Python MetadataServiceAsyncClient Examples

Example #1

File: aiplatform_generated_aiplatform_v1_metadata_service_create_context_async.py Project: morgandu/python-aiplatform

async def sample_create_context():
    # Create a client
    client = aiplatform_v1.MetadataServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1.CreateContextRequest(parent="parent_value", )

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

    # Handle the response
    print(response)

Example #2

async def sample_get_metadata_store():
    # Create a client
    client = aiplatform_v1.MetadataServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1.GetMetadataStoreRequest(name="name_value", )

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

    # Handle the response
    print(response)

Example #3

File: aiplatform_v1_generated_metadata_service_update_execution_async.py Project: morgandu/python-aiplatform

async def sample_update_execution():
    # Create a client
    client = aiplatform_v1.MetadataServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1.UpdateExecutionRequest()

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

    # Handle the response
    print(response)

Example #4

File: aiplatform_generated_aiplatform_v1_metadata_service_list_executions_async.py Project: morgandu/python-aiplatform

async def sample_list_executions():
    # Create a client
    client = aiplatform_v1.MetadataServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1.ListExecutionsRequest(parent="parent_value", )

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

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

Example #5

async def sample_query_artifact_lineage_subgraph():
    # Create a client
    client = aiplatform_v1.MetadataServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1.QueryArtifactLineageSubgraphRequest(
        artifact="artifact_value", )

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

    # Handle the response
    print(response)

Example #6

File: aiplatform_generated_aiplatform_v1_metadata_service_add_context_children_async.py Project: morgandu/python-aiplatform

async def sample_add_context_children():
    # Create a client
    client = aiplatform_v1.MetadataServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1.AddContextChildrenRequest(
        context="context_value", )

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

    # Handle the response
    print(response)

Example #7

File: aiplatform_generated_aiplatform_v1_metadata_service_query_execution_inputs_and_outputs_async.py Project: morgandu/python-aiplatform

async def sample_query_execution_inputs_and_outputs():
    # Create a client
    client = aiplatform_v1.MetadataServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1.QueryExecutionInputsAndOutputsRequest(
        execution="execution_value", )

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

    # Handle the response
    print(response)

Example #8

File: aiplatform_generated_aiplatform_v1_metadata_service_add_context_artifacts_and_executions_async.py Project: morgandu/python-aiplatform

async def sample_add_context_artifacts_and_executions():
    # Create a client
    client = aiplatform_v1.MetadataServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1.AddContextArtifactsAndExecutionsRequest(
        context="context_value", )

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

    # Handle the response
    print(response)

Example #9

async def sample_add_execution_events():
    # Create a client
    client = aiplatform_v1.MetadataServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1.AddExecutionEventsRequest(
        execution="execution_value",
    )

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

    # Handle the response
    print(response)

Example #10

async def sample_delete_context():
    # Create a client
    client = aiplatform_v1.MetadataServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1.DeleteContextRequest(name="name_value", )

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

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

    response = await operation.result()

    # Handle the response
    print(response)

Example #11

async def sample_create_metadata_store():
    # Create a client
    client = aiplatform_v1.MetadataServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1.CreateMetadataStoreRequest(parent="parent_value", )

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

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

    response = await operation.result()

    # Handle the response
    print(response)

Example #12

File: aiplatform_v1_generated_metadata_service_create_metadata_schema_async.py Project: morgandu/python-aiplatform

async def sample_create_metadata_schema():
    # Create a client
    client = aiplatform_v1.MetadataServiceAsyncClient()

    # Initialize request argument(s)
    metadata_schema = aiplatform_v1.MetadataSchema()
    metadata_schema.schema = "schema_value"

    request = aiplatform_v1.CreateMetadataSchemaRequest(
        parent="parent_value",
        metadata_schema=metadata_schema,
    )

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

    # Handle the response
    print(response)

Example #13

File: aiplatform_generated_aiplatform_v1_metadata_service_purge_contexts_async.py Project: morgandu/python-aiplatform

async def sample_purge_contexts():
    # Create a client
    client = aiplatform_v1.MetadataServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1.PurgeContextsRequest(
        parent="parent_value",
        filter="filter_value",
    )

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

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

    response = await operation.result()

    # Handle the response
    print(response)