Persistence

RDFLib provides an abstracted Store API for persistence of RDF and Notation 3. The Graph class works with instances of this API (as the first argument to its constructor) for triple-based management of an RDF store including: garbage collection, transaction management, update, pattern matching, removal, length, and database management (open() / close() / destroy()).

Additional persistence mechanisms can be supported by implementing this API for a different store.

Stores currently shipped with core RDFLib

• Memory (not persistent!)
• Sleepycat (on disk persistence via Python’s bsddb or bsddb3 packages)
• SPARQLStore - a read-only wrapper around a remote SPARQL Query endpoint.
• SPARQLUpdateStore - a read-write wrapper around a remote SPARQL query/update endpoint pair.

Usage

Most cases passing the name of the store to the Graph constructor is enough:

from rdflib import Graph

graph = Graph(store='Sleepycat')

Most store offering on-disk persistence will need to be opened before reading or writing. When peristing a triplestore (instead of a ConjuntiveGraph quadstore), you need to specify an identifier with which you can open the graph:

graph = Graph('Sleepycat', identifier='mygraph')

# first time create the store:
graph.open('/home/user/data/myRDFLibStore', create = True)

# work with the graph:
graph.add( mytriples )

# when done!
graph.close()

When done, close() must be called to free the resources associated with the store.

Additional store plugins

More store implementations are available in RDFLib extension projects:

• rdflib-sqlalchemy, which supports stored on a wide-variety of RDBMs backends,
• rdflib-leveldb - a store on to of Google’s LevelDB key-value store.
• rdflib-kyotocabinet - a store on to of the Kyoto Cabinet key-value store.

Example

• examples.sleepycat_example contains an example for using a Sleepycat store.
• examples.sparqlstore_example contains an example for using a SPARQLStore.