chore: rename raises in raise_on_failure

Signed-off-by: Guilhem Barthes <guilhem.barthes@owkin.com>

tests/test_data_samples_order.py

@@ -208,7 +208,7 @@ def test_task_data_samples_relative_order(factory, client, dataset, worker):
         i.asset_key for i in traintask.inputs if i.identifier == InputIdentifiers.datasamples
     ] == dataset.train_data_sample_keys
     # `raises = True`, will fail if task not successful
-    client.wait_task(traintask.key, raises=True)
+    client.wait_task(traintask.key, raise_on_failure=True)
 
     predict_input_models = FLTaskInputGenerator.train_to_predict(traintask.key)
     predicttask_spec = factory.create_predicttask(
@@ -225,7 +225,7 @@ def test_task_data_samples_relative_order(factory, client, dataset, worker):
 
     # Assert order is correct in the metric. If not, wait_task() will fail.
     # `raises = True`, will fail if task not successful
-    client.wait_task(testtask.key, raises=True)
+    client.wait_task(testtask.key, raise_on_failure=True)
 
 
 def test_composite_traintask_data_samples_relative_order(factory, client, dataset, worker):
@@ -265,7 +265,7 @@ def test_composite_traintask_data_samples_relative_order(factory, client, datase
         i.asset_key for i in composite_traintask.inputs if i.identifier == InputIdentifiers.datasamples
     ] == dataset.train_data_sample_keys
     # `raises = True`, will fail if task not successful
-    client.wait_task(composite_traintask.key, raises=True)
+    client.wait_task(composite_traintask.key, raise_on_failure=True)
 
     predict_input_models = FLTaskInputGenerator.composite_to_predict(composite_traintask.key)
 
@@ -283,7 +283,7 @@ def test_composite_traintask_data_samples_relative_order(factory, client, datase
 
     # Assert order is correct in the metric. If not, _wait() will fail.
     # `raises = True`, will fail if task not successful
-    client.wait_task(testtask.key, raises=True)
+    client.wait_task(testtask.key, raise_on_failure=True)
 
 
 @pytest.mark.slow
@@ -357,4 +357,4 @@ def save_predictions(predictions, path):
     traintask = client.add_task(spec)
 
     # `raises = True`, will fail if task not successful
-    client.wait_task(traintask.key, raises=True)
+    client.wait_task(traintask.key, raise_on_failure=True)

tests/test_docker_image_build.py

@@ -32,4 +32,4 @@ def test_base_substra_tools_image(factory, cfg, client, default_dataset, worker)
     )
     traintask = client.add_task(spec)
     # `raises = True`, will fail if task not successful
-    client.wait_task(traintask.key, raises=True)
+    client.wait_task(traintask.key, raise_on_failure=True)

tests/test_execution.py

@@ -38,7 +38,7 @@ def get_traintask_spec() -> TaskSpec:
 
     spec = get_traintask_spec()
     traintask = client.add_task(spec)
-    traintask = client.wait_task(traintask.key, raises=True)
+    traintask = client.wait_task(traintask.key, raise_on_failure=True)
     assert traintask.error_type is None
     assert traintask.metadata == {"foo": "bar"}
     assert len(traintask.outputs) == 1
@@ -62,7 +62,7 @@ def get_traintask_spec() -> TaskSpec:
 
     predicttask = client.add_task(spec)
     # `raises = True`, will fail if task not successful
-    predicttask = client.wait_task(predicttask.key, raises=True)
+    predicttask = client.wait_task(predicttask.key, raise_on_failure=True)
     assert predicttask.error_type is None
 
     spec = factory.create_testtask(
@@ -72,7 +72,7 @@ def get_traintask_spec() -> TaskSpec:
     )
     testtask = client.add_task(spec)
     # `raises = True`, will fail if task not successful
-    testtask = client.wait_task(testtask.key, raises=True)
+    testtask = client.wait_task(testtask.key, raise_on_failure=True)
     assert testtask.error_type is None
     performance = client.get_task_output_asset(testtask.key, OutputIdentifiers.performance)
     assert performance.asset == pytest.approx(2)
@@ -87,7 +87,7 @@ def get_traintask_spec() -> TaskSpec:
     )
     traintask = client.add_task(spec)
     # `raises = True`, will fail if task not successful
-    traintask = client.wait_task(traintask.key, raises=True)
+    traintask = client.wait_task(traintask.key, raise_on_failure=True)
     assert testtask.error_type is None
     assert traintask.metadata == {}
 
