Class MetadataServiceClient (1.28.1)

Version 1.28.1

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MetadataServiceClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.aiplatform_v1.services.metadata_service.transports.base.MetadataServiceTransport]] = None, client_options: typing.Optional[typing.Union[google.api_core.client_options.ClientOptions, dict]] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

Service for reading and writing metadata entries.

Properties

transport

Returns the transport used by the client instance.

Returns
Type	Description
MetadataServiceTransport	The transport used by the client instance.

Methods

MetadataServiceClient

MetadataServiceClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.aiplatform_v1.services.metadata_service.transports.base.MetadataServiceTransport]] = None, client_options: typing.Optional[typing.Union[google.api_core.client_options.ClientOptions, dict]] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

Instantiates the metadata service client.

Parameters
Name	Description
credentials	Optional[google.auth.credentials.Credentials] The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment.
transport	Union[str, MetadataServiceTransport] The transport to use. If set to None, a transport is chosen automatically.
client_options	Optional[Union[google.api_core.client_options.ClientOptions, dict]] Custom options for the client. It won't take effect if a transport instance is provided. (1) The api_endpoint property can be used to override the default endpoint provided by the client. GOOGLE_API_USE_MTLS_ENDPOINT environment variable can also be used to override the endpoint: "always" (always use the default mTLS endpoint), "never" (always use the default regular endpoint) and "auto" (auto switch to the default mTLS endpoint if client certificate is present, this is the default value). However, the api_endpoint property takes precedence if provided. (2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "true", then the client_cert_source property can be used to provide client certificate for mutual TLS transport. If not provided, the default SSL client certificate will be used if present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not set, no client certificate will be used.
client_info	google.api_core.gapic_v1.client_info.ClientInfo The client info used to send a user-agent string along with API requests. If None, then default info will be used. Generally, you only need to set this if you're developing your own client library.

Exceptions
Type	Description
google.auth.exceptions.MutualTLSChannelError	If mutual TLS transport creation failed for any reason.

__exit__

__exit__(type, value, traceback)

Releases underlying transport's resources.

Warning: ONLY use as a context manager if the transport is NOT shared with other clients! Exiting the with block will CLOSE the transport and may cause errors in other clients!

add_context_artifacts_and_executions

add_context_artifacts_and_executions(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.AddContextArtifactsAndExecutionsRequest,
            dict,
        ]
    ] = None,
    *,
    context: typing.Optional[str] = None,
    artifacts: typing.Optional[typing.MutableSequence[str]] = None,
    executions: typing.Optional[typing.MutableSequence[str]] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
    google.cloud.aiplatform_v1.types.metadata_service.AddContextArtifactsAndExecutionsResponse
)

Adds a set of Artifacts and Executions to a Context. If any of the Artifacts or Executions have already been added to a Context, they are simply skipped.

# 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_v1

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

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.AddContextArtifactsAndExecutionsRequest, dict] The request object. Request message for MetadataService.AddContextArtifactsAndExecutions.
context	str Required. The resource name of the Context that the Artifacts and Executions belong to. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context} This corresponds to the context field on the request instance; if request is provided, this should not be set.
artifacts	MutableSequence[str] The resource names of the Artifacts to attribute to the Context. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact} This corresponds to the artifacts field on the request instance; if request is provided, this should not be set.
executions	MutableSequence[str] The resource names of the Executions to associate with the Context. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution} This corresponds to the executions field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.types.AddContextArtifactsAndExecutionsResponse	Response message for MetadataService.AddContextArtifactsAndExecutions.

add_context_children

add_context_children(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.AddContextChildrenRequest,
            dict,
        ]
    ] = None,
    *,
    context: typing.Optional[str] = None,
    child_contexts: typing.Optional[typing.MutableSequence[str]] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.metadata_service.AddContextChildrenResponse

Adds a set of Contexts as children to a parent Context. If any of the child Contexts have already been added to the parent Context, they are simply skipped. If this call would create a cycle or cause any Context to have more than 10 parents, the request will fail with an INVALID_ARGUMENT error.

# 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_v1

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

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.AddContextChildrenRequest, dict] The request object. Request message for MetadataService.AddContextChildren.
context	str Required. The resource name of the parent Context. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context} This corresponds to the context field on the request instance; if request is provided, this should not be set.
child_contexts	MutableSequence[str] The resource names of the child Contexts. This corresponds to the child_contexts field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.types.AddContextChildrenResponse	Response message for MetadataService.AddContextChildren.

add_execution_events

add_execution_events(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.AddExecutionEventsRequest,
            dict,
        ]
    ] = None,
    *,
    execution: typing.Optional[str] = None,
    events: typing.Optional[
        typing.MutableSequence[google.cloud.aiplatform_v1.types.event.Event]
    ] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.metadata_service.AddExecutionEventsResponse

Adds Events to the specified Execution. An Event indicates whether an Artifact was used as an input or output for an Execution. If an Event already exists between the Execution and the Artifact, the Event is skipped.

