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'