def test_portgraph_add_actor(): pg = PortGraph() vid1 = pg.add_vertex() actor = Node() keys = {"toto", 1, "titi"} for key in keys: actor.add_input(key, "descr") actor.add_output(key, "descr") # bad actor assert_raises(AttributeError, lambda: pg.add_actor(None)) assert len(pg) == 1 assert_raises(AttributeError, lambda: pg.add_actor(None, vid1 + 1)) assert len(pg) == 1 # vertex id already used assert_raises(InvalidVertex, lambda: pg.add_actor(actor, vid1)) assert len(pg) == 1 for key in actor.inputs(): pg.add_in_port(vid1, key) for key in actor.outputs(): pg.add_out_port(vid1, key) pg.set_actor(vid1, actor) # vertex id already used assert_raises(InvalidVertex, lambda: pg.add_actor(actor, vid1)) assert len(pg) == 1 vid2 = pg.add_actor(actor) assert pg.actor(vid2) == actor assert set(actor.inputs()) == keys assert set(pg.local_id(pid) for pid in pg.in_ports(vid2)) == keys assert set(actor.outputs()) == keys assert set(pg.local_id(pid) for pid in pg.out_ports(vid2)) == keys
def test_evaluation_propagated_upstream(): visited = [] def func(txt): visited.append(txt) return txt pg = PortGraph() n = FuncNode(func) pg.add_actor(n, 0) pg.add_actor(n, 1) pg.connect(pg.out_port(0, 'txt'), pg.in_port(1, 'txt')) algo = BruteEvaluation(pg) ws = WorkflowState(pg) env = EvaluationEnvironment() ws.store_param(pg.in_port(0, 'txt'), "txt", 0) algo.eval(env, ws, 0) assert len(visited) == 1 algo.eval(env, ws, 1) assert len(visited) == 2 env.new_execution() algo.eval(env, ws, 1) assert len(visited) == 4
def test_evaluation_do_not_reevaluate_same_node(): visited = [] def func(): visited.append("yes") pg = PortGraph() n = FuncNode(func) pg.add_actor(n, 0) pg.add_actor(n, 1) env = EvaluationEnvironment() algo = BruteEvaluation(pg) ws = WorkflowState(pg) algo.eval(env, ws, 0) assert len(visited) == 1 algo.eval(env, ws, 1) assert len(visited) == 2 algo.eval(env, ws, 0) assert len(visited) == 2 env.new_execution() algo.eval(env, ws, 0) assert len(visited) == 3
def test_evaluation_needs_ready_to_evaluate_state(): def func(a, b): c = a + b return c pg = PortGraph() n = FuncNode(func) pg.add_actor(n, 0) algo = BruteEvaluation(pg) ws = WorkflowState(pg) assert_raises(EvaluationError, lambda: algo.eval(None, ws))
def test_evaluation_eval_all_nodes(): visited = [] def func(): visited.append("yes") pg = PortGraph() n = FuncNode(func) pg.add_actor(n, 0) pg.add_actor(n, 1) algo = BruteEvaluation(pg) env = EvaluationEnvironment() ws = WorkflowState(pg) algo.eval(env, ws) assert len(visited) == 2
def test_evaluation_clear(): def func(): pass pg = PortGraph() n = FuncNode(func) pg.add_actor(n, 0) pg.add_actor(n, 1) algo = BruteEvaluation(pg) env = EvaluationEnvironment() ws = WorkflowState(pg) algo.eval(env, ws) assert not algo.requires_evaluation(env, ws) ws.clear() assert algo.requires_evaluation(env, ws)
def test_lazy_evaluate_at_least_once_each_node(): evaluated = [] def func(): evaluated.append('bla') pg = PortGraph() vid = pg.add_actor(FuncNode(func)) assert pg.actor(vid).is_lazy() algo = LazyEvaluation(pg) env = EvaluationEnvironment() ws = WorkflowState(pg) algo.eval(env, ws) assert len(evaluated) == 1 algo.eval(env, ws) assert len(evaluated) == 1
def test_lazy_do_not_reevaluate_node_if_same_execution(): evaluated = [] def func(txt): evaluated.append(txt) return txt pg = PortGraph() vid = pg.add_actor(FuncNode(func)) assert pg.actor(vid).is_lazy() algo = LazyEvaluation(pg) env = EvaluationEnvironment() ws = WorkflowState(pg) ws.store_param(pg.in_port(vid, 'txt'), 'toto', env.current_execution()) algo.eval(env, ws) assert len(evaluated) == 1 algo.eval_node(env, ws, vid) assert len(evaluated) == 1
def test_lazy_always_reevaluate_non_lazy_nodes(): evaluated = [] def func(txt): evaluated.append(txt) return txt pg = PortGraph() vid = pg.add_actor(FuncNode(func)) pg.actor(vid).set_lazy(False) algo = LazyEvaluation(pg) env = EvaluationEnvironment() ws = WorkflowState(pg) ws.store_param(pg.in_port(vid, 'txt'), 'toto', env.current_execution()) algo.eval(env, ws) assert len(evaluated) == 1 env.new_execution() algo.eval(env, ws) assert len(evaluated) == 2