Name your pipeline runs

In the output logs of a pipeline run you will see the name of the run:

Pipeline run training_pipeline-2023_05_24-12_41_04_576473 has finished in 3.742s.

This name is automatically generated based on the current date and time. To change the name for a run, pass run_name as a parameter to the with_options() method:

training_pipeline = training_pipeline.with_options(
    run_name="custom_pipeline_run_name"
)
training_pipeline()

Pipeline run names must be unique, so if you plan to run your pipelines multiple times or run them on a schedule, make sure to either compute the run name dynamically or include one of the placeholders that ZenML will replace.

The substitutions for the custom placeholders like experiment_name can be set in:

• @pipeline decorator, so they are effective for all steps in this pipeline

• pipeline.with_options function, so they are effective for all steps in this pipeline run

Standard substitutions always available and consistent in all steps of the pipeline are:

• {date}: current date, e.g. 2024_11_27

• {time}: current time in UTC format, e.g. 11_07_09_326492

training_pipeline = training_pipeline.with_options(
    run_name="custom_pipeline_run_name_{experiment_name}_{date}_{time}"
)
training_pipeline()