def __init__(self,
data_graph,
*args,
shacl_graph=None,
ont_graph=None,
options=None,
**kwargs):
options = options or {}
self._load_default_options(options)
self.options = options
self.logger = options['logger']
self.pre_inferenced = kwargs.pop('pre_inferenced', False)
assert isinstance(data_graph, rdflib.Graph),\
"data_graph must be a rdflib Graph object"
self.data_graph = data_graph
self._target_graph = None
self.ont_graph = ont_graph
self.data_graph_is_multigraph = isinstance(
self.data_graph, (rdflib.Dataset, rdflib.ConjunctiveGraph))
if self.ont_graph is not None and \
isinstance(self.ont_graph, (rdflib.Dataset, rdflib.ConjunctiveGraph)):
self.ont_graph.default_union = True
if shacl_graph is None:
shacl_graph = clone_graph(data_graph, identifier='shacl')
assert isinstance(shacl_graph, rdflib.Graph),\
"shacl_graph must be a rdflib Graph object"
self.shacl_graph = ShapesGraph(shacl_graph, self.logger)
def __init__(
self,
data_graph: GraphLike,
*args,
shacl_graph: Optional[GraphLike] = None,
ont_graph: Optional[GraphLike] = None,
options: Optional[dict] = None,
**kwargs,
):
options = options or {}
self._load_default_options(options)
self.options = options # type: dict
self.logger = options['logger'] # type: logging.Logger
self.pre_inferenced = kwargs.pop('pre_inferenced', False)
if not isinstance(data_graph, rdflib.Graph):
raise RuntimeError("data_graph must be a rdflib Graph object")
self.data_graph = data_graph
self._target_graph = None
self.ont_graph = ont_graph
self.data_graph_is_multigraph = isinstance(
self.data_graph, (rdflib.Dataset, rdflib.ConjunctiveGraph))
if self.ont_graph is not None and isinstance(
self.ont_graph, (rdflib.Dataset, rdflib.ConjunctiveGraph)):
self.ont_graph.default_union = True
if shacl_graph is None:
shacl_graph = clone_graph(data_graph, identifier='shacl')
assert isinstance(
shacl_graph,
rdflib.Graph), "shacl_graph must be a rdflib Graph object"
self.shacl_graph = ShapesGraph(shacl_graph, self.logger)
def __init__(self, data_graph, *args, shacl_graph=None,
ont_graph=None, options=None, **kwargs):
options = options or {}
self._load_default_options(options)
self.options = options
self.logger = options['logger']
self.pre_inferenced = kwargs.pop('pre_inferenced', False)
assert isinstance(data_graph, rdflib.Graph),\
"data_graph must be a rdflib Graph object"
self.data_graph = data_graph
self._target_graph = self.data_graph
self.ont_graph = ont_graph
if shacl_graph is None:
shacl_graph = clone_graph(data_graph, identifier='shacl')
assert isinstance(shacl_graph, rdflib.Graph),\
"shacl_graph must be a rdflib Graph object"
self.shacl_graph = SHACLGraph(shacl_graph, self.logger)
def apply(self, data_graph):
focus_nodes = self.shape.focus_nodes(
data_graph) # uses target nodes to find focus nodes
applicable_nodes = self.filter_conditions(focus_nodes, data_graph)
construct_graphs = set()
for a in applicable_nodes:
for c in self._constructs:
init_bindings = {}
found_this = SPARQLQueryHelper.bind_this_regex.search(c)
if found_this:
init_bindings['this'] = a
c = self._qh.apply_prefixes(c)
results = data_graph.query(c, initBindings=init_bindings)
if results.type != "CONSTRUCT":
raise ReportableRuntimeError(
"Query executed by a SHACL SPARQLRule must be CONSTRUCT query."
)
construct_graphs.add(results.graph)
for g in construct_graphs:
data_graph = clone_graph(g, target_graph=data_graph)
def apply(self, data_graph: 'GraphLike') -> int:
focus_nodes = self.shape.focus_nodes(data_graph) # uses target nodes to find focus nodes
all_added = 0
SPARQLQueryHelper = get_query_helper_cls()
iterate_limit = 100
while True:
if iterate_limit < 1:
raise ReportableRuntimeError("Local rule iteration exceeded iteration limit of 100.")
iterate_limit -= 1
added = 0
applicable_nodes = self.filter_conditions(focus_nodes, data_graph)
construct_graphs = set()
for a in applicable_nodes:
for c in self._constructs:
init_bindings = {}
found_this = SPARQLQueryHelper.bind_this_regex.search(c)
if found_this:
init_bindings['this'] = a
c = self._qh.apply_prefixes(c)
results = data_graph.query(c, initBindings=init_bindings)
if results.type != "CONSTRUCT":
raise ReportableRuntimeError("Query executed by a SHACL SPARQLRule must be CONSTRUCT query.")
this_added = False
for i in results.graph:
if not this_added and i not in data_graph:
this_added = True
# We only need to know at least one triple was added, then break!
break
if this_added:
added += 1
construct_graphs.add(results.graph)
if added > 0:
for g in construct_graphs:
data_graph = clone_graph(g, target_graph=data_graph)
all_added += added
if self.iterate:
continue # Jump up to iterate
else:
break # Don't iterate
break # We've reached a local steady state
return all_added