# 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_v1

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

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.AddExecutionEventsRequest, dict] The request object. Request message for MetadataService.AddExecutionEvents.
execution	str Required. The resource name of the Execution that the Events connect Artifacts with. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution} This corresponds to the execution field on the request instance; if request is provided, this should not be set.
events	MutableSequence[google.cloud.aiplatform_v1.types.Event] The Events to create and add. This corresponds to the events field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.types.AddExecutionEventsResponse	Response message for MetadataService.AddExecutionEvents.

artifact_path

artifact_path(
    project: str, location: str, metadata_store: str, artifact: str
) -> str

Returns a fully-qualified artifact string.

cancel_operation

cancel_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.CancelOperationRequest
    ] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None

Starts asynchronous cancellation on a long-running operation.

The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters
Name	Description
request	.operations_pb2.CancelOperationRequest The request object. Request message for CancelOperation method.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

common_billing_account_path

common_billing_account_path(billing_account: str) -> str

Returns a fully-qualified billing_account string.

common_folder_path

common_folder_path(folder: str) -> str

Returns a fully-qualified folder string.

common_location_path

common_location_path(project: str, location: str) -> str

Returns a fully-qualified location string.

common_organization_path

common_organization_path(organization: str) -> str

Returns a fully-qualified organization string.

common_project_path

common_project_path(project: str) -> str

Returns a fully-qualified project string.

context_path

context_path(project: str, location: str, metadata_store: str, context: str) -> str

Returns a fully-qualified context string.

create_artifact

create_artifact(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.CreateArtifactRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    artifact: typing.Optional[
        google.cloud.aiplatform_v1.types.artifact.Artifact
    ] = None,
    artifact_id: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.artifact.Artifact

Creates an Artifact associated with a MetadataStore.

# 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_v1

def sample_create_artifact():
    # Create a client
    client = aiplatform_v1.MetadataServiceClient()

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.CreateArtifactRequest, dict] The request object. Request message for MetadataService.CreateArtifact.
parent	str Required. The resource name of the MetadataStore where the Artifact should be created. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
artifact	google.cloud.aiplatform_v1.types.Artifact Required. The Artifact to create. This corresponds to the artifact field on the request instance; if request is provided, this should not be set.
artifact_id	str The {artifact} portion of the resource name with the format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact} If not provided, the Artifact's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are /a-z][0-9]-/. Must be unique across all Artifacts in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Artifact.) This corresponds to the artifact_id field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.types.Artifact	Instance of a general artifact.

create_context

create_context(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.CreateContextRequest, dict
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    context: typing.Optional[google.cloud.aiplatform_v1.types.context.Context] = None,
    context_id: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.context.Context

Creates a Context associated with a MetadataStore.

# 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_v1

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

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.CreateContextRequest, dict] The request object. Request message for MetadataService.CreateContext.
parent	str Required. The resource name of the MetadataStore where the Context should be created. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
context	google.cloud.aiplatform_v1.types.Context Required. The Context to create. This corresponds to the context field on the request instance; if request is provided, this should not be set.
context_id	str The {context} portion of the resource name with the format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}. If not provided, the Context's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are /a-z][0-9]-/. Must be unique across all Contexts in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Context.) This corresponds to the context_id field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.types.Context	Instance of a general context.

create_execution

create_execution(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.CreateExecutionRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    execution: typing.Optional[
        google.cloud.aiplatform_v1.types.execution.Execution
    ] = None,
    execution_id: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.execution.Execution

Creates an Execution associated with a MetadataStore.

# 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_v1

def sample_create_execution():
    # Create a client
    client = aiplatform_v1.MetadataServiceClient()

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.CreateExecutionRequest, dict] The request object. Request message for MetadataService.CreateExecution.
parent	str Required. The resource name of the MetadataStore where the Execution should be created. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
execution	google.cloud.aiplatform_v1.types.Execution Required. The Execution to create. This corresponds to the execution field on the request instance; if request is provided, this should not be set.
execution_id	str The {execution} portion of the resource name with the format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution} If not provided, the Execution's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are /a-z][0-9]-/. Must be unique across all Executions in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Execution.) This corresponds to the execution_id field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.types.Execution	Instance of a general execution.

create_metadata_schema

create_metadata_schema(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.CreateMetadataSchemaRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    metadata_schema: typing.Optional[
        google.cloud.aiplatform_v1.types.metadata_schema.MetadataSchema
    ] = None,
    metadata_schema_id: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.metadata_schema.MetadataSchema

Creates a MetadataSchema.

