def convert( self ) : """ Top level entry to convert and generate all the triples. It finds the top level items, and generates triples for each of them; additionally, it generates a top level entry point to the items from base in the form of an RDF list. """ item_list = [] for top_level_item in self.get_top_level_items() : item_list.append( self.generate_triples(top_level_item, Evaluation_Context()) ) list = generate_RDF_collection( self.graph, item_list ) self.graph.add( (URIRef(self.base),self.ns_md["item"],list) ) # If the vocab expansion is also switched on, this is the time to do it. # This is the version with my current proposal: the basic expansion is always there; # the follow-your-nose inclusion of vocabulary is optional if self.vocabularies_used : try : try : from ..pyRdfa.rdfs.process import MiniOWL, process_rdfa_sem from ..pyRdfa.options import Options except : from pyRdfa.rdfs.process import MiniOWL, process_rdfa_sem from pyRdfa.options import Options # if we did not get here, the pyRdfa package could not be # imported. Too bad, but life should go on in the except branch... if self.vocab_expansion : # This is the full deal options = Options(vocab_expansion = self.vocab_expansion, vocab_cache = self.vocab_cache) process_rdfa_sem(self.graph, options) else : MiniOWL(self.graph).closure() except : pass
def convert( self ) : """ Top level entry to convert and generate all the triples. It finds the top level items, and generates triples for each of them; additionally, it generates a top level entry point to the items from base in the form of an RDF list. """ item_list = [] for top_level_item in self.get_top_level_items() : item_list.append( self.generate_triples(top_level_item, Evaluation_Context()) ) #list = generate_RDF_collection( self.graph, item_list ) #self.graph.add( (URIRef(self.base),self.ns_md["item"],list) ) # If the vocab expansion is also switched on, this is the time to do it. # This is the version with my current proposal: the basic expansion is always there; # the follow-your-nose inclusion of vocabulary is optional if self.vocabularies_used : try : try : from ..pyRdfa.rdfs.process import MiniOWL, process_rdfa_sem from ..pyRdfa.options import Options except : from pyRdfa.rdfs.process import MiniOWL, process_rdfa_sem from pyRdfa.options import Options # if we did not get here, the pyRdfa package could not be # imported. Too bad, but life should go on in the except branch... if self.vocab_expansion : # This is the full deal options = Options(vocab_expansion = self.vocab_expansion, vocab_cache = self.vocab_cache) process_rdfa_sem(self.graph, options) else : MiniOWL(self.graph).closure() except : pass
def graph_from_DOM(self, dom, graph = None, pgraph = None) :
"""
Extract the RDF Graph from a DOM tree. This is where the real processing happens. All other methods get down to this
one, eventually (e.g., after opening a URI and parsing it into a DOM).
@param dom: a DOM Node element, the top level entry node for the whole tree (i.e., the C{dom.documentElement} is used to initiate processing down the node hierarchy)
@keyword graph: an RDF Graph (if None, than a new one is created)
@type graph: rdflib Graph instance.
@keyword pgraph: an RDF Graph to hold (possibly) the processor graph content. If None, and the error/warning triples are to be generated, they will be added to the returned graph. Otherwise they are stored in this graph.
@type pgraph: rdflib Graph instance
@return: an RDF Graph
@rtype: rdflib Graph instance
"""
def copyGraph(tog, fromg) :
for t in fromg :
tog.add(t)
for k,ns in fromg.namespaces() :
tog.bind(k,ns)
if graph == None :
# Create the RDF Graph, that will contain the return triples...
graph = Graph()
# this will collect the content, the 'default graph', as called in the RDFa spec
default_graph = Graph()
# get the DOM tree
topElement = dom.documentElement
# Create the initial state. This takes care of things
# like base, top level namespace settings, etc.
state = ExecutionContext(topElement, default_graph, base=self.base, options=self.options, rdfa_version=self.rdfa_version)
# Perform the built-in and external transformations on the HTML tree.
for trans in self.options.transformers + builtInTransformers :
trans(topElement, self.options, state)
# This may have changed if the state setting detected an explicit version information:
self.rdfa_version = state.rdfa_version
# The top level subject starts with the current document; this
# is used by the recursion
# this function is the real workhorse
parse_one_node(topElement, default_graph, None, state, [])
# If the RDFS expansion has to be made, here is the place...
if self.options.vocab_expansion :
from pyRdfa.rdfs.process import process_rdfa_sem
process_rdfa_sem(default_graph, self.options)
# What should be returned depends on the way the options have been set up
if self.options.output_default_graph :
copyGraph(graph, default_graph)
if self.options.output_processor_graph :
if pgraph != None :
copyGraph(pgraph, self.options.processor_graph.graph)
else :
copyGraph(graph, self.options.processor_graph.graph)
elif self.options.output_processor_graph :
if pgraph != None :
copyGraph(pgraph, self.options.processor_graph.graph)
else :
copyGraph(graph, self.options.processor_graph.graph)
# this is necessary if several DOM trees are handled in a row...
self.options.reset_processor_graph()
return graph
