Linkers¶

Bases: BaseModel, ABC

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              matchlab.models.linkers.base.Linker[Linker]

              

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A methodology that finds candidate matches between two record steps.

A Model step calls prepare() once, then link(), each time it collects. Put one-off setup in prepare() instead, for example fitting a model over both datasets, so it doesn't repeat on every call to link(). link() must return a table with left_id, right_id, and score columns. normalise_model_scores casts that table to SCHEMA_MODEL_EDGES.

Every field is a setting unless marked matchlab.resources.FromResources. A fingerprint ignores a resource, so a marked field must not change what this scores.

Methods:

• prepare –

  Run once before link(), for setup that shouldn't repeat per call.

• link –

  Score candidate matches between left and right.

Attributes:

• model_config –
• version (int | None) –
• left_id (Literal['id']) –
• right_id (Literal['id']) –

model_config = ConfigDict(extra='forbid', frozen=True)

version: int | None = None

left_id: Literal['id'] = Field(default='id', description='The unique ID field in the left data')

right_id: Literal['id'] = Field(default='id', description='The unique ID field in the right data')

prepare(left: DataFrame, right: DataFrame) -> None

link(left: DataFrame, right: DataFrame) -> DataFrame