# 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_v1

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

    # 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 = client.create_metadata_schema(request=request)

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.CreateMetadataSchemaRequest, dict] The request object. Request message for MetadataService.CreateMetadataSchema.
parent	str Required. The resource name of the MetadataStore where the MetadataSchema should be created. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
metadata_schema	google.cloud.aiplatform_v1.types.MetadataSchema Required. The MetadataSchema to create. This corresponds to the metadata_schema field on the request instance; if request is provided, this should not be set.
metadata_schema_id	str The {metadata_schema} portion of the resource name with the format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/metadataSchemas/{metadataschema} If not provided, the MetadataStore's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are /a-z][0-9]-/. Must be unique across all MetadataSchemas in the parent Location. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting MetadataSchema.) This corresponds to the metadata_schema_id field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.types.MetadataSchema	Instance of a general MetadataSchema.

create_metadata_store

create_metadata_store(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.CreateMetadataStoreRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    metadata_store: typing.Optional[
        google.cloud.aiplatform_v1.types.metadata_store.MetadataStore
    ] = None,
    metadata_store_id: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Initializes a MetadataStore, including allocation of resources.

# 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_v1

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

    # 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 = operation.result()

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.CreateMetadataStoreRequest, dict] The request object. Request message for MetadataService.CreateMetadataStore.
parent	str Required. The resource name of the Location where the MetadataStore should be created. Format: projects/{project}/locations/{location}/ This corresponds to the parent field on the request instance; if request is provided, this should not be set.
metadata_store	google.cloud.aiplatform_v1.types.MetadataStore Required. The MetadataStore to create. This corresponds to the metadata_store field on the request instance; if request is provided, this should not be set.
metadata_store_id	str The {metadatastore} portion of the resource name with the format: projects/{project}/locations/{location}/metadataStores/{metadatastore} If not provided, the MetadataStore's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are /a-z][0-9]-/. Must be unique across all MetadataStores in the parent Location. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting MetadataStore.) This corresponds to the metadata_store_id field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.api_core.operation.Operation	An object representing a long-running operation. The result type for the operation will be MetadataStore Instance of a metadata store. Contains a set of metadata that can be queried.

delete_artifact

delete_artifact(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.DeleteArtifactRequest,
            dict,
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Deletes an Artifact.

# 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_v1

def sample_delete_artifact():
    # Create a client
    client = aiplatform_v1.MetadataServiceClient()

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

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.DeleteArtifactRequest, dict] The request object. Request message for MetadataService.DeleteArtifact.
name	str Required. The resource name of the Artifact to delete. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.api_core.operation.Operation	An object representing a long-running operation. The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }

delete_context

delete_context(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.DeleteContextRequest, dict
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Deletes a stored Context.

# 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_v1

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

    # 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 = operation.result()

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.DeleteContextRequest, dict] The request object. Request message for MetadataService.DeleteContext.
name	str Required. The resource name of the Context to delete. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.api_core.operation.Operation	An object representing a long-running operation. The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }

delete_execution

delete_execution(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.DeleteExecutionRequest,
            dict,
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Deletes an Execution.

# 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_v1

def sample_delete_execution():
    # Create a client
    client = aiplatform_v1.MetadataServiceClient()

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

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.DeleteExecutionRequest, dict] The request object. Request message for MetadataService.DeleteExecution.
name	str Required. The resource name of the Execution to delete. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.api_core.operation.Operation	An object representing a long-running operation. The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }

delete_metadata_store

delete_metadata_store(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.DeleteMetadataStoreRequest,
            dict,
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Deletes a single MetadataStore and all its child resources (Artifacts, Executions, and Contexts).

# 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_v1

def sample_delete_metadata_store():
    # Create a client
    client = aiplatform_v1.MetadataServiceClient()

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

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.DeleteMetadataStoreRequest, dict] The request object. Request message for MetadataService.DeleteMetadataStore.
name	str Required. The resource name of the MetadataStore to delete. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.api_core.operation.Operation	An object representing a long-running operation. The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }

delete_operation

delete_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.DeleteOperationRequest
    ] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None

Deletes a long-running operation.

This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters
Name	Description
request	.operations_pb2.DeleteOperationRequest The request object. Request message for DeleteOperation method.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

execution_path

execution_path(
    project: str, location: str, metadata_store: str, execution: str
) -> str

Returns a fully-qualified execution string.

from_service_account_file

from_service_account_file(filename: str, *args, **kwargs)

Creates an instance of this client using the provided credentials file.

