def test_failed_http_request(self, request): response = mock.MagicMock response.status_code = 404 response.text = '{"error_code": "RESOURCE_DOES_NOT_EXIST", "message": "No experiment"}' request.return_value = response store = RestStore(lambda: MlflowHostCreds("https://hello")) with pytest.raises(MlflowException) as cm: store.list_experiments() assert "RESOURCE_DOES_NOT_EXIST: No experiment" in str(cm.value)
def __init__(self, service_context, host_creds=None, **kwargs): """ Construct an AzureMLRestStore object. :param service_context: Service context for the AzureML workspace :type service_context: azureml._restclient.service_context.ServiceContext """ logger.debug("Initializing the AzureMLRestStore") AzureMLAbstractRestStore.__init__(self, service_context, host_creds) RestStore.__init__(self, self.get_host_creds, **kwargs)
def test_get_host_creds_from_default_store_rest_store(): with mock.patch("mlflow.tracking._tracking_service.utils._get_store" ) as get_store_mock: get_store_mock.return_value = RestStore( lambda: MlflowHostCreds("http://host")) assert isinstance(_get_host_creds_from_default_store()(), MlflowHostCreds)
def test_response_with_unknown_fields(self, request): experiment_json = { "experiment_id": "1", "name": "My experiment", "artifact_location": "foo", "lifecycle_stage": "deleted", "OMG_WHAT_IS_THIS_FIELD": "Hooly cow", } response = mock.MagicMock response.status_code = 200 experiments = {"experiments": [experiment_json]} response.text = json.dumps(experiments) request.return_value = response store = RestStore(lambda: MlflowHostCreds("https://hello")) experiments = store.list_experiments() assert len(experiments) == 1 assert experiments[0].name == "My experiment"
def _get_rest_store(store_uri, **_): def get_default_host_creds(): return rest_utils.MlflowHostCreds( host=store_uri, username=os.environ.get(_TRACKING_USERNAME_ENV_VAR), password=os.environ.get(_TRACKING_PASSWORD_ENV_VAR), token=os.environ.get(_TRACKING_TOKEN_ENV_VAR), ignore_tls_verification=os.environ.get(_TRACKING_INSECURE_TLS_ENV_VAR) == 'true', ) return RestStore(get_default_host_creds)
def test_successful_http_request(self, request): def mock_request(**kwargs): # Filter out None arguments kwargs = dict((k, v) for k, v in six.iteritems(kwargs) if v is not None) assert kwargs == { "method": "GET", "params": {"view_type": "ACTIVE_ONLY"}, "url": "https://hello/api/2.0/mlflow/experiments/list", "headers": _DEFAULT_HEADERS, "verify": True, } response = mock.MagicMock response.status_code = 200 response.text = '{"experiments": [{"name": "Exp!", "lifecycle_stage": "active"}]}' return response request.side_effect = mock_request store = RestStore(lambda: MlflowHostCreds("https://hello")) experiments = store.list_experiments() assert experiments[0].name == "Exp!"
def get_db_store(self): try: tracking_uri = mlflow.get_tracking_uri() except ImportError: logger.warning(VERSION_WARNING.format("mlflow.get_tracking_uri")) tracking_uri = mlflow.tracking.get_tracking_uri() from mlflow.utils.databricks_utils import get_databricks_host_creds try: # If get_db_info_from_uri exists, it means mlflow 1.10 or above from mlflow.utils.uri import get_db_info_from_uri profile, path = get_db_info_from_uri("databricks") return RestStore(lambda: get_databricks_host_creds(tracking_uri)) except ImportError: try: from mlflow.utils.uri import get_db_profile_from_uri except ImportError: logger.warning(VERSION_WARNING.format("from mlflow")) from mlflow.tracking.utils import get_db_profile_from_uri profile = get_db_profile_from_uri("databricks") logger.info("tracking uri: {} and profile: {}".format(tracking_uri, profile)) return RestStore(lambda: get_databricks_host_creds(profile))
def test_successful_http_request(self, request): def mock_request(*args, **kwargs): # Filter out None arguments assert args == ("GET", "https://hello/api/2.0/mlflow/experiments/list") kwargs = dict((k, v) for k, v in kwargs.items() if v is not None) assert kwargs == { "params": { "view_type": "ACTIVE_ONLY" }, "headers": DefaultRequestHeaderProvider().request_headers(), "verify": True, "timeout": 120, } response = mock.MagicMock() response.status_code = 200 response.text = '{"experiments": [{"name": "Exp!", "lifecycle_stage": "active"}]}' return response request.side_effect = mock_request store = RestStore(lambda: MlflowHostCreds("https://hello")) experiments = store.list_experiments() assert experiments[0].name == "Exp!"
