lenskit.pipeline
================

.. py:module:: lenskit.pipeline

.. autoapi-nested-parse::

   LensKit pipeline abstraction.



Submodules
----------

.. autoapisummary::

   lenskit.pipeline.components
   lenskit.pipeline.config
   lenskit.pipeline.nodes

.. toctree::
    :hidden:
    :maxdepth: 1

    /api/lenskit/pipeline/components/index
    /api/lenskit/pipeline/config/index
    /api/lenskit/pipeline/nodes/index

Attributes
----------

.. autoapisummary::

   lenskit.pipeline.CloneMethod


Classes
-------

.. toctree::
   :hidden:

   /api/lenskit/pipeline/PipelineBuilder
   /api/lenskit/pipeline/PipelineCache
   /api/lenskit/pipeline/RecPipelineBuilder
   /api/lenskit/pipeline/ComponentInputHook
   /api/lenskit/pipeline/Pipeline
   /api/lenskit/pipeline/PipelineProfiler
   /api/lenskit/pipeline/ProfileSink
   /api/lenskit/pipeline/PipelineState

.. autoapisummary::

   lenskit.pipeline.PipelineBuilder
   lenskit.pipeline.PipelineCache
   lenskit.pipeline.RecPipelineBuilder
   lenskit.pipeline.ComponentInputHook
   lenskit.pipeline.Pipeline
   lenskit.pipeline.PipelineProfiler
   lenskit.pipeline.ProfileSink
   lenskit.pipeline.PipelineState


Functions
---------

.. autoapisummary::

   lenskit.pipeline.predict_pipeline
   lenskit.pipeline.topn_pipeline



Package Contents
----------------

.. py:function:: predict_pipeline(scorer, *, fallback = True, name = None)

   Create a pipeline that predicts ratings, but does **not** include any
   ranking capabilities.  Mostly userful for testing and historical purposes.
   The resulting pipeline **must** be called with an item list.

   :Stability: Caller

   :param scorer: The scorer to use in the pipeline (it will added with the component
                  name ``scorer``, see :ref:`pipeline-names`).
   :param fallback: Whether to use a fallback predictor when the scorer cannot score.
                    When configured, the `scorer` node is the scorer, and the
                    `rating-predictor` node applies the fallback.
   :param name: The pipeline name.


.. py:function:: topn_pipeline(scorer, config = None, *, predicts_ratings = False, n = None, name = None)

   Create a pipeline that produces top-N recommendations using a scoring model.

   :Stability: Caller

   :param scorer: The scorer to use in the pipeline (it will added with the component
                  name ``scorer``, see :ref:`pipeline-names`).
   :param predicts_ratings: If ``True``, make set up to predict ratings (``rating-predictor``),
                            using ``scorer`` with a fallback of :class:`BiasScorer`; if
                            ``"raw"``, use ``scorer`` directly with no fallback.
   :param n: The recommendation list length to configure in the pipeline.
   :param name: The pipeline name.


.. py:type:: CloneMethod
   :canonical: Literal['config', 'pipeline-config']



Exported Aliases
----------------

.. py:exception:: lenskit.pipeline.PipelineError

    Re-exported alias for :py:exc:`lenskit.diagnostics.PipelineError`.

.. py:exception:: lenskit.pipeline.PipelineWarning

    Re-exported alias for :py:exc:`lenskit.diagnostics.PipelineWarning`.

.. py:class:: lenskit.pipeline.Lazy

    Re-exported alias for :py:class:`lenskit.lazy.Lazy`.

.. py:class:: lenskit.pipeline.Component

    Re-exported alias for :py:class:`lenskit.pipeline.components.Component`.

.. py:class:: lenskit.pipeline.ComponentConstructor

    Re-exported alias for :py:class:`lenskit.pipeline.components.ComponentConstructor`.

.. py:data:: lenskit.pipeline.PipelineFunction

    Re-exported alias for :py:data:`lenskit.pipeline.components.PipelineFunction`.

.. py:class:: lenskit.pipeline.PipelineConfig

    Re-exported alias for :py:class:`lenskit.pipeline.config.PipelineConfig`.

.. py:class:: lenskit.pipeline.Node

    Re-exported alias for :py:class:`lenskit.pipeline.nodes.Node`.