Validate.assert_dimension_scores()

Raise an AssertionError if any dimension’s health score falls below a minimum.

Usage

Source

Validate.assert_dimension_scores(
    thresholds=None,
    message=None,
)

The assert_dimension_scores() method checks each data quality dimension’s score (from get_dimension_scores()) against a minimum acceptable value. This is useful in automated testing and CI environments where you want to fail the run when, say, the completeness score drops below 95.

Parameters

thresholds: dict[str, float] | None = None

A mapping of dimension name to a minimum acceptable score (0-100). If None, the minimums set via config(dimension_thresholds=...) are used. A dimension present in the thresholds but absent from the validation is ignored.

message: str | None = None

Custom error message to use if the assertion fails. If None, a default message that lists the offending dimensions (with actual vs. required scores) is generated.

Returns

None

Raises

AssertionError

If any dimension’s score is below its specified minimum.

Examples

import pointblank as pb

validation = (
    pb.Validate(data=pb.load_dataset("small_table"))
    .col_vals_not_null(columns="c")
    .interrogate()
)

# Fail if the completeness score is below 95
validation.assert_dimension_scores(thresholds={"completeness": 95})

See Also

Use, scores, thresholds