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_new_require_evaluation():
pg = PortGraph()
pg.add_vertex(0)
algo = BruteEvaluation(pg)
assert id(algo.portgraph()) == id(pg)
env = EvaluationEnvironment()
ws = WorkflowState(pg)
assert algo.requires_evaluation(env, ws)
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_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_fail_if_port_mismatch_outputs():
def func():
return 1, 2
pg = PortGraph()
pg.add_vertex(0)
pg.add_out_port(0, 'res', 0)
n = RawFuncNode(func)
n.add_output('res', "descr")
pg.set_actor(0, n)
algo = BruteEvaluation(pg)
env = EvaluationEnvironment()
ws = WorkflowState(pg)
assert_raises(EvaluationError, lambda: algo.eval(env, 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_evaluation_affect_output_to_right_ports():
def func(a, b):
c = a + b
d = a * 2
return c, d
# simple order
pg = PortGraph()
n = FuncNode(func)
pg.add_vertex(0)
pg.add_in_port(0, 'a', 0)
pg.add_in_port(0, 'b', 1)
pg.add_out_port(0, 'c', 2)
pg.add_out_port(0, 'd', 3)
pg.set_actor(0, n)
algo = BruteEvaluation(pg)
env = EvaluationEnvironment()
ws = WorkflowState(pg)
ws.store_param(0, 'a', 0)
ws.store_param(1, 'b', 0)
algo.eval(env, ws)
assert ws.get(2) == 'ab'
assert ws.get(3) == 'aa'
# reverse input orders
pg = PortGraph()
n = FuncNode(func)
pg.add_vertex(0)
pg.add_in_port(0, 'b', 0)
pg.add_in_port(0, 'a', 1)
pg.add_out_port(0, 'c', 2)
pg.add_out_port(0, 'd', 3)
pg.set_actor(0, n)
algo = BruteEvaluation(pg)
env = EvaluationEnvironment()
ws = WorkflowState(pg)
ws.store_param(0, 'a', 0)
ws.store_param(1, 'b', 0)
algo.eval(env, ws)
assert ws.get(2) == 'ba'
assert ws.get(3) == 'bb'
# reverse output order
pg = PortGraph()
n = FuncNode(func)
pg.add_vertex(0)
pg.add_in_port(0, 'a', 0)
pg.add_in_port(0, 'b', 1)
pg.add_out_port(0, 'd', 2)
pg.add_out_port(0, 'c', 3)
pg.set_actor(0, n)
algo = BruteEvaluation(pg)
env = EvaluationEnvironment()
ws = WorkflowState(pg)
ws.store_param(0, 'a', 0)
ws.store_param(1, 'b', 0)
algo.eval(env, ws)
assert ws.get(3) == 'ab'
assert ws.get(2) == 'aa'
