Class Execution (1.18.3)

Version 1.18.3

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Execution(
    execution_name: str,
    *,
    metadata_store_id: str = "default",
    project: Optional[str] = None,
    location: Optional[str] = None,
    credentials: Optional[google.auth.credentials.Credentials] = None
)

Metadata Execution resource for Vertex AI

Inheritance

builtins.object > google.cloud.aiplatform.base.VertexAiResourceNoun > builtins.object > google.cloud.aiplatform.base.FutureManager > google.cloud.aiplatform.base.VertexAiResourceNounWithFutureManager > builtins.object > abc.ABC > google.cloud.aiplatform.metadata.resource._Resource > Execution

Properties

create_time

Time this resource was created.

display_name

Display name of this resource.

encryption_spec

Customer-managed encryption key options for this Vertex AI resource.

If this is set, then all resources created by this Vertex AI resource will be encrypted with the provided encryption key.

gca_resource

The underlying resource proto representation.

labels

User-defined labels containing metadata about this resource.

Read more about labels at https://goo.gl/xmQnxf

name

Name of this resource.

resource_name

Full qualified resource name.

state

State of this Execution.

update_time

Time this resource was last updated.

Methods

Execution

Execution(
    execution_name: str,
    *,
    metadata_store_id: str = "default",
    project: Optional[str] = None,
    location: Optional[str] = None,
    credentials: Optional[google.auth.credentials.Credentials] = None
)

Retrieves an existing Metadata Execution given a resource name or ID.

Parameters

Name	Description
execution_name	str Required. A fully-qualified resource name or resource ID of the Execution. Example: "projects/123/locations/us-central1/metadataStores/default/executions/my-resource". or "my-resource" when project and location are initialized or passed.
metadata_store_id	str Optional. MetadataStore to retrieve Execution from. If not set, metadata_store_id is set to "default". If execution_name is a fully-qualified resource, its metadata_store_id overrides this one.
project	str Optional. Project to retrieve the artifact from. If not set, project set in aiplatform.init will be used.
location	str Optional. Location to retrieve the Execution from. If not set, location set in aiplatform.init will be used.
credentials	auth_credentials.Credentials Optional. Custom credentials to use to retrieve this Execution. Overrides credentials set in aiplatform.init.

assign_input_artifacts

assign_input_artifacts(
    artifacts: List[
        Union[
            google.cloud.aiplatform.metadata.artifact.Artifact,
            google.cloud.aiplatform.models.Model,
        ]
    ]
)

Assigns Artifacts as inputs to this Executions.

Parameter

Name	Description
artifacts	List[Union[artifact.Artifact, models.Model]] Required. Artifacts to assign as input.

assign_output_artifacts

assign_output_artifacts(
    artifacts: List[
        Union[
            google.cloud.aiplatform.metadata.artifact.Artifact,
            google.cloud.aiplatform.models.Model,
        ]
    ]
)

Assigns Artifacts as outputs to this Executions.

Parameter

Name	Description
artifacts	List[Union[artifact.Artifact, models.Model]] Required. Artifacts to assign as input.

create

create(schema_title: str, *, state: google.cloud.aiplatform_v1.types.execution.Execution.State = <State.RUNNING: 2>, resource_id: Optional[str] = None, display_name: Optional[str] = None, schema_version: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None, description: Optional[str] = None, metadata_store_id: str = 'default', project: Optional[str] = None, location: Optional[str] = None, credentials=typing.Union[google.auth.credentials.Credentials, NoneType])

Creates a new Metadata Execution.

Parameters

Name	Description
schema_title	str Required. schema_title identifies the schema title used by the Execution.
state	gca_execution.Execution.State.RUNNING Optional. State of this Execution. Defaults to RUNNING.
resource_id	str Optional. The <resource_id> portion of the Execution name with the format. This is globally unique in a metadataStore: projects/123/locations/us-central1/metadataStores/<metadata_store_id>/executions/<resource_id>.
display_name	str Optional. The user-defined name of the Execution.
schema_version	str Optional. schema_version specifies the version used by the Execution. If not set, defaults to use the latest version.
metadata	Dict Optional. Contains the metadata information that will be stored in the Execution.
description	str Optional. Describes the purpose of the Execution to be created.
metadata_store_id	str Optional. The <metadata_store_id> portion of the resource name with the format: projects/123/locations/us-central1/metadataStores/<metadata_store_id>/artifacts/<resource_id> If not provided, the MetadataStore's ID will be set to "default".
project	str Optional. Project used to create this Execution. Overrides project set in aiplatform.init.
location	str Optional. Location used to create this Execution. Overrides location set in aiplatform.init.
credentials	auth_credentials.Credentials Optional. Custom credentials used to create this Execution. Overrides credentials set in aiplatform.init.

