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v1

tabulate_criteria_outcomes step v1.

Module​

Submodules​

Functions​

task_fn​

def task_fn(    datasource: BaseSource,    config: TabulateConfig,    evaluations: list[CriteriaEvaluation],) ‑> TabulateResult:

Project structured evaluations into the flat report DataFrame.

Arguments

  • datasource: The datasource (for default display-rename resolution).
  • config: Tabulate config (rename_columns).
  • evaluations: The structured evaluations from criteria_matching.

Returns TabulateResult carrying the flat csv_report_df.

Classes​

Config​

class Config(**data: Any):

Config for projecting criterion evaluations into the flat report df.

Arguments

  • rename_columns: Display-name map applied to failure-reason strings, so the projected reasons match the CSV report's display columns.

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 model_config
  • static rename_columns : dict[str, str]

Result​

class Result(**data: Any):

Container for the projected flat report DataFrame.

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 model_config