# http://www.w3.org/2000/10/swap/Primer
 
# This is a simple primer using some of the 
# example stuff in the above Primer on N3
# get RDFLib at http://rdflib.net/ 
 
 
# Load up RDFLib
 
from rdflib import *
from rdflib.graph import ConjunctiveGraph
from rdflib.namespace import Namespace
from rdflib.term import URIRef
from rdflib.parser import StringInputSource
 
# Firstly, it doesn't have to be so complex.
# Here we create a "Graph" of our work.
# Think of it as a blank piece of graph paper!
 
primer = ConjunctiveGraph()
myNS = Namespace('#')
 
primer.add((myNS.pat, myNS.knows, myNS.jo))
# or:
primer.add((myNS['pat'], myNS['age'], long(24)))
 
 
# Now, with just that, lets see how the system
# recorded *way* too many details about what
# you just asserted as fact.
#
 
from pprint import pprint
pprint(list(primer))
 
 
# just think .whatever((s, p, o))
# here we report on what we know
 
pprint(list(primer.subjects()))
pprint(list(primer.predicates()))
pprint(list(primer.objects()))
 
# and other things that make sense
 
# what do we know about pat?
pprint(list(primer.predicate_objects(myNS.pat)))
 
# who is what age?
pprint(list(primer.subject_objects(myNS.age)))
 
 
 
# Okay, so lets now work with a bigger
# dataset from the example, and start
# with a fresh new graph.
 
 
primer = ConjunctiveGraph()
 
 
# Lets start with a verbatim string straight from the primer text:
 
mySource = """
 
 
@prefix : <http://www.w3.org/2000/10/swap/Primer#>.
@prefix rdf:  <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix owl:  <http://www.w3.org/2002/07/owl#> .
@prefix dc:  <http://purl.org/dc/elements/1.1/> .
@prefix foo: <http://www.w3.org/2000/10/swap/Primer#>.
@prefix swap: <http://www.w3.org/2000/10/swap/>.
 
<> dc:title
  "Primer - Getting into the Semantic Web and RDF using N3".
 
<#pat> <#knows> <#jo> .
<#pat> <#age> 24 .
<#al> is <#child> of <#pat> .
 
<#pat> <#child>  <#al>, <#chaz>, <#mo> ;
       <#age>    24 ;
       <#eyecolor> "blue" .
 
 
:Person a rdfs:Class.
 
:Pat a :Person.
 
:Woman a rdfs:Class; rdfs:subClassOf :Person .
 
:sister a rdf:Property.
 
:sister rdfs:domain :Person; 
        rdfs:range :Woman.
 
:Woman = foo:FemaleAdult .
:Title a rdf:Property; = dc:title .
 
 
 
""" # --- End of primer code
 
# To make this go easier to spit back out... 
# technically, we already created a namespace
# with the object init (and it added some namespaces as well)
# By default, your main namespace is the URI of your 
# current working directory, so lets make that simpler:
 
myNS = Namespace(URIRef('http://www.w3.org/2000/10/swap/Primer#'))
primer.bind('', myNS)
primer.bind('owl', 'http://www.w3.org/2002/07/owl#')
primer.bind('dc', 'http://purl.org/dc/elements/1.1/')
primer.bind('swap', 'http://www.w3.org/2000/10/swap/')
sourceCode = StringInputSource(mySource, myNS)
 
# Lets load it up!
 
primer.parse(sourceCode, format='n3')
 
 
# Now you can query, either directly straight into a list:
 
[(x, y, z) for x, y, z in primer]
 
# or spit it back out (mostly) the way we created it:
 
print primer.serialize(format='n3')
 
# for more insight into things already done, lets see the namespaces
 
list(primer.namespaces())
 
# lets ask something about the data
 
list(primer.objects(myNS.pat, myNS.child))