@@ -122,7 +122,7 @@ def test_federated_learning_workflow(factory, client, default_datasets, workers)
             worker=workers[index],
         )
         traintask = client.add_task(spec)
-        traintask = client.wait_task(traintask.key, raises=True)
+        traintask = client.wait_task(traintask.key, raise_on_failure=True)
         out_models = client.get_task_models(traintask.key)
         assert traintask.error_type is None
         assert len(traintask.outputs) == 1
@@ -169,7 +169,7 @@ def test_tasks_execution_on_different_organizations(
     )
     traintask = client_1.add_task(spec)
     # `raises = True`, will fail if task not successful
-    traintask = client_1.wait_task(traintask.key, raises=True)
+    traintask = client_1.wait_task(traintask.key, raise_on_failure=True)
     assert traintask.error_type is None
     assert len(traintask.outputs) == 1
     # Raises an exception if the output asset have not been created
@@ -184,7 +184,7 @@ def test_tasks_execution_on_different_organizations(
     )
     predicttask = client_1.add_task(spec)
     # `raises = True`, will fail if task not successful
-    predicttask = client_1.wait_task(predicttask.key, raises=True)
+    predicttask = client_1.wait_task(predicttask.key, raise_on_failure=True)
     assert predicttask.error_type is None
     assert predicttask.worker == client_1.organization_id
 
@@ -195,7 +195,7 @@ def test_tasks_execution_on_different_organizations(
     )
     testtask = client_1.add_task(spec)
     # `raises = True`, will fail if task not successful
-    testtask = client_1.wait_task(testtask.key, raises=True)
+    testtask = client_1.wait_task(testtask.key, raise_on_failure=True)
     assert testtask.error_type is None
     assert testtask.worker == client_1.organization_id
     performance = client_2.get_task_output_asset(testtask.key, OutputIdentifiers.performance)
@@ -221,7 +221,7 @@ def test_function_build_failure(factory, network, default_dataset_1, worker):
             network.clients[0].add_task(spec)
     else:
         traintask = network.clients[0].add_task(spec)
-        traintask = network.clients[0].wait_task(traintask.key, raises=False)
+        traintask = network.clients[0].wait_task(traintask.key, raise_on_failure=False)
 
         assert traintask.status == Status.failed
         assert traintask.error_type == substra.sdk.models.TaskErrorType.build
@@ -248,7 +248,7 @@ def test_task_execution_failure(factory, network, default_dataset_1, worker):
             network.clients[0].add_task(spec)
     else:
         traintask = network.clients[0].add_task(spec)
-        traintask = network.clients[0].wait_task(traintask.key, raises=False)
+        traintask = network.clients[0].wait_task(traintask.key, raise_on_failure=False)
 
         assert traintask.status == Status.failed
         assert traintask.error_type == substra.sdk.models.TaskErrorType.execution
@@ -296,7 +296,7 @@ def score(inputs, outputs, task_properties):
     )
     traintask = client.add_task(spec)
     # `raises = True`, will fail if task not successful
-    traintask = client.wait_task(traintask.key, raises=True)
+    traintask = client.wait_task(traintask.key, raise_on_failure=True)
 
     # add predicttask
     spec = factory.create_predicttask(
@@ -306,7 +306,7 @@ def score(inputs, outputs, task_properties):
     )
     predicttask = client.add_task(spec)
     # `raises = True`, will fail if task not successful
-    predicttask = client.wait_task(predicttask.key, raises=True)
+    predicttask = client.wait_task(predicttask.key, raise_on_failure=True)
 
