Getting started with RDFLib

Installation

RDFLib is open source and is maintained in a GitHub repository. RDFLib releases, current and previous are listed on PyPi

The best way to install RDFLib is to use pip (sudo as required):

$ pip install rdflib

If you want the latest code to run, clone the master branch of the GitHub repo and use that.

Support

Usage support is available via questions tagged with [rdflib] on StackOverflow and development support, notifications and detailed discussion through the rdflib-dev group (mailing list):

http://groups.google.com/group/rdflib-dev

If you notice an bug or want to request an enhancement, please do so via our Issue Tracker in Github:

http://github.com/RDFLib/rdflib/issues

How it all works

The package uses various Python idioms that offer an appropriate way to introduce RDF to a Python programmer who hasn’t worked with RDF before.

The primary interface that RDFLib exposes for working with RDF is a Graph.

RDFLib graphs are not sorted containers; they have ordinary set operations (e.g. add() to add a triple) plus methods that search triples and return them in arbitrary order.

RDFLib graphs also redefine certain built-in Python methods in order to behave in a predictable way; they emulate container types and are best thought of as a set of 3-item tuples (“triples”, in RDF-speak):

[
    (subject0, predicate0, object0),
    (subject1, predicate1, object1),
    ...
    (subjectN, predicateN, objectN)
 ]

A tiny usage example:

import rdflib

# create a Graph
g = rdflib.Graph()

# parse in an RDF file hosted on the Internet
result = g.parse("http://www.w3.org/People/Berners-Lee/card")

# loop through each triple in the graph (subj, pred, obj)
for subj, pred, obj in g:
    # check if there is at least one triple in the Graph
    if (subj, pred, obj) not in g:
       raise Exception("It better be!")

# print the number of "triples" in the Graph
print("graph has {} statements.".format(len(g)))
# prints graph has 86 statements.

# print out the entire Graph in the RDF Turtle format
print(g.serialize(format="turtle").decode("utf-8"))

Here a Graph is created and then an RDF file online, Tim Berners-Lee’s social network details, is parsed into that graph. The print() statement uses the len() function to count the number of triples in the graph.

A more extensive example:

from rdflib import Graph, Literal, RDF, URIRef
# rdflib knows about some namespaces, like FOAF
from rdflib.namespace import FOAF , XSD

# create a Graph
g = Graph()

# Create an RDF URI node to use as the subject for multiple triples
donna = URIRef("http://example.org/donna")

# Add triples using store's add() method.
g.add((donna, RDF.type, FOAF.Person))
g.add((donna, FOAF.nick, Literal("donna", lang="ed")))
g.add((donna, FOAF.name, Literal("Donna Fales")))
g.add((donna, FOAF.mbox, URIRef("mailto:donna@example.org")))

# Add another person
ed = URIRef("http://example.org/edward")

# Add triples using store's add() method.
g.add((ed, RDF.type, FOAF.Person))
g.add((ed, FOAF.nick, Literal("ed", datatype=XSD.string)))
g.add((ed, FOAF.name, Literal("Edward Scissorhands")))
g.add((ed, FOAF.mbox, URIRef("mailto:e.scissorhands@example.org")))

# Iterate over triples in store and print them out.
print("--- printing raw triples ---")
for s, p, o in g:
    print((s, p, o))

# For each foaf:Person in the store, print out their mbox property's value.
print("--- printing mboxes ---")
for person in g.subjects(RDF.type, FOAF.Person):
    for mbox in g.objects(person, FOAF.mbox):
        print(mbox)

# Bind the FOAF namespace to a prefix for more readable output
g.bind("foaf", FOAF)

# print all the data in the Notation3 format
print("--- printing mboxes ---")
print(g.serialize(format='n3').decode("utf-8"))

More examples

There are many more examples in the examples folder in the source distribution.