Parameter
Name	Description
filename	str The path to the service account private key json file.

Returns
Type	Description
MetadataServiceClient	The constructed client.

from_service_account_info

from_service_account_info(info: dict, *args, **kwargs)

Creates an instance of this client using the provided credentials info.

Parameter
Name	Description
info	dict The service account private key info.

Returns
Type	Description
MetadataServiceClient	The constructed client.

from_service_account_json

from_service_account_json(filename: str, *args, **kwargs)

Creates an instance of this client using the provided credentials file.

Parameter
Name	Description
filename	str The path to the service account private key json file.

Returns
Type	Description
MetadataServiceClient	The constructed client.

get_artifact

get_artifact(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.GetArtifactRequest, dict
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.artifact.Artifact

Retrieves a specific Artifact.

# 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_v1

def sample_get_artifact():
    # Create a client
    client = aiplatform_v1.MetadataServiceClient()

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.GetArtifactRequest, dict] The request object. Request message for MetadataService.GetArtifact.
name	str Required. The resource name of the Artifact to retrieve. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.types.Artifact	Instance of a general artifact.

get_context

get_context(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.GetContextRequest, dict
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.context.Context

Retrieves a specific Context.

# 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_v1

def sample_get_context():
    # Create a client
    client = aiplatform_v1.MetadataServiceClient()

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.GetContextRequest, dict] The request object. Request message for MetadataService.GetContext.
name	str Required. The resource name of the Context to retrieve. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.types.Context	Instance of a general context.

get_execution

get_execution(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.GetExecutionRequest, dict
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.execution.Execution

Retrieves a specific Execution.

# 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_v1

def sample_get_execution():
    # Create a client
    client = aiplatform_v1.MetadataServiceClient()

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.GetExecutionRequest, dict] The request object. Request message for MetadataService.GetExecution.
name	str Required. The resource name of the Execution to retrieve. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.types.Execution	Instance of a general execution.

get_iam_policy

get_iam_policy(
    request: typing.Optional[google.iam.v1.iam_policy_pb2.GetIamPolicyRequest] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.policy_pb2.Policy

Gets the IAM access control policy for a function.

Returns an empty policy if the function exists and does not have a policy set.

Parameters
Name	Description
request	.iam_policy_pb2.GetIamPolicyRequest The request object. Request message for GetIamPolicy method.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
.policy_pb2.Policy	Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings. A binding binds one or more members to a single role. Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition, which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource. **JSON Example** :: { "bindings": [ { "role": "roles/resourcemanager.organizationAdmin", "members": [ "user:[e-mail]", "group:[e-mail]", "domain:google.com", "serviceAccount:[e-mail]" ] }, { "role": "roles/resourcemanager.organizationViewer", "members": ["user:[e-mail]"], "condition": { "title": "expirable access", "description": "Does not grant access after Sep 2020", "expression": "request.time < timestamp('2020-10-01t00:00:00.000z')",="" }="" }="" ]="" }="" **yaml="" example**="" ::="" bindings:="" -="" members:="" -="" user:[e-mail]="" -="" group:[e-mail]="" -="" domain:google.com="" -="" serviceaccount:[e-mail]="" role:="" roles/resourcemanager.organizationadmin="" -="" members:="" -="" user:[e-mail]="" role:="" roles/resourcemanager.organizationviewer="" condition:="" title:="" expirable="" access="" description:="" does="" not="" grant="" access="" after="" sep="" 2020="" expression:="" request.time="">< timestamp('2020-10-01t00:00:00.000z')="" for="" a="" description="" of="" iam="" and="" its="" features,="" see="" the="">IAM developer's guide __.

get_location

get_location(
    request: typing.Optional[
        google.cloud.location.locations_pb2.GetLocationRequest
    ] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.location.locations_pb2.Location

Gets information about a location.

Parameters
Name	Description
request	.location_pb2.GetLocationRequest The request object. Request message for GetLocation method.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
.location_pb2.Location	Location object.

get_metadata_schema

get_metadata_schema(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.GetMetadataSchemaRequest,
            dict,
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.metadata_schema.MetadataSchema

Retrieves a specific MetadataSchema.

# 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_v1

def sample_get_metadata_schema():
    # Create a client
    client = aiplatform_v1.MetadataServiceClient()

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.GetMetadataSchemaRequest, dict] The request object. Request message for MetadataService.GetMetadataSchema.
name	str Required. The resource name of the MetadataSchema to retrieve. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/metadataSchemas/{metadataschema} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.types.MetadataSchema	Instance of a general MetadataSchema.

get_metadata_store

get_metadata_store(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.GetMetadataStoreRequest,
            dict,
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.metadata_store.MetadataStore

Retrieves a specific MetadataStore.