     # add metric function
     spec = factory.create_function(category=FunctionCategory.metric, py_script=custom_metric_script)
@@ -329,7 +329,7 @@ def score(inputs, outputs, task_properties):
 
     testtask = client.add_task(spec)
     # `raises = True`, will fail if task not successful
-    testtask = client.wait_task(testtask.key, raises=True)
+    testtask = client.wait_task(testtask.key, raise_on_failure=True)
     assert testtask.error_type is None
     output_1 = client.get_task_output_asset(testtask.key, identifier_1)
     output_2 = client.get_task_output_asset(testtask.key, identifier_2)
@@ -363,7 +363,7 @@ def test_composite_traintask_execution_failure(factory, client, default_dataset,
     )
     if client.backend_mode == substra.BackendType.REMOTE:
         composite_traintask = client.add_task(spec)
-        composite_traintask = client.wait_task(composite_traintask.key, raises=False)
+        composite_traintask = client.wait_task(composite_traintask.key, raise_on_failure=False)
 
         assert composite_traintask.status == Status.failed
         assert composite_traintask.error_type == substra.sdk.models.TaskErrorType.execution
@@ -409,7 +409,7 @@ def test_aggregatetask_execution_failure(factory, client, default_dataset, worke
 
     if client.backend_mode == substra.BackendType.REMOTE:
         aggregatetask = client.add_task(spec)
-        aggregatetask = client.wait_task(aggregatetask.key, raises=False)
+        aggregatetask = client.wait_task(aggregatetask.key, raise_on_failure=False)
 
         for composite_traintask_key in composite_traintask_keys:
             composite_traintask = client.get_task(composite_traintask_key)
@@ -448,7 +448,7 @@ def test_composite_traintasks_execution(factory, client, default_dataset, defaul
     )
     composite_traintask_1 = client.add_task(spec)
     # `raises = True`, will fail if task not successful
-    composite_traintask_1 = client.wait_task(composite_traintask_1.key, raises=True)
+    composite_traintask_1 = client.wait_task(composite_traintask_1.key, raise_on_failure=True)
     assert composite_traintask_1.error_type is None
     assert len(composite_traintask_1.outputs) == 2
 
@@ -461,7 +461,7 @@ def test_composite_traintasks_execution(factory, client, default_dataset, defaul
     )
     composite_traintask_2 = client.add_task(spec)
     # `raises = True`, will fail if task not successful
-    composite_traintask_2 = client.wait_task(composite_traintask_2.key, raises=True)
+    composite_traintask_2 = client.wait_task(composite_traintask_2.key, raise_on_failure=True)
     assert composite_traintask_2.error_type is None
     assert len(composite_traintask_2.outputs) == 2
 
@@ -473,7 +473,7 @@ def test_composite_traintasks_execution(factory, client, default_dataset, defaul
     )
     predicttask = client.add_task(spec)
     # `raises = True`, will fail if task not successful
-    predicttask = client.wait_task(predicttask.key, raises=True)
+    predicttask = client.wait_task(predicttask.key, raise_on_failure=True)
     assert predicttask.status == Status.done
     assert predicttask.error_type is None
 
@@ -483,7 +483,7 @@ def test_composite_traintasks_execution(factory, client, default_dataset, defaul
         worker=worker,
     )
     testtask = client.add_task(spec)
-    testtask = client.wait_task(testtask.key, raises=True)
+    testtask = client.wait_task(testtask.key, raise_on_failure=True)
     assert testtask.error_type is None
     performance = client.get_task_output_asset(testtask.key, OutputIdentifiers.performance)
     assert performance.asset == pytest.approx(32)
@@ -538,7 +538,7 @@ def test_aggregatetask(factory, client, default_metric, default_dataset, worker)
     )
     predicttask = client.add_task(spec)
     # `raises = True`, will fail if task not successful
-    client.wait_task(predicttask.key, raises=True)
+    client.wait_task(predicttask.key, raise_on_failure=True)
 
     spec = factory.create_testtask(
         function=default_metric,
@@ -547,7 +547,7 @@ def test_aggregatetask(factory, client, default_metric, default_dataset, worker)
     )
     testtask = client.add_task(spec)
     # `raises = True`, will fail if task not successful
-    client.wait_task(testtask.key, raises=True)
+    client.wait_task(testtask.key, raise_on_failure=True)
 
