.. include:: global.inc .. _cheat_sheet: ##################### Cheat Sheet ##################### The ``ruffus`` module is a lightweight way to add support for running computational pipelines. | Each stage or **task** in a computational pipeline is represented by a python function | Each python function can be called in parallel to run multiple **jobs**. ================================================ 1. Annotate functions with **Ruffus** decorators ================================================ ****** Core ****** .. csv-table:: :header: "Decorator", "Syntax" :widths: 100, 600,1 "@originate (:ref:`Manual `) ", " :ref:`@originate ` ( ``output_files``, [``extra_parameters``,...] ) ", "" "@split (:ref:`Manual `) ", " :ref:`@split ` ( ``tasks_or_file_names``, ``output_files``, [``extra_parameters``,...] ) ", "" "@transform (:ref:`Manual `) ", " | :ref:`@transform ` ( ``tasks_or_file_names``, :ref:`suffix `\ *(*\ ``suffix_string``\ *)*\ , ``output_pattern``, [``extra_parameters``,...] ) | :ref:`@transform ` ( ``tasks_or_file_names``, :ref:`regex `\ *(*\ ``regex_pattern``\ *)*\ , ``output_pattern``, [``extra_parameters``,...] ) ", "" "@merge (:ref:`Manual `) ", " :ref:`@merge ` (``tasks_or_file_names``, ``output``, [``extra_parameters``,...] ) ", "" "@posttask (:ref:`Manual `) ", " | :ref:`@posttask ` ( ``signal_task_completion_function`` ) | :ref:`@posttask ` (:ref:`touch_file `\ ( ``'task1.completed'`` )) ", "" ************************************************************************************************ See :ref:`Decorators ` for a complete list of decorators ************************************************************************************************ ================================================ 2. Print dependency graph if necessary ================================================ - For a graphical flowchart in ``jpg``, ``svg``, ``dot``, ``png``, ``ps``, ``gif`` formats:: pipeline_printout_graph ( "flowchart.svg") .. comment This requires the `dot programme `_ to be installed - For a text printout of all jobs :: pipeline_printout() ================================================ 3. Run the pipeline ================================================ :: pipeline_run(multiprocess = N_PARALLEL_JOBS)