# 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_v1

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

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.GetMetadataStoreRequest, dict] The request object. Request message for MetadataService.GetMetadataStore.
name	str Required. The resource name of the MetadataStore to retrieve. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.types.MetadataStore	Instance of a metadata store. Contains a set of metadata that can be queried.

get_mtls_endpoint_and_cert_source

get_mtls_endpoint_and_cert_source(
    client_options: typing.Optional[
        google.api_core.client_options.ClientOptions
    ] = None,
)

Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order: (1) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is not "true", the client cert source is None. (2) if client_options.client_cert_source is provided, use the provided one; if the default client cert source exists, use the default one; otherwise the client cert source is None.

The API endpoint is determined in the following order: (1) if client_options.api_endpoint if provided, use the provided one. (2) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "always", use the default mTLS endpoint; if the environment variable is "never", use the default API endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114.

Parameter
Name	Description
client_options	google.api_core.client_options.ClientOptions Custom options for the client. Only the api_endpoint and client_cert_source properties may be used in this method.

Exceptions
Type	Description
google.auth.exceptions.MutualTLSChannelError	If any errors happen.

Returns
Type	Description
Tuple[str, Callable[[], Tuple[bytes, bytes]]]	returns the API endpoint and the client cert source to use.

get_operation

get_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.GetOperationRequest
    ] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.Operation

Gets the latest state of a long-running operation.

Parameters
Name	Description
request	.operations_pb2.GetOperationRequest The request object. Request message for GetOperation method.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
.operations_pb2.Operation	An Operation object.

list_artifacts

list_artifacts(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.ListArtifactsRequest, dict
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.services.metadata_service.pagers.ListArtifactsPager

Lists Artifacts in the MetadataStore.

# 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_v1

def sample_list_artifacts():
    # Create a client
    client = aiplatform_v1.MetadataServiceClient()

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

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

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

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.ListArtifactsRequest, dict] The request object. Request message for MetadataService.ListArtifacts.
parent	str Required. The MetadataStore whose Artifacts should be listed. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.services.metadata_service.pagers.ListArtifactsPager	Response message for MetadataService.ListArtifacts. Iterating over this object will yield results and resolve additional pages automatically.

list_contexts

list_contexts(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.ListContextsRequest, dict
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.services.metadata_service.pagers.ListContextsPager

Lists Contexts on the MetadataStore.

# 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_v1

def sample_list_contexts():
    # Create a client
    client = aiplatform_v1.MetadataServiceClient()

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

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

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

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.ListContextsRequest, dict] The request object. Request message for MetadataService.ListContexts
parent	str Required. The MetadataStore whose Contexts should be listed. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.services.metadata_service.pagers.ListContextsPager	Response message for MetadataService.ListContexts. Iterating over this object will yield results and resolve additional pages automatically.

list_executions

list_executions(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.ListExecutionsRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.services.metadata_service.pagers.ListExecutionsPager

Lists Executions in the MetadataStore.

# 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_v1

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

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

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

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

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.ListExecutionsRequest, dict] The request object. Request message for MetadataService.ListExecutions.
parent	str Required. The MetadataStore whose Executions should be listed. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.services.metadata_service.pagers.ListExecutionsPager	Response message for MetadataService.ListExecutions. Iterating over this object will yield results and resolve additional pages automatically.

list_locations

list_locations(
    request: typing.Optional[
        google.cloud.location.locations_pb2.ListLocationsRequest
    ] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.location.locations_pb2.ListLocationsResponse

Lists information about the supported locations for this service.

Parameters
Name	Description
request	.location_pb2.ListLocationsRequest The request object. Request message for ListLocations method.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
.location_pb2.ListLocationsResponse	Response message for ListLocations method.

list_metadata_schemas

list_metadata_schemas(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.ListMetadataSchemasRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
    google.cloud.aiplatform_v1.services.metadata_service.pagers.ListMetadataSchemasPager
)

Lists MetadataSchemas.

# 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_v1

def sample_list_metadata_schemas():
    # Create a client
    client = aiplatform_v1.MetadataServiceClient()

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

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.ListMetadataSchemasRequest, dict] The request object. Request message for MetadataService.ListMetadataSchemas.
parent	str Required. The MetadataStore whose MetadataSchemas should be listed. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.services.metadata_service.pagers.ListMetadataSchemasPager	Response message for MetadataService.ListMetadataSchemas. Iterating over this object will yield results and resolve additional pages automatically.

list_metadata_stores

list_metadata_stores(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.ListMetadataStoresRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
    google.cloud.aiplatform_v1.services.metadata_service.pagers.ListMetadataStoresPager
)

Lists MetadataStores for a Location.

