Listing pipelines

Information about pipelines in the catalog can be retrieved using the gds.pipeline.list() procedure.

1. Syntax

List pipelines from the catalog:

CALL gds.pipeline.list(pipelineName: String)
YIELD
    pipelineName: String,
    pipelineType: String,
    creationTime: DateTime,
    pipelineInfo: Map

Table 1. Parameters
Name	Type	Default	Optional	Description
pipelineName	String	`n/a`	yes	The name of a pipeline. If not specified, all pipelines in the catalog are listed.

Table 2. Results
Name	Type	Description
pipelineName	String	The name of the pipeline.
pipelineType	String	The type of the pipeline.
creationTime	Datetime	Time when the pipeline was created.
pipelineInfo	Map	Detailed information about this particular training pipeline, such as about intermediate steps in the pipeline.

2. Examples

Once we have created training pipelines in the catalog we can see information about either all of them or a single model using its name.

To exemplify listing pipelines, we create a node classification pipeline and a link prediction pipeline so that we have something to list.

Creating a link prediction training pipelines:

CALL gds.beta.pipeline.linkPrediction.create('lpPipe')

Creating node classification training pipelines:

CALL gds.beta.pipeline.nodeClassification.create('ncPipe')

2.1. Listing all pipelines

Listing detailed information about all pipelines:

CALL gds.pipeline.list()
YIELD pipelineName, pipelineType

Table 3. Results
pipelineName	pipelineType
`"lpPipe"`	`"Link prediction training pipeline"`
`"ncPipe"`	`"Node classification training pipeline"`

2.2. Listing a specific pipeline

Listing detailed information about specific pipeline:

CALL gds.pipeline.list('lpPipe')
YIELD pipelineName, pipelineType

Table 4. Results
pipelineName	pipelineType
`"lpPipe"`	`"Link prediction training pipeline"`