Navigating Graphs¶
An RDF Graph is a set of RDF triples, and we try to mirror exactly this in RDFLib. The Python
Graph()
tries to emulate a container type.
Graphs as Iterators¶
RDFLib graphs override __iter__()
in order to support iteration over the contained triples:
for s, p, o in someGraph:
if not (s, p, o) in someGraph:
raise Exception("Iterator / Container Protocols are Broken!!")
This loop iterates through all the subjects(s), predicates (p) & objects (o) in someGraph
.
Contains check¶
Graphs implement __contains__()
, so you can check if a triple is in a graph with a
triple in graph
syntax:
from rdflib import URIRef
from rdflib.namespace import RDF
bob = URIRef("http://example.org/people/bob")
if (bob, RDF.type, FOAF.Person) in graph:
print("This graph knows that Bob is a person!")
Note that this triple does not have to be completely bound:
if (bob, None, None) in graph:
print("This graph contains triples about Bob!")
Set Operations on RDFLib Graphs¶
Graphs override several pythons operators: __iadd__()
, __isub__()
,
etc. This supports addition, subtraction and other setoperations on Graphs:
operation 
effect 


return new graph with union (triples on both) 

in place union / addition 

return new graph with difference (triples in G1, not in G2) 

in place difference / subtraction 

intersection (triples in both graphs) 

xor (triples in either G1 or G2, but not in both) 
Warning
Setoperations on graphs assume Blank Nodes are shared between graphs. This may or may not be what you want. See Merging graphs for details.
Basic Triple Matching¶
Instead of iterating through all triples, RDFLib graphs support basic triple pattern matching with a
triples()
function. This function is a generator of triples that match a pattern given by
arguments, i.e. arguments restrict the triples that are returned. Terms that are None
are treated as a wildcard.
For example:
g.load("some_foaf.ttl")
# find all subjects (s) of type (rdf:type) person (foaf:Person)
for s, p, o in g.triples((None, RDF.type, FOAF.Person)):
print(f"{s} is a person")
# find all subjects of any type
for s, p, o in g.triples((None, RDF.type, None)):
print(f"{s} is a {o}")
# create a graph
bobgraph = Graph()
# add all triples with subject 'bob'
bobgraph += g.triples((bob, None, None))
If you are not interested in whole triples, you can get only the bits you want with the methods
objects()
, subjects()
, predicates()
,
predicate_objects()
, etc. Each take parameters for the components of the triple to constraint:
for person in g.subjects(RDF.type, FOAF.Person):
print("{} is a person".format(person))
Finally, for some properties, only one value per resource makes sense (i.e they are functional properties, or have a
maxcardinality of 1). The value()
method is useful for this, as it returns just a single
node, not a generator:
# get any name of bob
name = g.value(bob, FOAF.name)
# get the one person that knows bob and raise an exception if more are found
mbox = g.value(predicate = FOAF.name, object=bob, any=False)
Graph
methods for accessing triples¶
Here is a list of all convenience methods for querying Graphs:
 Graph.triples(triple)[source]
Generator over the triple store
Returns triples that match the given triple pattern. If triple pattern does not provide a context, all contexts will be searched.
 Graph.value(subject=None, predicate=rdflib.term.URIRef('http://www.w3.org/1999/02/22rdfsyntaxns#value'), object=None, default=None, any=True)[source]
Get a value for a pair of two criteria
Exactly one of subject, predicate, object must be None. Useful if one knows that there may only be one value.
It is one of those situations that occur a lot, hence this ‘macro’ like utility
Parameters: subject, predicate, object – exactly one must be None default – value to be returned if no values found any – if True, return any value in the case there is more than one, else, raise UniquenessError
 Graph.subjects(predicate=None, object=None)[source]
A generator of subjects with the given predicate and object
 Graph.objects(subject=None, predicate=None)[source]
A generator of objects with the given subject and predicate
 Graph.predicates(subject=None, object=None)[source]
A generator of predicates with the given subject and object
 Graph.subject_objects(predicate=None)[source]
A generator of (subject, object) tuples for the given predicate
 Graph.subject_predicates(object=None)[source]
A generator of (subject, predicate) tuples for the given object
 Graph.predicate_objects(subject=None)[source]
A generator of (predicate, object) tuples for the given subject