# 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_v1

def sample_list_metadata_stores():
    # Create a client
    client = aiplatform_v1.MetadataServiceClient()

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

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.ListMetadataStoresRequest, dict] The request object. Request message for MetadataService.ListMetadataStores.
parent	str Required. The Location whose MetadataStores should be listed. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.services.metadata_service.pagers.ListMetadataStoresPager	Response message for MetadataService.ListMetadataStores. Iterating over this object will yield results and resolve additional pages automatically.

list_operations

list_operations(
    request: typing.Optional[
        google.longrunning.operations_pb2.ListOperationsRequest
    ] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.ListOperationsResponse

Lists operations that match the specified filter in the request.

Parameters
Name	Description
request	.operations_pb2.ListOperationsRequest The request object. Request message for ListOperations method.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
.operations_pb2.ListOperationsResponse	Response message for ListOperations method.

metadata_schema_path

metadata_schema_path(
    project: str, location: str, metadata_store: str, metadata_schema: str
) -> str

Returns a fully-qualified metadata_schema string.

metadata_store_path

metadata_store_path(project: str, location: str, metadata_store: str) -> str

Returns a fully-qualified metadata_store string.

parse_artifact_path

parse_artifact_path(path: str) -> typing.Dict[str, str]

Parses a artifact path into its component segments.

parse_common_billing_account_path

parse_common_billing_account_path(path: str) -> typing.Dict[str, str]

Parse a billing_account path into its component segments.

parse_common_folder_path

parse_common_folder_path(path: str) -> typing.Dict[str, str]

Parse a folder path into its component segments.

parse_common_location_path

parse_common_location_path(path: str) -> typing.Dict[str, str]

Parse a location path into its component segments.

parse_common_organization_path

parse_common_organization_path(path: str) -> typing.Dict[str, str]

Parse a organization path into its component segments.

parse_common_project_path

parse_common_project_path(path: str) -> typing.Dict[str, str]

Parse a project path into its component segments.

parse_context_path

parse_context_path(path: str) -> typing.Dict[str, str]

Parses a context path into its component segments.

parse_execution_path

parse_execution_path(path: str) -> typing.Dict[str, str]

Parses a execution path into its component segments.

parse_metadata_schema_path

parse_metadata_schema_path(path: str) -> typing.Dict[str, str]

Parses a metadata_schema path into its component segments.

parse_metadata_store_path

parse_metadata_store_path(path: str) -> typing.Dict[str, str]

Parses a metadata_store path into its component segments.

purge_artifacts

purge_artifacts(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.PurgeArtifactsRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Purges Artifacts.

# 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_v1

def sample_purge_artifacts():
    # Create a client
    client = aiplatform_v1.MetadataServiceClient()

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

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.PurgeArtifactsRequest, dict] The request object. Request message for MetadataService.PurgeArtifacts.
parent	str Required. The metadata store to purge Artifacts from. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.api_core.operation.Operation	An object representing a long-running operation. The result type for the operation will be PurgeArtifactsResponse Response message for MetadataService.PurgeArtifacts.

purge_contexts

purge_contexts(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.PurgeContextsRequest, dict
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Purges Contexts.

# 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_v1

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

    # 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 = operation.result()

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.PurgeContextsRequest, dict] The request object. Request message for MetadataService.PurgeContexts.
parent	str Required. The metadata store to purge Contexts from. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.api_core.operation.Operation	An object representing a long-running operation. The result type for the operation will be PurgeContextsResponse Response message for MetadataService.PurgeContexts.

purge_executions

purge_executions(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.PurgeExecutionsRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Purges Executions.

# 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_v1

def sample_purge_executions():
    # Create a client
    client = aiplatform_v1.MetadataServiceClient()

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

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.PurgeExecutionsRequest, dict] The request object. Request message for MetadataService.PurgeExecutions.
parent	str Required. The metadata store to purge Executions from. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.api_core.operation.Operation	An object representing a long-running operation. The result type for the operation will be PurgeExecutionsResponse Response message for MetadataService.PurgeExecutions.

query_artifact_lineage_subgraph

query_artifact_lineage_subgraph(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.QueryArtifactLineageSubgraphRequest,
            dict,
        ]
    ] = None,
    *,
    artifact: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.lineage_subgraph.LineageSubgraph

Retrieves lineage of an Artifact represented through Artifacts and Executions connected by Event edges and returned as a LineageSubgraph.

