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_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_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
