Quickstart

from rdflib import Graph
from arango import ArangoClient
from arango_rdf import ArangoRDF

db = ArangoClient().db()

adbrdf = ArangoRDF(db)

def beatles():
   g = Graph()
   g.parse("https://raw.githubusercontent.com/ArangoDB-Community/ArangoRDF/main/tests/data/rdf/beatles.ttl", format="ttl")
   return g

ArangoDB to RDF

Note: RDF-to-ArangoDB functionality has been implemented using concepts described in the paper Transforming RDF-star to Property Graphs: A Preliminary Analysis of Transformation Approaches. So we offer two transformation approaches:

# 1. RDF-Topology Preserving Transformation (RPT)
adbrdf.rdf_to_arangodb_by_rpt(name="BeatlesRPT", rdf_graph=beatles(), overwrite_graph=True)

# 2. Property Graph Transformation (PGT)
adbrdf.rdf_to_arangodb_by_pgt(name="BeatlesPGT", rdf_graph=beatles(), overwrite_graph=True)

RDF to ArangoDB

# pip install arango-datasets
from arango_datasets import Datasets

name = "OPEN_INTELLIGENCE_ANGOLA"
Datasets(db).load(name)

# 1. Graph to RDF
rdf_graph = adbrdf.arangodb_graph_to_rdf(name, rdf_graph=Graph())

# 2. Collections to RDF
rdf_graph_2 = adbrdf.arangodb_collections_to_rdf(
   name,
   rdf_graph=Graph(),
   v_cols={"Event", "Actor", "Source"},
   e_cols={"eventActor", "hasSource"},
)

# 3. Metagraph to RDF
rdf_graph_3 = adbrdf.arangodb_to_rdf(
   name=name,
   rdf_graph=Graph(),
   metagraph={
      "vertexCollections": {
            "Event": {"date", "description", "fatalities"},
            "Actor": {"name"}
      },
      "edgeCollections": {
            "eventActor": {}
      },
   },
)