def test_dataflow_primitive_assignment(graph: DataflowGraph) -> None:
x: AssignableNodeReference = get_dataflow_node(graph, "x")
statement: Statement = Statement()
x.assign(ValueNode(42).reference(), statement, graph)
assert isinstance(x, DirectNodeReference)
assert len(x.node.value_assignments) == 1
assignment: Assignment[ValueNodeReference] = x.node.value_assignments[0]
assert assignment.lhs == x.node
assert assignment.rhs.node == ValueNode(42)
assert assignment.responsible == statement
assert assignment.context == graph
def _consume_token_rhs_element(
self) -> Tuple[Optional[NodeReference], Optional[str]]:
instance_id: Optional[str] = self._consume_token_instance()
if instance_id is not None:
if self._consume_token_attribute() is not None:
raise Exception(
"Syntax error: this simple language only supports attributes directly on instances in the lhs."
)
if instance_id not in self._instances:
return (None, instance_id)
return (self._instances[instance_id].reference(), None)
else:
token: str = self._tokens.pop(0)
if not token.isalnum():
raise Exception(
"Invalid syntax: expected `variable_name [. attr [...]]` or `<instance> instance_id`, got `%s`"
% token)
try:
return (ValueNode(int(token)).reference(), None)
except ValueError:
node_ref: AssignableNodeReference = get_dataflow_node(
self.get_graph(), token)
assert isinstance(node_ref, VariableNodeReference)
attribute_name: Optional[str] = self._consume_token_attribute()
while attribute_name is not None:
node_ref = AttributeNodeReference(node_ref, attribute_name)
attribute_name = self._consume_token_attribute()
return (node_ref, None)
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_tentative_attribute_propagation(
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)
x_a_n: AssignableNodeReference = get_dataflow_node(graph, "x.a.n")
x_a_n.assign(ValueNode(42).reference(), Statement(), graph)
def assert_tentative_a_n(var: AssignableNode,
values: Optional[Set[int]] = None) -> None:
if values is None:
values = {42}
instance: Optional[InstanceNode] = var.equivalence.tentative_instance
assert instance is not None
a: Optional[AttributeNode] = instance.get_attribute("a")
assert a is not None
instance2: Optional[InstanceNode] = a.equivalence.tentative_instance
assert instance2 is not None
n: Optional[AttributeNode] = instance2.get_attribute("n")
assert n is not None
assert len(n.value_assignments) == len(values)
assert {
assignment.rhs.node.value
for assignment in n.value_assignments
} == values
assert isinstance(z, VariableNodeReference)
assert_tentative_a_n(z.node)
u: AssignableNodeReference = get_dataflow_node(graph, "u")
v: AssignableNodeReference = get_dataflow_node(graph, "v")
u.assign(v, Statement(), graph)
z.assign(u, Statement(), graph)
assert isinstance(z, VariableNodeReference)
assert z.node.equivalence.tentative_instance is None
assert isinstance(v, VariableNodeReference)
assert_tentative_a_n(v.node)
x_a_n.assign(ValueNode(0).reference(), Statement(), graph)
assert_tentative_a_n(v.node, {0, 42})
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_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_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_dataflow_variable_loop_with_value_assignment_leaves(
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)
y.assign(ValueNode(42).reference(), Statement(), graph)
leaves: Set[AssignableNode] = set(x.leaf_nodes())
assert isinstance(x, DirectNodeReference)
assert isinstance(y, DirectNodeReference)
assert isinstance(z, DirectNodeReference)
assert leaves == {y.node}
def test_dataflow_tentative_attribute_propagation_over_uninitialized_attribute(
graph: DataflowGraph) -> None:
x_y: AssignableNodeReference = get_dataflow_node(graph, "x.y")
u_n: AssignableNodeReference = get_dataflow_node(graph, "u.n")
y: AssignableNodeReference = get_dataflow_node(graph, "y")
u: AssignableNodeReference = get_dataflow_node(graph, "u")
u_n.assign(ValueNode(42).reference(), Statement(), graph)
x_y.assign(y, Statement(), graph)
u.assign(x_y, Statement(), graph)
assert isinstance(y, VariableNodeReference)
instance: Optional[InstanceNode] = y.node.equivalence.tentative_instance
assert instance is not None
n: Optional[AttributeNode] = instance.get_attribute("n")
assert n is not None
assert len(n.value_assignments) == 1
assert n.value_assignments[0].rhs.node.value == 42
def test_dataflow_model_primitive_double_assignment_responsible(
dataflow_test_helper: DataflowTestHelper) -> None:
dataflow_test_helper.compile(
"""
x = 42
x = 0
""",
DoubleSetException,
)
graph: DataflowGraph = dataflow_test_helper.get_graph()
x: AssignableNodeReference = get_dataflow_node(graph, "x")
assert isinstance(x, VariableNodeReference)
assignments: List[Assignment] = x.node.value_assignments
assert len(assignments) == 2
zero_index: int = [assignment.rhs for assignment in assignments
].index(ValueNode(0).reference())
for i, assignment in enumerate(assignments):
value: int = 0 if i == zero_index else 42
assert assignment.context == graph
assert isinstance(assignment.responsible, Assign)
assert assignment.responsible.name == "x"
assert isinstance(assignment.responsible.value, Literal)
assert assignment.responsible.value.value == value
def test_slots_dataflow():
namespace: Namespace = Namespace("root", None)
resolver: Resolver = Resolver(namespace)
graph: DataflowGraph = DataflowGraph(resolver)
assignable_node: AssignableNode = AssignableNode("node")
value_node: ValueNode = ValueNode(42)
instance_node: InstanceNode = InstanceNode([])
assert_slotted(graph)
assert_slotted(assignable_node)
assert_slotted(assignable_node.equivalence)
assert_slotted(value_node)
assert_slotted(instance_node)
assert_slotted(AttributeNodeReference(assignable_node.reference(), "attr"))
assert_slotted(VariableNodeReference(assignable_node))
assert_slotted(ValueNodeReference(value_node))
assert_slotted(InstanceNodeReference(instance_node))
assert_slotted(
Assignment(assignable_node.reference(), value_node, Statement(),
graph))
assert_slotted(NodeStub("stub"))
assert_slotted(AttributeNode(instance_node, "attr"))
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}
Node,
NodeReference,
ValueNode,
)
def entity_instance(entity: str) -> InstanceNode:
node: InstanceNode = InstanceNode([])
node.entity = Entity(entity, Namespace("__config__", Namespace("__root_ns__")))
return node
@pytest.mark.parametrize(
"instance,expected_repr",
[
(ValueNode(42), "42"),
(ValueNode("42"), "'42'"),
(ValueNode(42).reference(), "42"),
(ValueNode("Hello World!"), repr("Hello World!")),
(AssignableNode("x"), "x"),
(AssignableNode("x").reference(), "x"),
(AttributeNodeReference(AttributeNodeReference(AssignableNode("x").reference(), "y"), "z"), "x.y.z"),
(entity_instance("MyEntity"), "__config__::MyEntity instance"),
(entity_instance("MyEntity").reference(), "__config__::MyEntity instance"),
(AttributeNode(entity_instance("MyEntity"), "n"), "attribute n on __config__::MyEntity instance"),
],
)
def test_dataflow_repr(instance: Union[Node, NodeReference], expected_repr: str) -> None:
assert repr(instance) == expected_repr
assert str(instance) == expected_repr