Returns

Type	Description
Execution	Instantiated representation of the managed Metadata Execution.

delete

delete(sync: bool = True)

Deletes this Vertex AI resource. WARNING: This deletion is permanent.

Parameter

Name	Description
sync	bool Whether to execute this deletion synchronously. If False, this method will be executed in concurrent Future and any downstream object will be immediately returned and synced when the Future has completed.

get

get(
    resource_id: str,
    metadata_store_id: str = "default",
    project: Optional[str] = None,
    location: Optional[str] = None,
    credentials: Optional[google.auth.credentials.Credentials] = None,
)

Retrieves a Metadata resource.

Parameters

Name	Description
resource_id	str Required. The <resource_id> portion of the resource name with the format: projects/123/locations/us-central1/metadataStores/<metadata_store_id>/<resource_noun>/<resource_id>.
metadata_store_id	str The <metadata_store_id> portion of the resource name with the format: projects/123/locations/us-central1/metadataStores/<metadata_store_id>/<resource_noun>/<resource_id> If not provided, the MetadataStore's ID will be set to "default".
project	str Project used to retrieve or create this resource. Overrides project set in aiplatform.init.
location	str Location used to retrieve or create this resource. Overrides location set in aiplatform.init.
credentials	auth_credentials.Credentials Custom credentials used to retrieve or create this resource. Overrides credentials set in aiplatform.init.

Returns

Type	Description
resource (_Resource)	Instantiated representation of the managed Metadata resource or None if no resource was found.

get_input_artifacts

get_input_artifacts()

Get the input Artifacts of this Execution.

get_or_create

get_or_create(
    resource_id: str,
    schema_title: str,
    display_name: Optional[str] = None,
    schema_version: Optional[str] = None,
    description: Optional[str] = None,
    metadata: Optional[Dict] = None,
    metadata_store_id: str = "default",
    project: Optional[str] = None,
    location: Optional[str] = None,
    credentials: Optional[google.auth.credentials.Credentials] = None,
)

Retrieves or Creates (if it does not exist) a Metadata resource.

Parameters

Name	Description
resource_id	str Required. The <resource_id> portion of the resource name with the format: projects/123/locations/us-central1/metadataStores/<metadata_store_id>/<resource_noun>/<resource_id>.
schema_title	str Required. schema_title identifies the schema title used by the resource.
display_name	str Optional. The user-defined name of the resource.
schema_version	str Optional. schema_version specifies the version used by the resource. If not set, defaults to use the latest version.
description	str Optional. Describes the purpose of the resource to be created.
metadata	Dict Optional. Contains the metadata information that will be stored in the resource.
metadata_store_id	str The <metadata_store_id> portion of the resource name with the format: projects/123/locations/us-central1/metadataStores/<metadata_store_id>/<resource_noun>/<resource_id> If not provided, the MetadataStore's ID will be set to "default".
project	str Project used to retrieve or create this resource. Overrides project set in aiplatform.init.
location	str Location used to retrieve or create this resource. Overrides location set in aiplatform.init.
credentials	auth_credentials.Credentials Custom credentials used to retrieve or create this resource. Overrides credentials set in aiplatform.init.

Returns

Type	Description
resource (_Resource)	Instantiated representation of the managed Metadata resource.

get_output_artifacts

get_output_artifacts()

Get the output Artifacts of this Execution.

list

list(
    filter: Optional[str] = None,
    metadata_store_id: str = "default",
    project: Optional[str] = None,
    location: Optional[str] = None,
    credentials: Optional[google.auth.credentials.Credentials] = None,
)

List Metadata resources that match the list filter in target metadataStore.

Parameters

Name	Description
filter	str Optional. A query to filter available resources for matching results.
metadata_store_id	str The <metadata_store_id> portion of the resource name with the format: projects/123/locations/us-central1/metadataStores/<metadata_store_id>/<resource_noun>/<resource_id> If not provided, the MetadataStore's ID will be set to "default".
project	str Project used to create this resource. Overrides project set in aiplatform.init.
location	str Location used to create this resource. Overrides location set in aiplatform.init.
credentials	auth_credentials.Credentials Custom credentials used to create this resource. Overrides credentials set in aiplatform.init.

Returns

Type	Description
resources (sequence[_Resource])	a list of managed Metadata resource.

sync_resource

sync_resource()

Syncs local resource with the resource in metadata store.

to_dict

to_dict()

Returns the resource proto as a dictionary.

update

update(
    state: Optional[google.cloud.aiplatform_v1.types.execution.Execution.State] = None,
    description: Optional[str] = None,
    metadata: Optional[Dict[str, Any]] = None,
)

Update this Execution.

Parameters

Name	Description
state	gca_execution.Execution.State Optional. State of this Execution.
description	str Optional. Describes the purpose of the Execution to be created.
metadata	Dict[str, Any Optional. Contains the metadata information that will be stored in the Execution.

wait

wait()

Helper method that blocks until all futures are complete.