Django RDF
djangordf is a Django library for managing RDF data with a declarative model layer. Domain classes are written like Django models but persist as triples in a SPARQL 1.1 triple store, with built-in SKOS conventions, language-tagged literals, and a lazy queryset that mirrors Django's manager API.
Full reference documentation: https://djangordf.readthedocs.io/.
Features
RDFModel— declarative base class withclass_iri,namespace, andgraph_iriconfigured through aMetainner class. Defaults toskos:Conceptand uses the namespace and graph IRIs from Django settings.- Property types —
DataPropertyfor typed literals,LangStringPropertyforrdf:langString(using theLangStringdataclass),ObjectPropertyfor instance-to-instance links (with lazy"self"and string-name target resolution), andURIPropertyfor raw IRIs. Each supportsmany=True/Falsecardinality. - SKOS defaults — properties named
pref_label,alt_label,broader,narrower, etc. resolve to their SKOS predicates automatically; no explicitpredicate=needed for the conventions. RDFManager+ lazyRDFQuerySet— Django-styleobjects.create,objects.get,objects.all,objects.filter.saveis idempotent and overwrites stale triples in a single SPARQL update;deletestrips every triple for the IRI.- Backends — ships an
InMemoryBackend(rdflib, good for tests and local development) and aFusekiBackend(SPARQL 1.1 HTTP, works against Apache Jena Fuseki, GraphDB, Blazegraph, Stardog). NamespaceRegistry— register prefixes throughDJANGORDF_NAMESPACESand resolve CURIEs like"skos:Concept"into fullURIRefobjects.- Legacy
export_model_to_rdf— the original Django-model-to-RDF exporter from earlier releases still works unchanged.
Installation
pip install djangordf
Add the app to INSTALLED_APPS and configure a backend:
# settings.py
INSTALLED_APPS = [
# ...
"djangordf",
]
DJANGORDF_BACKEND = {
"class": "djangordf.backends.memory.InMemoryBackend",
}
DJANGORDF_DEFAULT_NAMESPACE = "http://example.org/data/"
DJANGORDF_DEFAULT_GRAPH = "http://example.org/graph/default"
DJANGORDF_NAMESPACES = {
"ex": "http://example.org/vocab/",
}
Talking to a real triple store
Swap in the Fuseki backend (or any SPARQL 1.1 endpoint):
DJANGORDF_BACKEND = {
"class": "djangordf.backends.fuseki.FusekiBackend",
"endpoint": "http://localhost:3030/judaicalink",
# optional:
"user": "admin",
"password": "secret",
}
The repository ships a docker-compose.yml that boots a local Fuseki
for development; opt-in integration tests behind the @pytest.mark.fuseki
marker exercise the HTTP path end-to-end.
Usage
Define a model:
from djangordf import (
RDFModel,
LangStringProperty,
ObjectProperty,
)
from djangordf.namespaces import LangString
class Term(RDFModel):
pref_label = LangStringProperty(many=True)
alt_label = LangStringProperty(many=True)
broader = ObjectProperty("self", many=True)
No class Meta, no predicate= arguments: Term defaults to
skos:Concept, and pref_label / alt_label / broader resolve to
their SKOS predicates through the convention map. Mint, query, link:
buch = Term.objects.create(
pref_label=[LangString("Buch", "de"), LangString("Book", "en")],
)
roman = Term.objects.create(
pref_label=[LangString("Roman", "de")],
broader=[buch],
)
reloaded = Term.objects.get(roman.iri)
assert reloaded.broader[0].iri == buch.iri
assert any(
ls.lang == "en" and ls.value == "Book"
for ls in buch.pref_label
)
save is idempotent — calling it twice does not duplicate triples.
Updates overwrite previous values in one SPARQL transaction:
buch.pref_label = [LangString("Buch (überarbeitet)", "de")]
buch.save()
Queries return a lazy RDFQuerySet; the store is only hit on
iteration, len, count, or first:
for term in Term.objects.all():
print(term.iri, term.pref_label)
assert Term.objects.filter(broader=buch).count() == 1
Explicit predicates and CURIE-based class IRIs are also supported:
from rdflib import URIRef
from rdflib.namespace import XSD
from djangordf import DataProperty, URIProperty
class Person(RDFModel):
name = DataProperty(
predicate=URIRef("http://xmlns.com/foaf/0.1/name"),
datatype=XSD.string,
)
homepage = URIProperty(
predicate=URIRef("http://xmlns.com/foaf/0.1/homepage"),
)
class Meta:
class_iri = "foaf:Person" # resolved via NamespaceRegistry
namespace = "http://example.org/people/"
graph_iri = "http://example.org/graph/people"
Walking-skeleton example
A self-contained, runnable end-to-end example lives at
examples/walking_skeleton.py. It
mirrors the design spec's acceptance script and exits 0 against the
default in-memory backend:
python examples/walking_skeleton.py
Legacy Django-to-RDF export
The original export_model_to_rdf(QuerySet, ...) function is still
available for one-shot dumps of relational Django data into a Turtle
file; see djangordf/functions.py and the existing tests in
tests/test_export.py.
Settings reference
| Setting | Purpose | Default |
|---|---|---|
DJANGORDF_BACKEND |
Triple-store backend config (dict with class plus kwargs) |
In-memory backend |
DJANGORDF_DEFAULT_NAMESPACE |
Used to mint IRIs when Meta.namespace is silent |
urn:djangordf:<model>: |
DJANGORDF_DEFAULT_GRAPH |
Used when Meta.graph_iri is silent |
urn:djangordf:default |
DJANGORDF_NAMESPACES |
prefix -> uri map read into the NamespaceRegistry at app ready |
{} |
License
This project is licensed under the MIT License.
Metadata
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