InClassifier

class

class InClassifier(
    column_names: ColumnNamesWithAltSpec | None = None,
    on_missing_column: OnInvalidColumnSpec = 'ignore',
    on_wrong_value: OnInvalidValueSpec = 'ignore',
    values: ValuesSpec = field(kw_only=True),
    tags: TagsSpec | None = field(default=None, kw_only=True),
    on_wrong_type: OnInvalidColumnSpec = 'ignore',
)

Bases: BoolClassifier, ABC

Categories: dq-classifier

A boolean classifier that checks if a value is in a specified set of values.

Examples

The concrete membership classifiers are IsIn and IsNotIn:

IsIn(["status"], values={"new", "open"})
IsNotIn(["status"], values={"void"})

Parameters

parameter

column_namesColumnNamesWithAltSpec | None (list[str | tuple[str, str | None]] | None)

Columns to classify. Each entry is a column name, or a (column, verdict_column) tuple naming the column the verdict lands in; the two forms can be mixed. None (the default) classifies every user column, skipping the types this classifier does not support (see on_wrong_type). A verdict column that is not named explicitly is the source column plus this classifier's suffix.

parameter

on_missing_columnOnInvalidColumnSpec (Literal['ignore', 'fail'])

What to do when a named column is not in the table: "ignore" (the default) leaves it out, "fail" aborts the check.

parameter

on_wrong_valueOnInvalidValueSpec (Literal['ignore', 'fail'])

What to do when a value cannot be evaluated against this classifier: "ignore" (the default) yields a null verdict, "fail" aborts the check.

parameter

valuesValuesSpec (frozenset[int | float | bool | str | date | time | datetime | timedelta | bytes | Decimal | None])

Values to test membership against; a non-empty collection, deduplicated into a frozenset. None may be included to test for null membership.

parameter

tagsTagsSpec | None (list[str] | None)

Optional labels for this classifier. An operator given the same tag applies only to the classifiers carrying it; untagged operators apply to all of them.

parameter

on_wrong_typeOnInvalidColumnSpec (Literal['ignore', 'fail'])

Fixed to "ignore": this classifier accepts every column type, so there is no wrong type to report.

Methods

method

supported_dtypes

def supported_dtypes() -> frozenset