def _evaluate_not_constraint(not_c):
nonlocal self, shape, target_graph, focus_value_nodes, _evaluation_path
_reports = []
_non_conformant = False
not_shape = shape.get_other_shape(not_c)
if not not_shape:
raise ReportableRuntimeError(
"Shape pointed to by sh:not does not exist or is not " "a well-formed SHACL Shape."
)
if not_shape in potentially_recursive:
warn(ShapeRecursionWarning(_evaluation_path))
return _non_conformant, _reports
for f, value_nodes in focus_value_nodes.items():
for v in value_nodes:
try:
_is_conform, _r = not_shape.validate(
target_graph, focus=v, _evaluation_path=_evaluation_path[:]
)
except ValidationFailure as e:
raise e
if _is_conform:
# in this case, we _dont_ want to conform!
_non_conformant = True
rept = self.make_v_result(target_graph, f, value_node=v)
_reports.append(rept)
return _non_conformant, _reports
def _evaluate_node_shape(node_shape):
nonlocal self, target_graph, shape, focus_value_nodes, _evaluation_path
_reports = []
_non_conformant = False
node_shape = shape.get_other_shape(node_shape)
if node_shape in potentially_recursive:
warn(ShapeRecursionWarning(_evaluation_path))
return _non_conformant, _reports
if not node_shape or node_shape.is_property_shape:
raise ReportableRuntimeError(
"Shape pointed to by sh:node does not exist or "
"is not a well-formed SHACL NodeShape.")
for f, value_nodes in focus_value_nodes.items():
for v in value_nodes:
_is_conform, _r = node_shape.validate(
target_graph,
focus=v,
_evaluation_path=_evaluation_path[:])
# ignore the fails from the node, create our own fail
if (not _is_conform) or len(_r) > 0:
_non_conformant = True
rept = self.make_v_result(target_graph,
f,
value_node=v)
_reports.append(rept)
return _non_conformant, _reports
def _evaluate_not_constraint(self, not_c, datagraph, focus_value_nodes,
potentially_recursive, _evaluation_path):
"""
:type not_c: List[Node]
:type datagraph: rdflib.Graph
:type focus_value_nodes: dict
:type potentially_recursive: List
:type _evaluation_path: List
"""
_reports = []
_non_conformant = False
not_shape = self.shape.get_other_shape(not_c)
if not not_shape:
raise ReportableRuntimeError(
"Shape pointed to by sh:not does not exist or is not a well-formed SHACL Shape."
)
if not_shape in potentially_recursive:
warn(ShapeRecursionWarning(_evaluation_path))
return _non_conformant, _reports
for f, value_nodes in focus_value_nodes.items():
for v in value_nodes:
try:
_is_conform, _r = not_shape.validate(
datagraph,
focus=v,
_evaluation_path=_evaluation_path[:])
except ValidationFailure as e:
raise e
if _is_conform:
# in this case, we _dont_ want to conform!
_non_conformant = True
rept = self.make_v_result(datagraph, f, value_node=v)
_reports.append(rept)
return _non_conformant, _reports
def _evaluate_property_shape(prop_shape):
nonlocal shape, target_graph, focus_value_nodes, _evaluation_path
_reports = []
_non_conformant = False
prop_shape = shape.get_other_shape(prop_shape)
if prop_shape in potentially_recursive:
warn(ShapeRecursionWarning(_evaluation_path))
return _non_conformant, _reports
if not prop_shape or not prop_shape.is_property_shape:
raise ReportableRuntimeError(
"Shape pointed to by sh:property does not exist "
"or is not a well-formed SHACL PropertyShape.")
for f, value_nodes in focus_value_nodes.items():
for v in value_nodes:
_is_conform, _r = prop_shape.validate(
target_graph,
focus=v,
_evaluation_path=_evaluation_path[:])
_non_conformant = _non_conformant or (not _is_conform)
_reports.extend(_r)
return _non_conformant, _reports
def _evaluate_value_shape(_v_shape):
nonlocal self, shape, target_graph, focus_value_nodes, _evaluation_path
_reports = []
_non_conformant = False
other_shape = shape.get_other_shape(_v_shape)
if other_shape in potentially_recursive:
warn(ShapeRecursionWarning(_evaluation_path))
return _non_conformant, _reports
if not other_shape:
raise ReportableRuntimeError(
"Shape pointed to by sh:property does not "
"exist or is not a well-formed SHACL Shape.")
if self.is_disjoint:
# Textual Definition of Sibling Shapes:
# Let Q be a shape in shapes graph G that declares a qualified cardinality constraint (by having values for sh:qualifiedValueShape and at least one of sh:qualifiedMinCount or sh:qualifiedMaxCount). Let ps be the set of shapes in G that have Q as a value of sh:property. If Q has true as a value for sh:qualifiedValueShapesDisjoint then the set of sibling shapes for Q is defined as the set of all values of the SPARQL property path sh:property/sh:qualifiedValueShape for any shape in ps minus the value of sh:qualifiedValueShape of Q itself. The set of sibling shapes is empty otherwise.
sibling_shapes = set()
parent_shapes = set(
self.shape.sg.subjects(SH_property, self.shape.node))
for p in iter(parent_shapes):
found_siblings = set(self.shape.sg.objects(p, SH_property))
for s in iter(found_siblings):
if s == self.shape.node:
continue
sibling_shapes.update(
self.shape.sg.objects(s, SH_qualifiedValueShape))
sibling_shapes = set(
self.shape.get_other_shape(s) for s in sibling_shapes)
else:
sibling_shapes = set()
for f, value_nodes in focus_value_nodes.items():
number_conforms = 0
for v in value_nodes:
try:
_is_conform, _r = other_shape.validate(
target_graph,
focus=v,
_evaluation_path=_evaluation_path[:])
if _is_conform:
_conforms_to_sibling = False
for sibling_shape in sibling_shapes:
_c2, _r = sibling_shape.validate(
target_graph,
focus=v,
_evaluation_path=_evaluation_path[:])
_conforms_to_sibling = _conforms_to_sibling or _c2
if not _conforms_to_sibling:
number_conforms += 1
except ValidationFailure as v:
raise v
if self.max_count is not None and number_conforms > self.max_count:
_non_conformant = True
_r = self.make_v_result(
target_graph,
f,
constraint_component=
SH_QualifiedMaxCountConstraintComponent)
_reports.append(_r)
if self.min_count is not None and number_conforms < self.min_count:
_non_conformant = True
_r = self.make_v_result(
target_graph,
f,
constraint_component=
SH_QualifiedMinCountConstraintComponent)
_reports.append(_r)
return _non_conformant, _reports