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
OWL-RL is actively maintained, has low install friction, no security vulnerabilities, and solves a specific and well-defined problem in semantic web reasoning. The unclear license treatment warrants a quick review of LICENSE.txt, but the package is suitable for projects that need OWL2 RL or RDFS inference on rdflib graphs.
Install
owlrl on PyPI
Before you install
Low friction: pure Python wheel with a single runtime dependency (rdflib). Actively maintained with last commit 2026-08-06. Supports Python 3.9 through 3.13.
Requires RDFLib 7.6.0 or newer.
License in practice
Licensed under W3C-20150513 (W3C© SOFTWARE NOTICE AND LICENSE). License treatment is marked unclear; review LICENSE.txt before use in proprietary or commercial contexts to confirm compatibility with your project.
Quickstart
pip install owlrl
from owlrl import DeductiveClosure
from rdflib import Graph
g = Graph()
g.parse('data.ttl')
DeductiveClosure(g).expand()Verify before relying
- Performance characteristics and scalability limits for large RDF graphs.
- Whether the forward-chaining approach is suitable for real-time or streaming inference workloads.
- Specific OWL2 RL axioms and RDFS rules that are fully implemented versus those with known limitations.
- Performance impact of optional integration with PyOxigraph compared to native rdflib stores.
Package facts
| License | W3C-20150513 unclear |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagerdflib |
| Maintenance | Actively maintained 37 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 1,112,524 / month, #4,354 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI ApprovedProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.9 |
Evidence: owlrl-7.6.2-py3-none-any.whl
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See also owlready2 · pyshacl · rdflib · CFGraph · SPARQLWrapper · prov · sparqlslurper · rdflib-jsonld · followthemoney · pyrdfa3