def test_dataflow_assignment_node_attribute(graph: DataflowGraph,
instantiate: bool) -> None:
x: AssignableNodeReference = get_dataflow_node(graph, "x")
y: AssignableNodeReference = get_dataflow_node(graph, "y")
z: AssignableNodeReference = get_dataflow_node(graph, "z")
x.assign(y, Statement(), graph)
y.assign(z, Statement(), graph)
if instantiate:
y.assign(create_instance().reference(), Statement(), graph)
x_n: AssignableNodeReference = get_dataflow_node(graph, "x.n")
assignment_node: AssignableNode = x_n.assignment_node()
instance: InstanceNode
if instantiate:
assert isinstance(y, VariableNodeReference)
assert len(y.node.instance_assignments) == 1
instance = y.node.instance_assignments[0].rhs.node()
else:
assert isinstance(z, VariableNodeReference)
assert z.node.equivalence.tentative_instance is not None
instance = z.node.equivalence.tentative_instance
# verify tentative nodes only get created once
assignment_node2: AssignableNode = x_n.assignment_node()
assert assignment_node == assignment_node2
assert assignment_node == instance.get_attribute("n")
def test_dataflow_tentative_attribute_propagation_on_equivalence(
graph: DataflowGraph) -> None:
x: AssignableNodeReference = get_dataflow_node(graph, "x")
y: AssignableNodeReference = get_dataflow_node(graph, "y")
z: AssignableNodeReference = get_dataflow_node(graph, "z")
x.assign(y, Statement(), graph)
y.assign(z, Statement(), graph)
z.assign(x, Statement(), graph)
x_n: AssignableNodeReference = get_dataflow_node(graph, "x.n")
x_n.assign(ValueNode(42).reference(), Statement(), graph)
assert isinstance(y, VariableNodeReference)
assert len(y.node.instance_assignments) == 0
y.assign(create_instance().reference(), Statement(), graph)
assert len(y.node.instance_assignments) == 1
y_n: Optional[AttributeNode] = y.node.instance_assignments[0].rhs.node(
).get_attribute("n")
assert y_n is not None
assert len(y_n.value_assignments) == 1
assert y_n.value_assignments[0].rhs.node.value == 42
def test_dataflow_index(graph: DataflowGraph, reverse: bool) -> None:
entity: Entity = Entity("DummyEntity", Namespace("dummy_namespace"))
i1: InstanceNode = create_instance(graph, entity)
i2: InstanceNode = create_instance(graph, entity)
assert i1.get_self() is i1
assert i2.get_self() is i2
assert i1 is not i2
graph.add_index_match([i.reference() for i in [i1, i2]])
if reverse:
# make sure adding them again in another order does not cause issues
graph.add_index_match([i.reference() for i in [i2, i1]])
assert i1.get_self() is i1
assert i2.get_self() is i1
assert i2.reference().node() is i1
assert i2.reference().top_node() is i2
assert i1.get_all_index_nodes() == {i1, i2}
def test_dataflow_index_nodes(graph: DataflowGraph) -> None:
entity: Entity = Entity("DummyEntity", Namespace("dummy_namespace"))
i1: InstanceNode = create_instance(graph, entity)
i2: InstanceNode = create_instance(graph, entity)
i1.register_attribute("n").assign(
ValueNode(0).reference(), Statement(), graph)
i1.register_attribute("n").assign(
ValueNode(0).reference(), Statement(), graph)
x: AssignableNodeReference = get_dataflow_node(graph, "x")
y: AssignableNodeReference = get_dataflow_node(graph, "y")
x.assign(i1.reference(), Statement(), graph)
y.assign(i2.reference(), Statement(), graph)
graph.add_index_match([i.reference() for i in [i1, i2]])
x_n: AssignableNodeReference = get_dataflow_node(graph, "x.n")
y_n: AssignableNodeReference = get_dataflow_node(graph, "y.n")
assert set(x_n.nodes()) == set(y_n.nodes())
def test_dataflow_attribute_reference_nodes(graph: DataflowGraph) -> None:
x: AssignableNodeReference = get_dataflow_node(graph, "x")
y: AssignableNodeReference = get_dataflow_node(graph, "y")
x.assign(y, Statement(), graph)
y.assign(create_instance().reference(), Statement(), graph)
assert isinstance(y, VariableNodeReference)
assert len(y.node.instance_assignments) == 1
y_n: AssignableNodeReference = get_dataflow_node(graph, "y.n")
y_n.assign(ValueNode(42).reference(), Statement(), graph)
x_n: AssignableNodeReference = get_dataflow_node(graph, "x.n")
x_n_nodes: List[AssignableNode] = list(x_n.nodes())
assert len(x_n_nodes) == 1
assert x_n_nodes[0] == y.node.instance_assignments[0].rhs.node(
).get_attribute("n")
def test_attribute_assignment(graph: DataflowGraph, instantiate: bool) -> None:
x: AssignableNodeReference = get_dataflow_node(graph, "x")
x_n: AssignableNodeReference = get_dataflow_node(graph, "x.n")
if instantiate:
x.assign(create_instance().reference(), Statement(), graph)
x_n.assign(ValueNode(42).reference(), Statement(), graph)
assert isinstance(x, VariableNodeReference)
instance: InstanceNode
if instantiate:
assert x.node.equivalence.tentative_instance is None
assert len(x.node.instance_assignments) == 1
instance = x.node.instance_assignments[0].rhs.node()
else:
assert x.node.equivalence.tentative_instance is not None
instance = x.node.equivalence.tentative_instance
n: Optional[AttributeNode] = instance.get_attribute("n")
assert n is not None
assert len(n.value_assignments) == 1
assert n.value_assignments[0].rhs == ValueNode(42).reference()
def test_dataflow_variable_chain_leaf(graph: DataflowGraph) -> None:
x: AssignableNodeReference = get_dataflow_node(graph, "x")
y: AssignableNodeReference = get_dataflow_node(graph, "y")
z: AssignableNodeReference = get_dataflow_node(graph, "z")
x.assign(y, Statement(), graph)
y.assign(z, Statement(), graph)
leaves: Set[AssignableNode] = set(x.leaf_nodes())
assert isinstance(z, DirectNodeReference)
assert leaves == {z.node}
@pytest.mark.parametrize("value_node", [ValueNode(42), create_instance()])
def test_dataflow_variable_tree_leaves(graph: DataflowGraph,
value_node: Node) -> None:
x: AssignableNodeReference = get_dataflow_node(graph, "x")
y: AssignableNodeReference = get_dataflow_node(graph, "y")
z: AssignableNodeReference = get_dataflow_node(graph, "z")
x.assign(y, Statement(), graph)
y.assign(z, Statement(), graph)
y.assign(value_node.reference(), Statement(), graph)
leaves: Set[AssignableNode] = set(x.leaf_nodes())
assert isinstance(y, DirectNodeReference)
assert isinstance(z, DirectNodeReference)
assert leaves == {y.node, z.node}