Class MetadataServiceClient (1.18.3)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_add_context_artifacts_and_executions():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.AddContextArtifactsAndExecutionsRequest(
        context="context_value",
    )

    # Make the request
    response = client.add_context_artifacts_and_executions(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_add_context_children():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.AddContextChildrenRequest(
        context="context_value",
    )

    # Make the request
    response = client.add_context_children(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_add_execution_events():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.AddExecutionEventsRequest(
        execution="execution_value",
    )

    # Make the request
    response = client.add_execution_events(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_create_artifact():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.CreateArtifactRequest(
        parent="parent_value",
    )

    # Make the request
    response = client.create_artifact(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_create_context():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.CreateContextRequest(
        parent="parent_value",
    )

    # Make the request
    response = client.create_context(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_create_execution():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.CreateExecutionRequest(
        parent="parent_value",
    )

    # Make the request
    response = client.create_execution(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_create_metadata_schema():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    metadata_schema = aiplatform_v1beta1.MetadataSchema()
    metadata_schema.schema = "schema_value"

    request = aiplatform_v1beta1.CreateMetadataSchemaRequest(
        parent="parent_value",
        metadata_schema=metadata_schema,
    )

    # Make the request
    response = client.create_metadata_schema(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_create_metadata_store():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.CreateMetadataStoreRequest(
        parent="parent_value",
    )

    # Make the request
    operation = client.create_metadata_store(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_delete_artifact():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.DeleteArtifactRequest(
        name="name_value",
    )

    # Make the request
    operation = client.delete_artifact(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_delete_context():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.DeleteContextRequest(
        name="name_value",
    )

    # Make the request
    operation = client.delete_context(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_delete_execution():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.DeleteExecutionRequest(
        name="name_value",
    )

    # Make the request
    operation = client.delete_execution(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_delete_metadata_store():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.DeleteMetadataStoreRequest(
        name="name_value",
    )

    # Make the request
    operation = client.delete_metadata_store(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_get_artifact():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.GetArtifactRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_artifact(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_get_context():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.GetContextRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_context(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_get_execution():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.GetExecutionRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_execution(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_get_metadata_schema():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.GetMetadataSchemaRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_metadata_schema(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_get_metadata_store():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.GetMetadataStoreRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_metadata_store(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_list_artifacts():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.ListArtifactsRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_artifacts(request=request)

    # Handle the response
    for response in page_result:
        print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_list_contexts():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.ListContextsRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_contexts(request=request)

    # Handle the response
    for response in page_result:
        print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_list_executions():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.ListExecutionsRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_executions(request=request)

    # Handle the response
    for response in page_result:
        print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_list_metadata_schemas():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.ListMetadataSchemasRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_metadata_schemas(request=request)

    # Handle the response
    for response in page_result:
        print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_list_metadata_stores():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.ListMetadataStoresRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_metadata_stores(request=request)

    # Handle the response
    for response in page_result:
        print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_purge_artifacts():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.PurgeArtifactsRequest(
        parent="parent_value",
        filter="filter_value",
    )

    # Make the request
    operation = client.purge_artifacts(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_purge_contexts():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.PurgeContextsRequest(
        parent="parent_value",
        filter="filter_value",
    )

    # Make the request
    operation = client.purge_contexts(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_purge_executions():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.PurgeExecutionsRequest(
        parent="parent_value",
        filter="filter_value",
    )

    # Make the request
    operation = client.purge_executions(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_query_artifact_lineage_subgraph():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.QueryArtifactLineageSubgraphRequest(
        artifact="artifact_value",
    )

    # Make the request
    response = client.query_artifact_lineage_subgraph(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_query_context_lineage_subgraph():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.QueryContextLineageSubgraphRequest(
        context="context_value",
    )

    # Make the request
    response = client.query_context_lineage_subgraph(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_query_execution_inputs_and_outputs():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.QueryExecutionInputsAndOutputsRequest(
        execution="execution_value",
    )

    # Make the request
    response = client.query_execution_inputs_and_outputs(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_remove_context_children():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.RemoveContextChildrenRequest(
        context="context_value",
    )

    # Make the request
    response = client.remove_context_children(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_update_artifact():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.UpdateArtifactRequest(
    )

    # Make the request
    response = client.update_artifact(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_update_context():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.UpdateContextRequest(
    )

    # Make the request
    response = client.update_context(request=request)

    # Handle the response
    print(response)

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1beta1

def sample_update_execution():
    # Create a client
    client = aiplatform_v1beta1.MetadataServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.UpdateExecutionRequest(
    )

    # Make the request
    response = client.update_execution(request=request)

    # Handle the response
    print(response)