 
 @pytest.mark.slow
@@ -594,7 +594,7 @@ def test_aggregatetask_chained(factory, client, default_dataset, worker):
 
     aggregatetask_2 = client.add_task(spec)
     # `raises = True`, will fail if task not successful
-    client.wait_task(aggregatetask_2.key, raises=True)
+    client.wait_task(aggregatetask_2.key, raise_on_failure=True)
     assert aggregatetask_2.error_type is None
     assert len([i for i in aggregatetask_2.inputs if i.identifier == InputIdentifiers.models]) == 1
 
@@ -643,7 +643,7 @@ def test_aggregatetask_traintask(factory, client, default_dataset, worker):
 
     traintask_2 = client.add_task(spec)
     # `raises = True`, will fail if task not successful
-    traintask_2 = client.wait_task(traintask_2.key, raises=True)
+    traintask_2 = client.wait_task(traintask_2.key, raise_on_failure=True)
 
     assert traintask_2.status == Status.done
     assert traintask_2.error_type is None
@@ -687,7 +687,7 @@ def test_composite_traintask_2_organizations_to_composite_traintask(factory, cli
     )
     composite_traintask = clients[0].add_task(spec)
     # `raises = True`, will fail if task not successful
-    clients[0].wait_task(composite_traintask.key, raises=True)
+    clients[0].wait_task(composite_traintask.key, raise_on_failure=True)
 
 
 @pytest.mark.slow
@@ -760,7 +760,7 @@ def test_aggregate_composite_traintasks(factory, network, clients, default_datas
             )
 
             t = clients[0].add_task(spec)
-            clients[0].wait_task(t.key, raises=True)
+            clients[0].wait_task(t.key, raise_on_failure=True)
             composite_traintask_keys.append(t.key)
 
         # create aggregate on its organization
@@ -770,7 +770,7 @@ def test_aggregate_composite_traintasks(factory, network, clients, default_datas
             inputs=FLTaskInputGenerator.composites_to_aggregate(composite_traintask_keys),
         )
         aggregatetask = clients[0].add_task(spec)
-        clients[0].wait_task(aggregatetask.key, raises=True)
+        clients[0].wait_task(aggregatetask.key, raise_on_failure=True)
 
         # save state of round
         previous_aggregatetask_key = aggregatetask.key
@@ -786,15 +786,15 @@ def test_aggregate_composite_traintasks(factory, network, clients, default_datas
             worker=workers[index],
         )
         predicttask = clients[0].add_task(spec)
-        clients[0].wait_task(predicttask.key, raises=True)
+        clients[0].wait_task(predicttask.key, raise_on_failure=True)
 
         spec = factory.create_testtask(
             function=metric,
             inputs=dataset.test_data_inputs + FLTaskInputGenerator.predict_to_test(predicttask.key),
             worker=workers[index],
         )
         testtask = clients[0].add_task(spec)
-        clients[0].wait_task(testtask.key, raises=True)
+        clients[0].wait_task(testtask.key, raise_on_failure=True)
         # y_true: [20], y_pred: [52.0], result: 32.0
         performance = clients[0].get_task_output_asset(testtask.key, OutputIdentifiers.performance)
         assert performance.asset == pytest.approx(32 + index)
@@ -806,15 +806,15 @@ def test_aggregate_composite_traintasks(factory, network, clients, default_datas
         worker=workers[0],
     )
     predicttask = clients[0].add_task(spec)
-    clients[0].wait_task(predicttask.key, raises=True)
+    clients[0].wait_task(predicttask.key, raise_on_failure=True)
 
