lenskit.batch

Batch-run recommendation pipelines for evaluation.

Attributes

BatchInput

Allowed input types for batch inference routines.

Classes

BatchRecRequest	Full recommendation request for batch inference, including candidate items.
TestRequestAdapter	Wrapper for an item list collection that interprets it as a collection of
BatchResults	Results from a batch recommendation run. Results consist of the outputs of
BatchPipelineRunner	Apply a pipeline to a collection of test users.
InvocationSpec	Specification for a single pipeline invocation, to record one or more

Functions

predict(…)	Convenience function to batch-generate rating predictions (or other per-item
recommend(…)	Convenience function to batch-generate recommendations from a pipeline. This

Package Contents

type lenskit.batch.BatchInput = Iterable[BatchRecRequest] | Iterable[RecQuery] | Iterable[ID | GenericKey] | ItemListCollection[GenericKey]

Allowed input types for batch inference routines.

lenskit.batch.predict[K: lenskit.data.GenericKey](pipeline: lenskit.pipeline.Pipeline, test: lenskit.data.ItemListCollection[K], *, n_jobs: int | None = None, use_ray: bool | None = None) → lenskit.data.ItemListCollection[K]

lenskit.batch.predict(pipeline: lenskit.pipeline.Pipeline, test: _queries.BatchInput, *, n_jobs: int | None = None, use_ray: bool | None = None) → lenskit.data.ItemListCollection[lenskit.data.GenericKey]

Convenience function to batch-generate rating predictions (or other per-item scores) from a pipeline. This is a batch version of lenskit.predict(), and is a convenience wrapper around using a BatchPipelineRunner() to generate predictions.

Note

If test is just a sequence of IDs, this method will still work, but it will score _all candidate items_ for each of the IDs.

Stability:

Caller (see Stability Levels).

lenskit.batch.recommend[K: lenskit.data.GenericKey](pipeline: lenskit.pipeline.Pipeline, queries: lenskit.data.ItemListCollection[K], n: int | None = None, *, n_jobs: int | None = None, use_ray: bool | None = None, profiler: lenskit.pipeline.PipelineProfiler | None = None, users=None) → lenskit.data.ItemListCollection[K]

lenskit.batch.recommend(pipeline: lenskit.pipeline.Pipeline, queries: _queries.BatchInput, n: int | None = None, *, n_jobs: int | None = None, use_ray: bool | None = None, profiler: lenskit.pipeline.PipelineProfiler | None = None, users=None) → lenskit.data.ItemListCollection[lenskit.data.GenericKey]

Convenience function to batch-generate recommendations from a pipeline. This is a batch version of lenskit.recommend(), and is a convenience wrapper around using a BatchPipelineRunner() to generate recommendations.

See also

BatchPipelineRunner.run() for details on the arguments, and Batch Queries for details on the valid inputs for queries.

Parameters:

queries – The request queries.

Stability:

Caller (see Stability Levels).

Exported Aliases

lenskit.batch.GenericKey

Re-exported alias for lenskit.data.GenericKey.

class lenskit.batch.ItemListCollection

Re-exported alias for lenskit.data.ItemListCollection.

class lenskit.batch.Pipeline

Re-exported alias for lenskit.pipeline.Pipeline.

class lenskit.batch.PipelineProfiler

Re-exported alias for lenskit.pipeline.PipelineProfiler.