def test_list_experiments(view_type, tmpdir):
sqlite_uri = "sqlite:///" + os.path.join(tmpdir.strpath, "test.db")
store = SqlAlchemyStore(sqlite_uri, default_artifact_root=tmpdir.strpath)
num_experiments = SEARCH_MAX_RESULTS_DEFAULT + 1
if view_type == ViewType.DELETED_ONLY:
# Delete the default experiment
mlflow.tracking.MlflowClient(sqlite_uri).delete_experiment("0")
# This is a bit hacky but much faster than creating experiments one by one with
# `mlflow.create_experiment`
with store.ManagedSessionMaker() as session:
lifecycle_stages = LifecycleStage.view_type_to_stages(view_type)
experiments = [
SqlExperiment(
name=f"exp_{i + 1}",
lifecycle_stage=random.choice(lifecycle_stages),
artifact_location=tmpdir.strpath,
) for i in range(num_experiments - 1)
]
session.add_all(experiments)
try:
url, process = _init_server(sqlite_uri,
root_artifact_uri=tmpdir.strpath)
print("In process %s", process)
mlflow.set_tracking_uri(url)
# `max_results` is unspecified
assert len(mlflow.list_experiments(view_type)) == num_experiments
# `max_results` is larger than the number of experiments in the database
assert len(mlflow.list_experiments(view_type, num_experiments +
1)) == num_experiments
# `max_results` is equal to the number of experiments in the database
assert len(mlflow.list_experiments(view_type,
num_experiments)) == num_experiments
# `max_results` is smaller than the number of experiments in the database
assert len(mlflow.list_experiments(view_type, num_experiments -
1)) == num_experiments - 1
finally:
process.terminate()
def list_experiments(view):
"""
List all experiments in the configured tracking server.
"""
view_type = ViewType.from_string(view) if view else ViewType.ACTIVE_ONLY
experiments = mlflow.list_experiments(view_type)
table = [[
exp.experiment_id,
exp.name,
exp.artifact_location if is_uri(exp.artifact_location) else
os.path.abspath(exp.artifact_location),
] for exp in experiments]
print(
tabulate(sorted(table),
headers=["Experiment Id", "Name", "Artifact Location"]))
def test_list_experiments():
start_run_and_log_data()
experiments = mlflow.list_experiments(view_type=ViewType.ALL,
max_results=5)
assert len(experiments) > 0
