PipelineJob Class 
Pipeline job.
You should not instantiate this class directly. Instead, you should use the @pipeline decorator to create a PipelineJob.
] :param compute: Compute target name of the built pipeline. Defaults to None :type compute: str :param tags: Tag dictionary. Tags can be added, removed, and updated. Defaults to None :type tags: dict[str, str] :param kwargs: A dictionary of additional configuration parameters. Defaults to None :type kwargs: dict
Constructor
PipelineJob(*, component: str | PipelineComponent | Component | None = None, inputs: Dict[str, Input | str | bool | int | float] | None = None, outputs: Dict[str, Output] | None = None, name: str | None = None, description: str | None = None, display_name: str | None = None, experiment_name: str | None = None, jobs: Dict[str, BaseNode] | None = None, settings: PipelineJobSettings | None = None, identity: ManagedIdentityConfiguration | AmlTokenConfiguration | UserIdentityConfiguration | None = None, compute: str | None = None, tags: Dict[str, str] | None = None, **kwargs: Any)
		Parameters
| Name | Description | 
|---|---|
| 
		 component 
			
				Required
			 
	 | 
	
		
		 Pipeline component version. The field is mutually exclusive with 'jobs'.  | 
| 
		 inputs 
			
				Required
			 
	 | 
	
		
		 Inputs to the pipeline job.  | 
| 
		 outputs 
			
				Required
			 
	 | 
	
		
		 Outputs of the pipeline job.  | 
| 
		 name 
			
				Required
			 
	 | 
	
		
		 Name of the PipelineJob. Defaults to None.  | 
| 
		 description 
			
				Required
			 
	 | 
	
		
		 Description of the pipeline job. Defaults to None  | 
| 
		 display_name 
			
				Required
			 
	 | 
	
		
		 Display name of the pipeline job. Defaults to None  | 
| 
		 experiment_name 
			
				Required
			 
	 | 
	
		
		 Name of the experiment the job will be created under. If None is provided, the experiment will be set to the current directory. Defaults to None  | 
| 
		 jobs 
			
				Required
			 
	 | 
	
		
		 Pipeline component node name to component object. Defaults to None  | 
| 
		 settings 
			
				Required
			 
	 | 
	
		
		 Setting of the pipeline job. Defaults to None  | 
| 
		 identity 
			
				Required
			 
	 | 
	
		
		 Identity that the training job will use while running on compute. Defaults to None  | 
Keyword-Only Parameters
| Name | Description | 
|---|---|
| 
		 component 
	 | 
	
		 Default value: None 
			 | 
| 
		 inputs 
	 | 
	
		 Default value: None 
			 | 
| 
		 outputs 
	 | 
	
		 Default value: None 
			 | 
| 
		 name 
	 | 
	
		 Default value: None 
			 | 
| 
		 description 
	 | 
	
		 Default value: None 
			 | 
| 
		 display_name 
	 | 
	
		 Default value: None 
			 | 
| 
		 experiment_name 
	 | 
	
		 Default value: None 
			 | 
| 
		 jobs 
	 | 
	
		 Default value: None 
			 | 
| 
		 settings 
	 | 
	
		 Default value: None 
			 | 
| 
		 identity 
	 | 
	
		 Default value: None 
			 | 
| 
		 compute 
	 | 
	
		 Default value: None 
			 | 
| 
		 tags 
	 | 
	
		 Default value: None 
			 | 
Examples
Shows how to create a pipeline using this class.
   from azure.ai.ml.entities import PipelineJob, PipelineJobSettings
   pipeline_job = PipelineJob(
       description="test pipeline job",
       tags={},
       display_name="test display name",
       experiment_name="pipeline_job_samples",
       properties={},
       settings=PipelineJobSettings(force_rerun=True, default_compute="cpu-cluster"),
       jobs={"component1": component_func(component_in_number=1.0, component_in_path=uri_file_input)},
   )
   ml_client.jobs.create_or_update(pipeline_job)
	Methods
| dump | 
					 Dumps the job content into a file in YAML format.  | 
			
dump
Dumps the job content into a file in YAML format.
dump(dest: str | PathLike | IO, **kwargs: Any) -> None
		Parameters
| Name | Description | 
|---|---|
| 
		 dest 
			
				Required
			 
	 | 
	
		
		 The local path or file stream to write the YAML content to. If dest is a file path, a new file will be created. If dest is an open file, the file will be written to directly.  | 
Exceptions
| Type | Description | 
|---|---|
| 
					 Raised if dest is a file path and the file already exists.  | 
			|
| 
					 Raised if dest is an open file and the file is not writable.  | 
			
Attributes
base_path
creation_context
The creation context of the resource.
Returns
| Type | Description | 
|---|---|
| 
					 The creation metadata for the resource.  | 
		
id
inputs
jobs
log_files
outputs
settings
Settings of the pipeline job.
Returns
| Type | Description | 
|---|---|
| 
					 Settings of the pipeline job.  | 
		
status
The status of the job.
Common values returned include "Running", "Completed", and "Failed". All possible values are:
NotStarted - This is a temporary state that client-side Run objects are in before cloud submission.
Starting - The Run has started being processed in the cloud. The caller has a run ID at this point.
Provisioning - On-demand compute is being created for a given job submission.
Preparing - The run environment is being prepared and is in one of two stages:
Docker image build
conda environment setup
Queued - The job is queued on the compute target. For example, in BatchAI, the job is in a queued state
while waiting for all the requested nodes to be ready.
Running - The job has started to run on the compute target.
Finalizing - User code execution has completed, and the run is in post-processing stages.
CancelRequested - Cancellation has been requested for the job.
Completed - The run has completed successfully. This includes both the user code execution and run
post-processing stages.
Failed - The run failed. Usually the Error property on a run will provide details as to why.
Canceled - Follows a cancellation request and indicates that the run is now successfully cancelled.
NotResponding - For runs that have Heartbeats enabled, no heartbeat has been recently sent.
Returns
| Type | Description | 
|---|---|
| 
					 Status of the job.  |