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