# 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_v1

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

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.QueryArtifactLineageSubgraphRequest, dict] The request object. Request message for MetadataService.QueryArtifactLineageSubgraph.
artifact	str Required. The resource name of the Artifact whose Lineage needs to be retrieved as a LineageSubgraph. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact} The request may error with FAILED_PRECONDITION if the number of Artifacts, the number of Executions, or the number of Events that would be returned for the Context exceeds 1000. This corresponds to the artifact field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.types.LineageSubgraph	A subgraph of the overall lineage graph. Event edges connect Artifact and Execution nodes.

query_context_lineage_subgraph

query_context_lineage_subgraph(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.QueryContextLineageSubgraphRequest,
            dict,
        ]
    ] = None,
    *,
    context: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.lineage_subgraph.LineageSubgraph

Retrieves Artifacts and Executions within the specified Context, connected by Event edges and returned as a LineageSubgraph.

# 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_v1

def sample_query_context_lineage_subgraph():
    # Create a client
    client = aiplatform_v1.MetadataServiceClient()

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.QueryContextLineageSubgraphRequest, dict] The request object. Request message for MetadataService.QueryContextLineageSubgraph.
context	str Required. The resource name of the Context whose Artifacts and Executions should be retrieved as a LineageSubgraph. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context} The request may error with FAILED_PRECONDITION if the number of Artifacts, the number of Executions, or the number of Events that would be returned for the Context exceeds 1000. This corresponds to the context field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.types.LineageSubgraph	A subgraph of the overall lineage graph. Event edges connect Artifact and Execution nodes.

query_execution_inputs_and_outputs

query_execution_inputs_and_outputs(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.QueryExecutionInputsAndOutputsRequest,
            dict,
        ]
    ] = None,
    *,
    execution: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.lineage_subgraph.LineageSubgraph

Obtains the set of input and output Artifacts for this Execution, in the form of LineageSubgraph that also contains the Execution and connecting Events.

# 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_v1

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

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.QueryExecutionInputsAndOutputsRequest, dict] The request object. Request message for MetadataService.QueryExecutionInputsAndOutputs.
execution	str Required. The resource name of the Execution whose input and output Artifacts should be retrieved as a LineageSubgraph. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution} This corresponds to the execution field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.types.LineageSubgraph	A subgraph of the overall lineage graph. Event edges connect Artifact and Execution nodes.

remove_context_children

remove_context_children(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.RemoveContextChildrenRequest,
            dict,
        ]
    ] = None,
    *,
    context: typing.Optional[str] = None,
    child_contexts: typing.Optional[typing.MutableSequence[str]] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.metadata_service.RemoveContextChildrenResponse

Remove a set of children contexts from a parent Context. If any of the child Contexts were NOT added to the parent Context, they are simply skipped.

# 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_v1

def sample_remove_context_children():
    # Create a client
    client = aiplatform_v1.MetadataServiceClient()

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.RemoveContextChildrenRequest, dict] The request object. Request message for [MetadataService.DeleteContextChildrenRequest][].
context	str Required. The resource name of the parent Context. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context} This corresponds to the context field on the request instance; if request is provided, this should not be set.
child_contexts	MutableSequence[str] The resource names of the child Contexts. This corresponds to the child_contexts field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.types.RemoveContextChildrenResponse	Response message for MetadataService.RemoveContextChildren.

set_iam_policy

set_iam_policy(
    request: typing.Optional[google.iam.v1.iam_policy_pb2.SetIamPolicyRequest] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.policy_pb2.Policy

Sets the IAM access control policy on the specified function.

Replaces any existing policy.

Parameters
Name	Description
request	.iam_policy_pb2.SetIamPolicyRequest The request object. Request message for SetIamPolicy method.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
.policy_pb2.Policy	Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings. A binding binds one or more members to a single role. Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition, which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource. **JSON Example** :: { "bindings": [ { "role": "roles/resourcemanager.organizationAdmin", "members": [ "user:[e-mail]", "group:[e-mail]", "domain:google.com", "serviceAccount:[e-mail]" ] }, { "role": "roles/resourcemanager.organizationViewer", "members": ["user:[e-mail]"], "condition": { "title": "expirable access", "description": "Does not grant access after Sep 2020", "expression": "request.time < timestamp('2020-10-01t00:00:00.000z')",="" }="" }="" ]="" }="" **yaml="" example**="" ::="" bindings:="" -="" members:="" -="" user:[e-mail]="" -="" group:[e-mail]="" -="" domain:google.com="" -="" serviceaccount:[e-mail]="" role:="" roles/resourcemanager.organizationadmin="" -="" members:="" -="" user:[e-mail]="" role:="" roles/resourcemanager.organizationviewer="" condition:="" title:="" expirable="" access="" description:="" does="" not="" grant="" access="" after="" sep="" 2020="" expression:="" request.time="">< timestamp('2020-10-01t00:00:00.000z')="" for="" a="" description="" of="" iam="" and="" its="" features,="" see="" the="">IAM developer's guide __.

