def test_get_artifact_uri_appends_to_uri_path_component_correctly(
artifact_location, expected_uri_format):
client = MlflowClient()
client.create_experiment("get-artifact-uri-test", artifact_location=artifact_location)
mlflow.set_experiment("get-artifact-uri-test")
with mlflow.start_run():
run_id = mlflow.active_run().info.run_id
for artifact_path in ["path/to/artifact", "/artifact/path", "arty.txt"]:
artifact_uri = mlflow.get_artifact_uri(artifact_path)
assert artifact_uri == tracking.artifact_utils.get_artifact_uri(run_id, artifact_path)
assert artifact_uri == expected_uri_format.format(
run_id=run_id, path=artifact_path.lstrip("/"))
def set_experiment(experiment_name):
"""
Set given experiment as active experiment. If experiment does not exist, create an experiment
with provided name.
:param experiment_name: Name of experiment to be activated.
"""
client = MlflowClient()
experiment = client.get_experiment_by_name(experiment_name)
exp_id = experiment.experiment_id if experiment else None
if exp_id is None: # id can be 0
print("INFO: '{}' does not exist. Creating a new experiment".format(experiment_name))
exp_id = client.create_experiment(experiment_name)
global _active_experiment_id
_active_experiment_id = exp_id
def set_experiment(experiment_name):
"""
Set given experiment as active experiment. If experiment does not exist, create an experiment
with provided name.
:param experiment_name: Case sensitive name of an experiment to be activated.
.. code-block:: python
:caption: Example
import mlflow
# Set an experiment name, which must be unique and case sensitive.
mlflow.set_experiment("Social NLP Experiments")
# Get Experiment Details
experiment = mlflow.get_experiment_by_name("Social NLP Experiments")
# Print the contents of Experiment data
print("Experiment_id: {}".format(experiment.experiment_id))
print("Artifact Location: {}".format(experiment.artifact_location))
print("Tags: {}".format(experiment.tags))
print("Lifecycle_stage: {}".format(experiment.lifecycle_stage))
.. code-block:: text
:caption: Output
Experiment_id: 1
Artifact Location: file:///.../mlruns/1
Tags: {}
Lifecycle_stage: active
"""
client = MlflowClient()
experiment = client.get_experiment_by_name(experiment_name)
exp_id = experiment.experiment_id if experiment else None
if exp_id is None: # id can be 0
print("INFO: '{}' does not exist. Creating a new experiment".format(
experiment_name))
exp_id = client.create_experiment(experiment_name)
elif experiment.lifecycle_stage == LifecycleStage.DELETED:
raise MlflowException(
"Cannot set a deleted experiment '%s' as the active experiment."
" You can restore the experiment, or permanently delete the "
" experiment to create a new one." % experiment.name)
global _active_experiment_id
_active_experiment_id = exp_id
def set_experiment(experiment_name):
"""
Set given experiment as active experiment. If experiment does not exist, create an experiment
with provided name.
:param experiment_name: Name of experiment to be activated.
"""
client = MlflowClient()
experiment = client.get_experiment_by_name(experiment_name)
exp_id = experiment.experiment_id if experiment else None
if exp_id is None: # id can be 0
print("INFO: '{}' does not exist. Creating a new experiment".format(experiment_name))
exp_id = client.create_experiment(experiment_name)
elif experiment.lifecycle_stage == LifecycleStage.DELETED:
raise MlflowException(
"Cannot set a deleted experiment '%s' as the active experiment."
" You can restore the experiment, or permanently delete the "
" experiment to create a new one." % experiment.name)
global _active_experiment_id
_active_experiment_id = exp_id
import mlflow
from mlflow.tracking.client import MlflowClient
client = MlflowClient()
exp_name = "artifact_test_experiment"
if client.get_experiment_by_name(exp_name) is None:
client.create_experiment(exp_name,
artifact_location="sqlite:///testartifactdb")
mlflow.set_experiment(exp_name)
fpath = "test.txt"
with open(fpath, "w") as f:
f.write("TEST")
with mlflow.start_run():
mlflow.log_artifact(fpath, "")
import mlflow
from mlflow.tracking.client import MlflowClient
client = MlflowClient()
exp_name = "artifact_test_experiment_sql"
if client.get_experiment_by_name(exp_name) is None:
client.create_experiment(exp_name, artifact_location="mssql+pyodbc://sqluser:Mlflow2019@[email protected]:1433/mlflow_test?driver=ODBC+Driver+17+for+SQL+Server")
mlflow.set_experiment(exp_name)
fpath = "test.txt"
with open(fpath, "w") as f:
f.write("TEST")
with mlflow.start_run():
mlflow.log_artifact(fpath, "")
from mlflow.tracking.client import MlflowClient
from datetime import datetime, timedelta
import math
import random
random.seed(42)
client = MlflowClient()
mock_experiment_file = f'/tmp/mock_experiment'
# Delete experiment if it already exists
if client.get_experiment_by_name(mock_experiment_file):
client.delete_experiment(
client.get_experiment_by_name(mock_experiment_file).experiment_id)
mock_experiment_id = client.create_experiment(mock_experiment_file)
def simulate_runs(dt, eid, mae, num_runs=1):
'''
Simulates a run(s) with a specified datetime, experiment, and mae.
:param dt: Timestamp used for both run start_time and log_metric time.
:param eid: Experiment id to log this run under.
:param mae: Mean absolute error metric to log.
:param num_runs: Number of runs to store.
'''
ts = int(dt.timestamp() * 1000)
for _ in range(num_runs):
run = client.create_run(experiment_id=eid, start_time=ts)