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result

Result for the generic en-face lesion calculation step (v1).

Classes​

LesionCalculationResult​

class LesionCalculationResult(**data: Any):

Result of a lesion calculation task.

records_stored reports how many per-file area rows were persisted to the lesion_calculation cache table. The metrics themselves are not returned in-memory: this step runs in background mode, where an in-memory result does not cross the phase boundary, so a downstream step reads the rows via the <step_name>.cache accessor (or records in the same process).

records_stored means two different things depending on which path the task took: on the compute path it is the number of rows persisted by this invocation (len(records) in persist_lesion_metrics); on the read-before-compute early return, where nothing was stale, it is instead the total row count of the step's own partition (own_accessor.count() in lesion_calculation_task) — there being no new rows to report, the field falls back to describing what is already there.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors​

Variables​

  • static model_config
  • cache : CacheAccessor | None - Return the CacheAccessor for reading this result in a DAG pipeline.

  • records : pandas.core.frame.DataFrame - Retrieve this result's rows as a DataFrame.

    The DataFrame is fetched from the cache on each access — it is not stored in the result object, allowing lazy access to large datasets without materialising them in memory until needed.

    Returns: A pandas.DataFrame with one row per cached record.

    Raises: RuntimeError: If no accessor is attached (e.g. the result was serialised across a Prefect task boundary). In a DAG pipeline use <step_name>.cache instead.

Static methods​

from_accessor​

def from_accessor(    accessor: CacheAccessor, *, records_stored: int | None = None,) ‑> Self:

Inherited from:

CacheBackedResult.from_accessor :

Build a result carrying accessor, in one call rather than two.

_accessor is a PrivateAttr, so it cannot be passed to the constructor and every producer would otherwise construct the result and then reach in to attach the accessor. That two-step is the shape this replaces.

Arguments

  • accessor: The CacheAccessor backing <step>.cache, scoped to the partition this result stands for.
  • records_stored: Rows this result stands for. Defaults to accessor.count() — the whole partition — which is what a step that persisted nothing this run reports. A step that wrote rows passes what it wrote; see the field's docstring for why the two are not interchangeable.

Returns An instance of the calling subclass, with the accessor attached.

Methods​

model_post_init​

def model_post_init(self: BaseModel, context: Any, /) ‑> None:

Inherited from:

CacheBackedResult.model_post_init :

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that's what pydantic-core passes when calling it.

Arguments

  • self: The BaseModel instance.
  • context: The context.