nipoppy.workflows.PipelineRunner

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

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)

  • keep_workdir (bool)

  • simulate (bool)

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

  • logger (Optional[logging.Logger])

  • dry_run (bool)

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)

property dpaths_to_check: list[pathlib.Path]

Directory paths to create if needed during the setup phase.

Return type:

list[pathlib.Path]

keep_workdir = False
simulate = False