lenskit.basic.candidates.TrainingItemsCandidateSelector
=======================================================

.. py:class:: lenskit.basic.candidates.TrainingItemsCandidateSelector(config = None, **kwargs)
   

   Bases: :py:obj:`lenskit.pipeline.Component`\ [\ :py:obj:`lenskit.data.ItemList`\ ], :py:obj:`lenskit.training.Trainable`


   Candidate selector that selects all known items from the training data, optionally
   excluding certain items from the query (i.e., the request user's history).

   In order to look up the user's history in the training data, this needs to
   be combined with a component like
   :class:`~.history.UserTrainingHistoryLookup`.

   :Stability: Caller


   .. py:attribute:: config
      :type:  TrainingItemsCandidateConfig

      The component configuration object.  Component classes that support
      configuration **must** redefine this attribute with their specific
      configuration class type, which can be a Python dataclass or a Pydantic
      model class.


   .. py:attribute:: items
      :type:  lenskit.data.Vocabulary

      List of known items from the training data.


   .. py:method:: is_trained()

      Query if this component has already been trained.



   .. py:method:: train(data, options = TrainingOptions())

      Train the model to learn its parameters from a training dataset.

      :param data: The training dataset.
      :param options: The training options.



   .. py:method:: __call__(query)

      Run the pipeline's operation and produce a result.  This is the key
      method for components to implement.