     spec = factory.create_testtask(
         function=default_metrics[0],
         inputs=default_datasets[0].test_data_inputs + FLTaskInputGenerator.predict_to_test(predicttask.key),
         worker=workers[0],
     )
     testtask = clients[0].add_task(spec)
-    clients[0].wait_task(testtask.key, raises=True)
+    clients[0].wait_task(testtask.key, raise_on_failure=True)
     # y_true: [20], y_pred: [28.0], result: 8.0
     performance = clients[0].get_task_output_asset(testtask.key, OutputIdentifiers.performance)
     assert performance.asset == pytest.approx(8)
@@ -875,7 +875,7 @@ def test_use_data_sample_located_in_shared_path(factory, network, client, organi
 
     spec = factory.create_traintask(function=function, inputs=dataset.train_data_inputs, worker=worker)
     traintask = client.add_task(spec)
-    traintask = client.wait_task(traintask.key, raises=True)
+    traintask = client.wait_task(traintask.key, raise_on_failure=True)
     assert traintask.error_type is None
 
     # Raises an exception if the output asset have not been created
@@ -886,14 +886,14 @@ def test_use_data_sample_located_in_shared_path(factory, network, client, organi
         function=predict_function, traintask=traintask, dataset=dataset, data_samples=[data_sample_key], worker=worker
     )
     predicttask = client.add_task(spec)
-    predicttask = client.wait_task(predicttask.key, raises=True)
+    predicttask = client.wait_task(predicttask.key, raise_on_failure=True)
     assert predicttask.error_type is None
 
     spec = factory.create_testtask(
         function=default_metric, predicttask=predicttask, dataset=dataset, data_samples=[data_sample_key], worker=worker
     )
     testtask = client.add_task(spec)
-    testtask = client.wait_task(testtask.key, raises=True)
+    testtask = client.wait_task(testtask.key, raise_on_failure=True)
     assert testtask.error_type is None
     performance = client.get_task_output_asset(testtask.key, OutputIdentifiers.performance)
     assert performance.asset == pytest.approx(2)
@@ -945,7 +945,7 @@ def save_predictions(predictions, path):
     function = client.add_function(spec)
     spec = factory.create_traintask(function=function, inputs=default_dataset.train_data_inputs, worker=worker)
     traintask = client.add_task(spec)
-    client.wait_task(traintask.key, raises=True)
+    client.wait_task(traintask.key, raise_on_failure=True)
 
 
 WRITE_TO_HOME_DIRECTORY_FUNCTION = f"""
@@ -996,6 +996,6 @@ def test_write_to_home_directory(factory, client, default_dataset, worker):
     function = client.add_function(spec)
     spec = factory.create_traintask(function=function, inputs=default_dataset.train_data_inputs, worker=worker)
     traintask = client.add_task(spec)
-    traintask = client.wait_task(traintask.key, raises=True)
+    traintask = client.wait_task(traintask.key, raise_on_failure=True)
 
     assert traintask.error_type is None

tests/test_execution_compute_plan.py

@@ -436,7 +436,7 @@ def test_compute_plan_single_client_failure(factory, client, default_dataset, de
 
     # Submit compute plan and wait for it to complete
     cp_added = client.add_compute_plan(cp_spec)
-    cp = client.wait_compute_plan(cp_added.key, raises=False)
+    cp = client.wait_compute_plan(cp_added.key, raise_on_failure=False)
 
     assert cp.status == "PLAN_STATUS_FAILED"
     assert cp.end_date is not None
@@ -649,11 +649,11 @@ def test_execution_compute_plan_canceled(factory, client, default_dataset, cfg,
     # and tasks are scheduled in the celery workers
     first_traintask = [t for t in client.list_compute_plan_tasks(cp.key) if t.rank == 0][0]
     # `raises = True`, will fail if task not successful
-    client.wait_task(first_traintask.key, raises=True)
+    client.wait_task(first_traintask.key, raise_on_failure=True)
 
     client.cancel_compute_plan(cp.key)
     # as cancel request do not directly update localrep we need to wait for the sync
-    cp = client.wait_compute_plan(cp.key, raises=False, timeout=cfg.options.organization_sync_timeout)
+    cp = client.wait_compute_plan(cp.key, raise_on_failure=False, timeout=cfg.options.organization_sync_timeout)
     assert cp.status == models.ComputePlanStatus.canceled
     assert cp.end_date is not None
     assert cp.duration is not None