lenskit.data.RelationshipSet

class lenskit.data.RelationshipSet(name, vocabularies, schema, table)

Bases: object

Representation for a set of relationship records. This is the class for accessing general relationships, with arbitrarily many entity classes involved and repeated relationships allowed.

For two-entity relationships without duplicates (including relationships formed by coalescing repeated relationships or interactions), MatrixRelationshipSet extends this with additional capabilities.

Relationship sets can be pickled or serialized, and will not save the entire dataset with them. They are therefore safe to save as component elements during training processes.

Note

Client code does not need to construct this class; obtain instances from a dataset’s relationships() or interactions() method.

Stability:

Caller (see Stability Levels).

Parameters:

• name (str)

• vocabularies (dict[str, Vocabulary])

• schema (RelationshipSchema)

• table (pa.Table)

__init__(name, vocabularies, schema, table)

Parameters:

• name (str)

• vocabularies (dict[str, Vocabulary])

• schema (RelationshipSchema)

• table (Table)

Methods

__init__(name, vocabularies, schema, table)
arrow(*[, attributes, ids])	Get these relationships and their attributes as a PyArrow table.
count()
matrix(*[, row_entity, col_entity])	Convert this relationship set into a matrix, coalescing duplicate observations.
pandas(*[, attributes, ids])	Get these relationship and their attributes as a PyArrow table.

Attributes

attribute_names
entities
is_interaction	Query whether these relationships represent interactions.
name	The name of the relationship class for these relationships.
schema

name: str

The name of the relationship class for these relationships.

property is_interaction: bool

Query whether these relationships represent interactions.

arrow(*, attributes=None, ids=False)

Get these relationships and their attributes as a PyArrow table.

Parameters:

• attributes (str | list[str] | None) – The attributes to select.

• ids – If True, include ID columns for the entities, instead of just the number columns.

Return type:

Table

pandas(*, attributes=None, ids=False)

Get these relationship and their attributes as a PyArrow table.

Parameters:

• attributes (str | list[str] | None) – The attributes to include in the resulting table.

• ids – If True, include ID columns for the entities, instead of just the number columns.

Return type:

DataFrame

matrix(*, row_entity='user', col_entity='item')

Convert this relationship set into a matrix, coalescing duplicate observations.

Parameters:

• row_entity (str) – The specified row entity of the matrix

• col_entity (str) – The specified column entity of the matrix

Return type:

MatrixRelationshipSet