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#!/usr/bin/env python
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
"""
Validate experiment metrics before creation
"""
import os
from azure.identity import DefaultAzureCredential
from azure.onlineexperimentation import OnlineExperimentationClient
from azure.onlineexperimentation.models import (
ExperimentMetric,
LifecycleStage,
DesiredDirection,
EventCountMetricDefinition,
ObservedEvent,
)
from azure.core.exceptions import HttpResponseError
def validate_metric():
endpoint = os.environ["AZURE_ONLINEEXPERIMENTATION_ENDPOINT"]
client = OnlineExperimentationClient(endpoint, DefaultAzureCredential())
# Define a metric to validate
metric_to_validate = ExperimentMetric(
lifecycle=LifecycleStage.ACTIVE,
display_name="Test metric for validation",
description="This metric definition will be validated before creation",
categories=["Test"],
desired_direction=DesiredDirection.INCREASE,
definition=EventCountMetricDefinition(event=ObservedEvent(event_name="TestEvent")),
)
try:
# Validate the metric - checks for errors in the definition
validation_result = client.validate_metric(metric_to_validate)
# Check if the metric definition is valid
if validation_result.is_valid:
print("Metric definition is valid")
# Now create the validated metric
created_metric = client.create_or_update_metric("test_metric_id", metric_to_validate)
print(f"Created metric: {created_metric.id}")
else:
# Handle validation errors
print("Metric definition has errors:")
for detail in validation_result.diagnostics:
print(f"- [{detail.code}] {detail.message}")
except HttpResponseError as error:
print(f"Operation failed: {error}")
if __name__ == "__main__":
validate_metric()
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