def test_kedro_mlflow_config_setup_tracking_priority(mocker, tmp_path,
config_dir):
"""Test if the mlflow_tracking uri set is the one of mlflow.yml
if it also eist in credentials.
Args:
mocker ([type]): [description]
tmp_path ([type]): [description]
config_dir ([type]): [description]
"""
# create a ".kedro.yml" file to identify "tmp_path" as the root of a kedro project
mocker.patch("kedro_mlflow.utils._is_kedro_project", lambda x: True)
(tmp_path / "conf/base/credentials.yml").write_text(
yaml.dump(dict(my_mlflow_creds=dict(mlflow_tracking_uri="mlruns2"))))
config = KedroMlflowConfig(
project_path=tmp_path,
mlflow_tracking_uri="mlruns1",
credentials="my_mlflow_creds",
)
context = load_context(tmp_path)
config.setup(context)
assert mlflow.get_tracking_uri() == (tmp_path / "mlruns1").as_uri()
def test_kedro_mlflow_config_setup_tracking_priority(kedro_project_with_mlflow_conf):
"""Test if the mlflow_tracking uri set is the one of mlflow.yml
if it also eist in credentials.
Args:
mocker ([type]): [description]
tmp_path ([type]): [description]
"""
# create a ".kedro.yml" file to identify "tmp_path" as the root of a kedro project
(kedro_project_with_mlflow_conf / "conf/base/credentials.yml").write_text(
yaml.dump(dict(my_mlflow_creds=dict(mlflow_tracking_uri="mlruns2")))
)
config = KedroMlflowConfig(
project_path=kedro_project_with_mlflow_conf,
mlflow_tracking_uri="mlruns1",
credentials="my_mlflow_creds",
)
project_metadata = _get_project_metadata(kedro_project_with_mlflow_conf)
_add_src_to_path(project_metadata.source_dir, kedro_project_with_mlflow_conf)
configure_project(project_metadata.package_name)
with KedroSession.create(
"fake_project", project_path=kedro_project_with_mlflow_conf
):
config.setup()
assert (
mlflow.get_tracking_uri()
== (kedro_project_with_mlflow_conf / "mlruns1").as_uri()
)
def test_kedro_mlflow_config_experiment_was_deleted(kedro_project_with_mlflow_conf):
# create an experiment with the same name and then delete it
mlflow_tracking_uri = (kedro_project_with_mlflow_conf / "mlruns").as_uri()
mlflow_client = MlflowClient(mlflow_tracking_uri)
mlflow_client.create_experiment("exp1")
mlflow_client.delete_experiment(
mlflow_client.get_experiment_by_name("exp1").experiment_id
)
# the config must restore properly the experiment
config = KedroMlflowConfig(
project_path=kedro_project_with_mlflow_conf,
mlflow_tracking_uri="mlruns",
experiment_opts=dict(name="exp1"),
)
project_metadata = _get_project_metadata(kedro_project_with_mlflow_conf)
_add_src_to_path(project_metadata.source_dir, kedro_project_with_mlflow_conf)
configure_project(project_metadata.package_name)
with KedroSession.create(
"fake_project", project_path=kedro_project_with_mlflow_conf
):
config.setup()
assert "exp1" in [exp.name for exp in config.mlflow_client.list_experiments()]
def test_kedro_mlflow_config_new_experiment_does_not_exists(
mocker, tmp_path, config_dir):
# create a ".kedro.yml" file to identify "tmp_path" as the root of a kedro project
mocker.patch("kedro_mlflow.utils._is_kedro_project", return_value=True)
config = KedroMlflowConfig(
project_path=tmp_path,
mlflow_tracking_uri="mlruns",
experiment_opts=dict(name="exp1"),
)
context = load_context(tmp_path)
config.setup(context)
assert "exp1" in [
exp.name for exp in config.mlflow_client.list_experiments()
]
def test_kedro_mlflow_config_setup_export_credentials(mocker, tmp_path,
config_dir):
# create a ".kedro.yml" file to identify "tmp_path" as the root of a kedro project
mocker.patch("kedro_mlflow.utils._is_kedro_project", lambda x: True)
(tmp_path / "conf/base/credentials.yml").write_text(
yaml.dump(dict(my_mlflow_creds=dict(fake_mlflow_cred="my_fake_cred"))))
# the config must restore properly the experiment
config = KedroMlflowConfig(project_path=tmp_path,
credentials="my_mlflow_creds")
context = load_context(tmp_path)
config.setup(context)
assert os.environ["fake_mlflow_cred"] == "my_fake_cred"
def test_kedro_mlflow_config_setup_set_tracking_uri(mocker, tmp_path,
config_dir):
# create a ".kedro.yml" file to identify "tmp_path" as the root of a kedro project
mocker.patch("kedro_mlflow.utils._is_kedro_project", lambda x: True)
