True,
default_resource_request=default_resource_request)
env_2 = cl.Environment(2,
"dev-2",
"cluster-2",
False,
default_resource_request=default_resource_request)
ep1 = cl.VersionEndpoint("1234", 1, "running", "localhost/1", "svc-1",
env_1.name, env_1, "grafana.com")
ep2 = cl.VersionEndpoint("4567", 1, "running", "localhost/1", "svc-2",
env_2.name, env_2, "grafana.com")
rule_1 = cl.ModelEndpointRule(
destinations=[cl.ModelEndpointRuleDestination(ep1.id, weight=100)])
rule_2 = cl.ModelEndpointRule(
destinations=[cl.ModelEndpointRuleDestination(ep2.id, weight=100)])
mdl_endpoint_1 = cl.ModelEndpoint(1, 1, None, "serving", "localhost/1", rule_1,
env_1.name, env_1)
mdl_endpoint_2 = cl.ModelEndpoint(2, 1, None, "serving", "localhost/2", rule_2,
env_2.name, env_2)
config = {
"job_config": {
"version": "v1",
"kind": "PredictionJob",
"name": "job-1",
"bigquery_source": {
"table": "project.dataset.source_table",
"features": ["feature_1", "feature_2"],
"options": {
"key": "val",
}
},
mlflow_tracking_url = "http://mlflow.api.merlin.dev"
created_at = "2019-08-29T08:13:12.377Z"
updated_at = "2019-08-29T08:13:12.377Z"
default_resource_request = cl.ResourceRequest(1, 1, "100m", "128Mi")
env_1 = cl.Environment(1,
"dev",
"cluster-1",
True,
default_resource_request=default_resource_request)
env_2 = cl.Environment(2,
"dev-2",
"cluster-2",
False,
default_resource_request=default_resource_request)
mdl_endpoint_1 = cl.ModelEndpoint(1, 1, None, "serving", "localhost", None,
env_1.name, env_1, created_at, updated_at)
@responses.activate
def test_get_project(mock_url, mock_oauth, use_google_oauth):
responses.add('GET',
'/api/v1/projects',
body=f"""[{{
"id": 0,
"name": "my-project",
"mlflow_tracking_url": "http://mlflow.api.merlin.dev",
"created_at": "{created_at}",
"updated_at": "{updated_at}"
}}]""",
status=200,
content_type='application/json')