Class PipelineJob (1.62.0)

Version 1.62.0

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PipelineJob(mapping=None, *, ignore_unknown_fields=False, **kwargs)

An instance of a machine learning PipelineJob.

Attributes
Name	Description
name	str Output only. The resource name of the PipelineJob.
display_name	str The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
create_time	google.protobuf.timestamp_pb2.Timestamp Output only. Pipeline creation time.
start_time	google.protobuf.timestamp_pb2.Timestamp Output only. Pipeline start time.
end_time	google.protobuf.timestamp_pb2.Timestamp Output only. Pipeline end time.
update_time	google.protobuf.timestamp_pb2.Timestamp Output only. Timestamp when this PipelineJob was most recently updated.
pipeline_spec	google.protobuf.struct_pb2.Struct The spec of the pipeline.
state	google.cloud.aiplatform_v1.types.PipelineState Output only. The detailed state of the job.
job_detail	google.cloud.aiplatform_v1.types.PipelineJobDetail Output only. The details of pipeline run. Not available in the list view.
error	google.rpc.status_pb2.Status Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
labels	MutableMapping[str, str] The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - vertex-ai-pipelines-run-billing-id, user set value will get overrided.
runtime_config	google.cloud.aiplatform_v1.types.PipelineJob.RuntimeConfig Runtime config of the pipeline.
encryption_spec	google.cloud.aiplatform_v1.types.EncryptionSpec Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
service_account	str The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the iam.serviceAccounts.actAs permission on this service account.
network	str The full name of the Compute Engine network __ to which the Pipeline Job's workload should be peered. For example, projects/12345/global/networks/myVPC. Format __ is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.
reserved_ip_ranges	MutableSequence[str] A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
template_uri	str A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.
template_metadata	google.cloud.aiplatform_v1.types.PipelineTemplateMetadata Output only. Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
schedule_name	str Output only. The schedule resource name. Only returned if the Pipeline is created by Schedule API.
preflight_validations	bool Optional. Whether to do component level validations before job creation.

Classes

LabelsEntry

LabelsEntry(mapping=None, *, ignore_unknown_fields=False, **kwargs)

The abstract base class for a message.

Parameters
Name	Description
kwargs	dict Keys and values corresponding to the fields of the message.
mapping	Union[dict, .Message] A dictionary or message to be used to determine the values for this message.
ignore_unknown_fields	Optional(bool) If True, do not raise errors for unknown fields. Only applied if mapping is a mapping type or there are keyword parameters.

RuntimeConfig

RuntimeConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)

The runtime config of a PipelineJob.

Methods

PipelineJob

PipelineJob(mapping=None, *, ignore_unknown_fields=False, **kwargs)

An instance of a machine learning PipelineJob.