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v1

fluid_calculation record, v1 — canonical aliases.

Consumers and the record registry import from here and never touch the inner module names, mirroring steps/*/v1/__init__.py.

Module​

Submodules​

Classes​

ORM​

class ORM(**kwargs):

SQLAlchemy model for the fluid_calculation cache table.

One row per (task_hash, file_id): the fluid volume metrics computed for a scan from pathology model predictions. Fluid volume is a deterministic function of the scan and the pathology output (and the config, which folds into task_hash) — NOT of the project — so project_id is provenance only and excluded from the key, letting two projects on the same datasource share rows (mirrors model_inferences).

The metrics live in the schemaless metrics_json blob (the FluidVolumeMetrics scalar fields plus the variable segmentation_volumes map). A per-file error string (missing-data reason or calculation_error:...) is stored in error instead; exactly one of the two is populated for any given row.

A simple constructor that allows initialization from kwargs.

Sets attributes on the constructed instance using the names and values in kwargs.

Only keys that are present as attributes of the instance's class are allowed. These could be, for example, any mapped columns or relationships.

Ancestors​

Variables​

  • error : Union[sqlalchemy.orm.attributes.InstrumentedAttribute[+_T_co], +_T_co]
  • file_id : Union[sqlalchemy.orm.attributes.InstrumentedAttribute[+_T_co], +_T_co]
  • last_accessed_at : Union[sqlalchemy.orm.attributes.InstrumentedAttribute[+_T_co], +_T_co]
  • metrics_json : Union[sqlalchemy.orm.attributes.InstrumentedAttribute[+_T_co], +_T_co]
  • processed_at : Union[sqlalchemy.orm.attributes.InstrumentedAttribute[+_T_co], +_T_co]
  • project_id : Union[sqlalchemy.orm.attributes.InstrumentedAttribute[+_T_co], +_T_co]
  • run_id : Union[sqlalchemy.orm.attributes.InstrumentedAttribute[+_T_co], +_T_co]
  • tags : Union[sqlalchemy.orm.attributes.InstrumentedAttribute[+_T_co], +_T_co]
  • task_hash : Union[sqlalchemy.orm.attributes.InstrumentedAttribute[+_T_co], +_T_co]

Record​

class Record(**data: Any):

Record of a single row from the fluid_calculation table.

Exactly one of metrics_json (successful calculation) or error (missing-data reason or calculation_error:...) is populated for a row.

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.

Variables​

  • static error : str | None
  • static file_id : str
  • static metrics_json : dict[str, typing.Any] | None
  • static model_config
  • static project_id : str | None
  • static run_id : str | None
  • static task_hash : str