def _get_rest_store(store_uri, **_): return RestStore(partial(_get_default_host_creds, store_uri))
def test_requestor(self, request): response = mock.MagicMock response.status_code = 200 response.text = "{}" request.return_value = response creds = MlflowHostCreds("https://hello") store = RestStore(lambda: creds) user_name = "mock user" source_name = "rest test" source_name_patch = mock.patch( "mlflow.tracking.context.default_context._get_source_name", return_value=source_name) source_type_patch = mock.patch( "mlflow.tracking.context.default_context._get_source_type", return_value=SourceType.LOCAL, ) with mock.patch( "mlflow.utils.rest_utils.http_request" ) as mock_http, mock.patch( "mlflow.tracking._tracking_service.utils._get_store", return_value=store), mock.patch( "mlflow.tracking.context.default_context._get_user", return_value=user_name), mock.patch( "time.time", return_value=13579 ), source_name_patch, source_type_patch: with mlflow.start_run(experiment_id="43"): cr_body = message_to_json( CreateRun( experiment_id="43", user_id=user_name, start_time=13579000, tags=[ ProtoRunTag(key="mlflow.source.name", value=source_name), ProtoRunTag(key="mlflow.source.type", value="LOCAL"), ProtoRunTag(key="mlflow.user", value=user_name), ], )) expected_kwargs = self._args(creds, "runs/create", "POST", cr_body) assert mock_http.call_count == 1 actual_kwargs = mock_http.call_args[1] # Test the passed tag values separately from the rest of the request # Tag order is inconsistent on Python 2 and 3, but the order does not matter expected_tags = expected_kwargs["json"].pop("tags") actual_tags = actual_kwargs["json"].pop("tags") assert sorted(expected_tags, key=lambda t: t["key"]) == sorted( actual_tags, key=lambda t: t["key"]) assert expected_kwargs == actual_kwargs with mock.patch("mlflow.utils.rest_utils.http_request") as mock_http: store.log_param("some_uuid", Param("k1", "v1")) body = message_to_json( LogParam(run_uuid="some_uuid", run_id="some_uuid", key="k1", value="v1")) self._verify_requests(mock_http, creds, "runs/log-parameter", "POST", body) with mock.patch("mlflow.utils.rest_utils.http_request") as mock_http: store.set_experiment_tag("some_id", ExperimentTag("t1", "abcd" * 1000)) body = message_to_json( SetExperimentTag(experiment_id="some_id", key="t1", value="abcd" * 1000)) self._verify_requests(mock_http, creds, "experiments/set-experiment-tag", "POST", body) with mock.patch("mlflow.utils.rest_utils.http_request") as mock_http: store.set_tag("some_uuid", RunTag("t1", "abcd" * 1000)) body = message_to_json( SetTag(run_uuid="some_uuid", run_id="some_uuid", key="t1", value="abcd" * 1000)) self._verify_requests(mock_http, creds, "runs/set-tag", "POST", body) with mock.patch("mlflow.utils.rest_utils.http_request") as mock_http: store.delete_tag("some_uuid", "t1") body = message_to_json(DeleteTag(run_id="some_uuid", key="t1")) self._verify_requests(mock_http, creds, "runs/delete-tag", "POST", body) with mock.patch("mlflow.utils.rest_utils.http_request") as mock_http: store.log_metric("u2", Metric("m1", 0.87, 12345, 3)) body = message_to_json( LogMetric(run_uuid="u2", run_id="u2", key="m1", value=0.87, timestamp=12345, step=3)) self._verify_requests(mock_http, creds, "runs/log-metric", "POST", body) with mock.patch("mlflow.utils.rest_utils.http_request") as mock_http: metrics = [ Metric("m1", 0.87, 12345, 0), Metric("m2", 0.49, 12345, -1), Metric("m3", 0.58, 12345, 2), ] params = [Param("p1", "p1val"), Param("p2", "p2val")] tags = [RunTag("t1", "t1val"), RunTag("t2", "t2val")] store.log_batch(run_id="u2", metrics=metrics, params=params, tags=tags) metric_protos = [metric.to_proto() for metric in metrics] param_protos = [param.to_proto() for param in params] tag_protos = [tag.to_proto() for tag in tags] body = message_to_json( LogBatch(run_id="u2", metrics=metric_protos, params=param_protos, tags=tag_protos)) self._verify_requests(mock_http, creds, "runs/log-batch", "POST", body) with mock.patch("mlflow.utils.rest_utils.http_request") as mock_http: store.delete_run("u25") self._verify_requests(mock_http, creds, "runs/delete", "POST", message_to_json(DeleteRun(run_id="u25"))) with mock.patch("mlflow.utils.rest_utils.http_request") as mock_http: store.restore_run("u76") self._verify_requests(mock_http, creds, "runs/restore", "POST", message_to_json(RestoreRun(run_id="u76"))) with mock.patch("mlflow.utils.rest_utils.http_request") as mock_http: store.delete_experiment("0") self._verify_requests( mock_http, creds, "experiments/delete", "POST", message_to_json(DeleteExperiment(experiment_id="0")), ) with mock.patch("mlflow.utils.rest_utils.http_request") as mock_http: store.restore_experiment("0") self._verify_requests( mock_http, creds, "experiments/restore", "POST", message_to_json(RestoreExperiment(experiment_id="0")), ) with mock.patch("mlflow.utils.rest_utils.http_request") as mock_http: response = mock.MagicMock response.text = '{"runs": ["1a", "2b", "3c"], "next_page_token": "67890fghij"}' mock_http.return_value = response result = store.search_runs( ["0", "1"], "params.p1 = 'a'", ViewType.ACTIVE_ONLY, max_results=10, order_by=["a"], page_token="12345abcde", ) expected_message = SearchRuns( experiment_ids=["0", "1"], filter="params.p1 = 'a'", run_view_type=ViewType.to_proto(ViewType.ACTIVE_ONLY), max_results=10, order_by=["a"], page_token="12345abcde", ) self._verify_requests(mock_http, creds, "runs/search", "POST", message_to_json(expected_message)) assert result.token == "67890fghij" with mock.patch("mlflow.utils.rest_utils.http_request") as mock_http: run_id = "run_id" m = Model(artifact_path="model/path", run_id="run_id", flavors={"tf": "flavor body"}) result = store.record_logged_model("run_id", m) expected_message = LogModel(run_id=run_id, model_json=m.to_json()) self._verify_requests(mock_http, creds, "runs/log-model", "POST", message_to_json(expected_message))