lenskit.batch.BatchPipelineRunner
=================================

.. py:class:: lenskit.batch.BatchPipelineRunner(*, n_jobs = None, use_ray = None, profiler = None, batch_size = None)
   :canonical: lenskit.batch._runner.BatchPipelineRunner

   Apply a pipeline to a collection of test users.

   :Stability: Caller

   Argss:
       pipeline:
           The pipeline to evaluate.
       n_jobs:
           The number of parallel threads to use, or ``None`` for default
           defined by LensKit configuration and environment variables (see
           :ref:`parallel-config`).
       use_ray:
           Use Ray instead of threads to parallelize batch inference,
           overriding any option set in an environment variable or
           :file:`lenskit.toml`.
       batch_size:
           The batch size for multiprocess execution.  If ``None``, a batch
           size based on the number of inputs is used, with a maximum batch
           size of 1000.


   .. py:attribute:: n_jobs
      :type:  int


   .. py:attribute:: use_ray
      :type:  bool


   .. py:attribute:: batch_size
      :type:  int | None
      :value: None



   .. py:attribute:: profiler
      :type:  lenskit.pipeline.PipelineProfiler | None


   .. py:attribute:: invocations
      :type:  list[InvocationSpec]


   .. py:method:: add_invocation(inv)


   .. py:method:: score(component = 'scorer', *, output = 'scores')

      Request the batch run to generate test item scores.

      :param component: The name of the rating predictor component to run.
      :param output: The name of the results in the output dictionary.



   .. py:method:: predict(component = 'rating-predictor', *, output = 'predictions')

      Request the batch run to generate test item rating predictions.  It is identical
      to :meth:`score` but with different defaults.

      :param component: The name of the rating predictor component to run.
      :param output: The name of the results in the output dictionary.



   .. py:method:: recommend(component = 'recommender', *, output = 'recommendations', **extra)

      Request the batch run to generate recomendations.

      :param component: The name of the recommender component to run.
      :param output: The name of the results in the output dictionary.
      :param extra: Extra inputs to the recommender. A common option is ``n``, the
                    number of recommendations to return (a default may be baked into
                    the pipeline).



   .. py:method:: run(pipeline, queries)

      Run the pipeline and return its results.

      .. note::

          The runner does **not** guarantee that results are in the same order
          as the original inputs.

      :param pipeline: The pipeline to run.
      :param queries: The collection of test queries use.  See :ref:`batch-queries`
                      for details on the various input formats.

      :returns: The batch results, mapping output names to item list collections of
                outputs.