Validation¶

Inspect an ExtractResult against the template's constraints.

validate ¶

validate(
    result: ExtractResult, template: Template
) -> Report

Validate an ExtractResult against a template's constraints.

This is a pure inspection — it does not mutate result. The returned Report carries every error surfaced during extraction (structural and coercion problems) plus any constraint violations found in the canonical data.

Parameters:

Name	Type	Description	Default
`result`	`ExtractResult`	The output of `crease.extract`.	required
`template`	`Template`	The same `Template` used to produce `result`.	required

Returns:

Type	Description
`Report`	A `Report` describing every problem found.

check ¶

check(
    path: str | Path,
    template: Template,
    *,
    engine: Engine | None = None,
) -> tuple[ExtractResult, Report]

Run extract + validate in one call.

Parameters:

Name	Type	Description	Default
`path`	`str \| Path`	Path to the source file.	required
`template`	`Template`	A loaded `crease.Template`.	required
`engine`	`Engine \| None`	See `crease.extract`.	`None`

Returns:

Type	Description
`ExtractResult`	A tuple `(result, report)`. `result` always carries a populated
`Report`	canonical dict (even when there are errors — partial extraction is
`tuple[ExtractResult, Report]`	the whole point); `report` carries the full error list.

Report `dataclass` ¶

Report(errors_list: list[Error] = list())

Result of validating an ExtractResult against its template.

Attributes:

Name	Type	Description
`errors_list`	`list[Error]`	The full list of `Error` records.

The richer API surface (is_valid, errors(), error_count()) is accessed as methods/properties, matching the pydantic idiom.

is_valid `property` ¶

is_valid: bool

True iff zero errors. The 90% check.

has_structural `property` ¶

has_structural: bool

True if any error is structural (template can't map the file).

errors ¶

errors() -> list[Error]

Return the full list of errors. Pydantic-shaped.

error_count ¶

error_count() -> int

raise_if_invalid ¶

raise_if_invalid() -> None

If any errors are present, raise ValidationError with the full list.

to_dict ¶

to_dict() -> dict[str, Any]

Serialize to a plain dict suitable for JSON output.