nipoppy.workflows.runner

PipelineRunner workflow.

Module Contents

class nipoppy.workflows.runner.PipelineRunner(dpath_root, pipeline_name, pipeline_version=None, pipeline_step=None, participant_id=None, session_id=None, simulate=False, fpath_layout=None, logger=None, dry_run=False)

Bases: nipoppy.workflows.pipeline.BasePipelineWorkflow

Pipeline runner.

Parameters:

  • dpath_root (nipoppy.env.StrOrPathLike)

  • pipeline_name (str)

  • pipeline_version (Optional[str])

  • pipeline_step (Optional[str])

  • participant_id (str)

  • session_id (str)

  • simulate (bool)

  • fpath_layout (Optional[nipoppy.env.StrOrPathLike])

  • logger (Optional[logging.Logger])

  • dry_run (bool)

dpaths_to_check()

Directory paths to create if needed during the setup phase.

Return type:

list[pathlib.Path]

get_participants_sessions_to_run(participant_id, session_id)

Generate a list of participant and session IDs to run.

Specifically, this list will include participants who have BIDS data but who have not previously successfully completed the pipeline (according) to the bagel file.

Parameters:

  • participant_id (Optional[str])

  • session_id (Optional[str])

launch_boutiques_run(participant_id, session_id, objs=None, **kwargs)

Launch a pipeline run using Boutiques.

Parameters:

  • participant_id (str)

  • session_id (str)

  • objs (Optional[list])

process_container_config(participant_id, session_id, bind_paths=None)

Update container config and generate container command.

Parameters:

  • participant_id (str)

  • session_id (str)

  • bind_paths (Optional[list[nipoppy.env.StrOrPathLike]])

Return type:

str

run_cleanup()

Run pipeline runner cleanup.

run_single(participant_id, session_id)

Run pipeline on a single participant/session.

Parameters:

  • participant_id (str)

  • session_id (str)