test_iam_permissions

test_iam_permissions(
    request: typing.Optional[
        google.iam.v1.iam_policy_pb2.TestIamPermissionsRequest
    ] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.iam_policy_pb2.TestIamPermissionsResponse

Tests the specified IAM permissions against the IAM access control policy for a function.

If the function does not exist, this will return an empty set of permissions, not a NOT_FOUND error.

Parameters
Name	Description
request	.iam_policy_pb2.TestIamPermissionsRequest The request object. Request message for TestIamPermissions method.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
.iam_policy_pb2.TestIamPermissionsResponse	Response message for TestIamPermissions method.

update_artifact

update_artifact(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.UpdateArtifactRequest,
            dict,
        ]
    ] = None,
    *,
    artifact: typing.Optional[
        google.cloud.aiplatform_v1.types.artifact.Artifact
    ] = None,
    update_mask: typing.Optional[google.protobuf.field_mask_pb2.FieldMask] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.artifact.Artifact

Updates a stored Artifact.

# 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_v1

def sample_update_artifact():
    # Create a client
    client = aiplatform_v1.MetadataServiceClient()

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.UpdateArtifactRequest, dict] The request object. Request message for MetadataService.UpdateArtifact.
artifact	google.cloud.aiplatform_v1.types.Artifact Required. The Artifact containing updates. The Artifact's Artifact.name field is used to identify the Artifact to be updated. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact} This corresponds to the artifact field on the request instance; if request is provided, this should not be set.
update_mask	google.protobuf.field_mask_pb2.FieldMask Optional. A FieldMask indicating which fields should be updated. This corresponds to the update_mask field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.types.Artifact	Instance of a general artifact.

update_context

update_context(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.UpdateContextRequest, dict
        ]
    ] = None,
    *,
    context: typing.Optional[google.cloud.aiplatform_v1.types.context.Context] = None,
    update_mask: typing.Optional[google.protobuf.field_mask_pb2.FieldMask] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.context.Context

Updates a stored Context.

# 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_v1

def sample_update_context():
    # Create a client
    client = aiplatform_v1.MetadataServiceClient()

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.UpdateContextRequest, dict] The request object. Request message for MetadataService.UpdateContext.
context	google.cloud.aiplatform_v1.types.Context Required. The Context containing updates. The Context's Context.name field is used to identify the Context to be updated. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context} This corresponds to the context field on the request instance; if request is provided, this should not be set.
update_mask	google.protobuf.field_mask_pb2.FieldMask Optional. A FieldMask indicating which fields should be updated. This corresponds to the update_mask field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.types.Context	Instance of a general context.

update_execution

update_execution(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.metadata_service.UpdateExecutionRequest,
            dict,
        ]
    ] = None,
    *,
    execution: typing.Optional[
        google.cloud.aiplatform_v1.types.execution.Execution
    ] = None,
    update_mask: typing.Optional[google.protobuf.field_mask_pb2.FieldMask] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.execution.Execution

Updates a stored Execution.

# 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_v1

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

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
request	Union[google.cloud.aiplatform_v1.types.UpdateExecutionRequest, dict] The request object. Request message for MetadataService.UpdateExecution.
execution	google.cloud.aiplatform_v1.types.Execution Required. The Execution containing updates. The Execution's Execution.name field is used to identify the Execution to be updated. Format: projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution} This corresponds to the execution field on the request instance; if request is provided, this should not be set.
update_mask	google.protobuf.field_mask_pb2.FieldMask Optional. A FieldMask indicating which fields should be updated. This corresponds to the update_mask field on the request instance; if request is provided, this should not be set.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
google.cloud.aiplatform_v1.types.Execution	Instance of a general execution.

wait_operation

wait_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.WaitOperationRequest
    ] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.Operation

Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state.

If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters
Name	Description
request	.operations_pb2.WaitOperationRequest The request object. Request message for WaitOperation method.
retry	google.api_core.retry.Retry Designation of what errors, if any, should be retried.
timeout	float The timeout for this request.
metadata	Sequence[Tuple[str, str]] Strings which should be sent along with the request as metadata.

Returns
Type	Description
.operations_pb2.Operation	An Operation object.