djangordf 0.9.0

A RDF library for Django models

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 with class_iri, namespace, and graph_iri configured through a Meta inner class. Defaults to skos:Concept and uses the namespace and graph IRIs from Django settings.
• Property types — DataProperty for typed literals, LangStringProperty for rdf:langString (using the LangString dataclass), ObjectProperty for instance-to-instance links (with lazy "self" and string-name target resolution), and URIProperty for raw IRIs. Each supports many=True/False cardinality.
• SKOS defaults — properties named pref_label, alt_label, broader, narrower, etc. resolve to their SKOS predicates automatically; no explicit predicate= needed for the conventions.
• RDFManager + lazy RDFQuerySet — Django-style objects.create, objects.get, objects.all, objects.filter. save is idempotent and overwrites stale triples in a single SPARQL update; delete strips every triple for the IRI.
• Backends — ships an InMemoryBackend (rdflib, good for tests and local development) and a FusekiBackend (SPARQL 1.1 HTTP, works against Apache Jena Fuseki, GraphDB, Blazegraph, Stardog).
• NamespaceRegistry — register prefixes through DJANGORDF_NAMESPACES and resolve CURIEs like "skos:Concept" into full URIRef objects.
• 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.