# create an experiment with the same name and then delete it
mlflow_tracking_uri = (tmp_path / "awesome_tracking").as_uri()
# the config must restore properly the experiment
config = KedroMlflowConfig(
project_path=tmp_path,
mlflow_tracking_uri="awesome_tracking",
experiment_opts=dict(name="exp1"),
)
context = load_context(tmp_path)
config.setup(context)
assert mlflow.get_tracking_uri() == mlflow_tracking_uri
def test_kedro_mlflow_config_new_experiment_does_not_exists(
kedro_project_with_mlflow_conf,
):
config = KedroMlflowConfig(
project_path=kedro_project_with_mlflow_conf,
mlflow_tracking_uri="mlruns",
experiment_opts=dict(name="exp1"),
)
project_metadata = _get_project_metadata(kedro_project_with_mlflow_conf)
_add_src_to_path(project_metadata.source_dir, kedro_project_with_mlflow_conf)
configure_project(project_metadata.package_name)
with KedroSession.create(
"fake_project", project_path=kedro_project_with_mlflow_conf
):
config.setup()
assert "exp1" in [exp.name for exp in config.mlflow_client.list_experiments()]
def test_kedro_mlflow_config_setup_export_credentials(kedro_project_with_mlflow_conf):
(kedro_project_with_mlflow_conf / "conf/base/credentials.yml").write_text(
yaml.dump(dict(my_mlflow_creds=dict(fake_mlflow_cred="my_fake_cred")))
)
# the config must restore properly the experiment
config = KedroMlflowConfig(
project_path=kedro_project_with_mlflow_conf, credentials="my_mlflow_creds"
)
project_metadata = _get_project_metadata(kedro_project_with_mlflow_conf)
_add_src_to_path(project_metadata.source_dir, kedro_project_with_mlflow_conf)
configure_project(project_metadata.package_name)
with KedroSession.create(
"fake_project", project_path=kedro_project_with_mlflow_conf
):
config.setup()
assert os.environ["fake_mlflow_cred"] == "my_fake_cred"
def test_kedro_mlflow_config_setup_set_tracking_uri(kedro_project_with_mlflow_conf):
# create an experiment with the same name and then delete it
mlflow_tracking_uri = (kedro_project_with_mlflow_conf / "awesome_tracking").as_uri()
# the config must restore properly the experiment
config = KedroMlflowConfig(
project_path=kedro_project_with_mlflow_conf,
mlflow_tracking_uri="awesome_tracking",
experiment_opts=dict(name="exp1"),
)
project_metadata = _get_project_metadata(kedro_project_with_mlflow_conf)
_add_src_to_path(project_metadata.source_dir, kedro_project_with_mlflow_conf)
configure_project(project_metadata.package_name)
with KedroSession.create(
"fake_project", project_path=kedro_project_with_mlflow_conf
):
config.setup()
assert mlflow.get_tracking_uri() == mlflow_tracking_uri
def test_kedro_mlflow_config_experiment_exists(mocker, kedro_project_with_mlflow_conf):
# create an experiment with the same name
mlflow_tracking_uri = (
kedro_project_with_mlflow_conf / "conf" / "local" / "mlruns"
).as_uri()
MlflowClient(mlflow_tracking_uri).create_experiment("exp1")
config = KedroMlflowConfig(
project_path=kedro_project_with_mlflow_conf,
mlflow_tracking_uri="mlruns",
experiment_opts=dict(name="exp1"),
)
project_metadata = _get_project_metadata(kedro_project_with_mlflow_conf)
_add_src_to_path(project_metadata.source_dir, kedro_project_with_mlflow_conf)
configure_project(project_metadata.package_name)
with KedroSession.create(
"fake_project", project_path=kedro_project_with_mlflow_conf
):
config.setup()
assert "exp1" in [exp.name for exp in config.mlflow_client.list_experiments()]
def test_kedro_mlflow_config_experiment_was_deleted(mocker, tmp_path,
config_dir):
# create a ".kedro.yml" file to identify "tmp_path" as the root of a kedro project
mocker.patch("kedro_mlflow.utils._is_kedro_project", lambda x: True)
# create an experiment with the same name and then delete it
mlflow_tracking_uri = (tmp_path / "mlruns").as_uri()
mlflow_client = MlflowClient(mlflow_tracking_uri)
mlflow_client.create_experiment("exp1")
mlflow_client.delete_experiment(
mlflow_client.get_experiment_by_name("exp1").experiment_id)
# the config must restore properly the experiment
config = KedroMlflowConfig(
project_path=tmp_path,
mlflow_tracking_uri="mlruns",
experiment_opts=dict(name="exp1"),
)
context = load_context(tmp_path)
config.setup(context)
assert "exp1" in [
exp.name for exp in config.mlflow_client.list_experiments()
]