Version: 2.0.0

tabsdatak.dataquality


`AllOk`	A boolean criteria that selects rows where every boolean classifier passes (`True`).
`AnyFailed`	A boolean criteria that selects rows where at least one boolean classifier fails (`False`).
`BetweenClassifier`	A boolean classifier that checks if a value is within a specified range.
`BinCountSpec`	A type alias for the number of bins a Scale will have, between 1 and MAX_BINS.
`BinIdxSpec`	A type alias for a zero-based bin index, constrained by MAX_BINS.
`BinsCriteriaSpec`	A non-empty set of bins used in criteria.
`BinSpec`	A type alias for the bin, either an index [0..100] or a special one [none, nan, underflow, overflow]
`BoolClassifier`	Abstract base class for classifiers with a boolean verdict.
`BoolCriteria`	Abstract base for criteria over boolean classifier verdicts.
`Categorizer`	Abstract base class for classifiers that assign each value to a bin.
`CategoryCriteria`	Abstract base for criteria over a categorizer's bin assignments.
`Classifier`	Abstract base class for all data quality classifiers.
`ClassifiersSpec`	A non-empty list of `Classifier` instances.
`ColumnNameSpec`	A type alias for a single column name, represented as a string.
`ColumnNamesWithAltSpec`	A list of column references.
`ColumnNameWithAltSpec`	A single column reference: either the source column name, or a `(source, destination)` tuple naming the column to store the result in (`destination` may be `None` to auto-generate it).
`Criteria`	Selects rows for a `Filter`, `Select` or `Fail` operator.
`CriteriaOperator`	An operator that uses a criteria to select records.
`DataQuality`	A data quality check applied to one of a function's output tables.
`DoesNotMatch`	A boolean classifier that checks whether a value does not match a regular expression.
`Enrich`	An operator that appends each classifier's verdict column to the target table.
`ExponentialScale`	A scale whose bin edges are spaced exponentially over `[min_val, max_val]` (used with `ScaleCategorizer`).
`Fail`	An operator that fails (aborts) the current transaction when the rows selected by `criteria` reach `threshold`.
`Filter`	An operator that removes the rows selected by `criteria` from the target table.
`HasLength`	A boolean classifier that checks whether a value's length is within a range.
`IdentityScale`	A scale where every integer in `[min_val, max_val)` maps to its own bin (used with `ScaleCategorizer`).
`InBins`	A category criteria that selects rows whose bin is one of the given bins.
`InClassifier`	A boolean classifier that checks if a value is in a specified set of values.
`IncludeQualityColumnsSpec`	A type alias for quality columns to included in the Select or Filter target table.
`IsBetween`	A boolean classifier that checks whether a value is inside a range.
`IsFalse`	A boolean classifier that checks whether a value is `False`.
`IsIn`	A boolean classifier that checks whether a value is in a set of values.
`IsNan`	A boolean classifier that checks whether a value is `NaN` (not a number).
`IsNegative`	A boolean classifier that checks whether a numeric value is negative.
`IsNegativeOrZero`	A boolean classifier that checks whether a numeric value is negative or zero.
`IsNotBetween`	A boolean classifier that checks whether a value is outside a range.
`IsNotIn`	A boolean classifier that checks whether a value is not in a set of values.
`IsNotNan`	A boolean classifier that checks whether a value is not `NaN`.
`IsNotNull`	A boolean classifier that checks whether a value is not null.
`IsNotNullNorNan`	A boolean classifier that checks whether a value is neither null nor `NaN`.
`IsNotZero`	A boolean classifier that checks whether a numeric value is not zero.
`IsNull`	A boolean classifier that checks whether a value is null.
`IsNullOrNan`	A boolean classifier that checks whether a value is null or `NaN`.
`IsPositive`	A boolean classifier that checks whether a numeric value is positive.
`IsPositiveOrZero`	A boolean classifier that checks whether a numeric value is positive or zero.
`IsTrue`	A boolean classifier that checks whether a value is `True`.
`IsZero`	A boolean classifier that checks whether a numeric value is zero.
`LenSpec`	A type alias for a non-negative integer, typically used for specifying length.
`LinearScale`	A scale that splits `[min_val, max_val]` into equal-width bins (used with `ScaleCategorizer`).
`LogarithmicScale`	A scale whose bin edges are spaced logarithmically over `[min_val, max_val]` (used with `ScaleCategorizer`).
`MatchClassifier`	A boolean classifier that checks if a value matches a regex pattern.
`Matches`	A boolean classifier that checks whether a value matches a regular expression.
`MAX_BINS`	The maximum number of bins allowed in a bucketing operation.
`MonomialScale`	A power-law scale over `[min_val, max_val]` whose bin widths grow as a power of the value (used with `ScaleCategorizer`).
`NotInBins`	A category criteria that selects rows whose bin is not among the given bins.
`OnInvalidColumnSpec`	A type alias that specifies what to do if a column is invalid for the classifier.
`OnInvalidValueSpec`	A type alias that specifies what to do if a classifier value is invalid for column.
`Operator`	Abstract base class for all data quality operators.
`OperatorsSpec`	A non-empty list of `Operator` instances.
`PercentSpec`	A type alias for a percentage value, which can be an integer or a float between 0 and 100.
`PercentThreshold`	A `Fail` threshold expressed as a percentage of the table's rows.
`PythonDataTypeSpec`	A type alias for a union of common Python data types used in data quality checks.
`RangeClosedOnSpec`	A type alias that specifies which side of a range is closed (inclusive).
`RangeValueSpec`	A type alias for a value used in defining a range, based on Python data types.
`RowCountSpec`	A type alias for a non-negative row count.
`RowCountThreshold`	A `Fail` threshold expressed as an absolute number of rows.
`Scale`	Abstract base class for the scales used by `ScaleCategorizer`.
`ScaleBaseSpec`	A type alias for the base of a scale, which must be a float greater than 0.
`ScaleCategorizer`	A classifier that assigns each value to a bin defined by a `Scale`.
`ScaleIdentityLimitSpec`	A type alias for a limit in a scale identity, ranging from 0 to 100.
`ScaleLimitSpec`	A type alias for a generic limit in a scale, which can be an integer or a float.
`ScalePowerSpec`	A type alias for the power of a scale, which must be a float greater than 0.
`Select`	An operator that copies the rows selected by `criteria` to another table, leaving the target table unchanged.
`SpecialBinSpec`	A type alias for the bins for None, NaN, underflow and overflow values.
`Summary`	An operator that writes a data quality summary (one row per classifier: verdict tallies, or bin counts for a categorizer) to a table.
`TagOperator`	An operator that is scoped to classifiers by tag.
`TagSpec`	A type alias for a single tag, represented as a string.
`TagsSpec`	A list of tags.
`Threshold`	Abstract base class for the thresholds used by the `Fail` operator.
`ValuesSpec`	A non-empty set of values to check membership against (`None` is allowed, to test for null membership).

BinCountSpec

type_alias

BinCountSpec: StrictInt

A type alias for the number of bins a Scale will have, between 1 and MAX_BINS.

BinIdxSpec

type_alias

BinIdxSpec: StrictInt

A type alias for a zero-based bin index, constrained by MAX_BINS.

BinsCriteriaSpec

type_alias

BinsCriteriaSpec: frozenset[BinSpec]

Resolved type:

frozenset[StrictInt | Literal['none', 'nan', 'underflow', 'overflow']]

A non-empty set of bins used in criteria.

BinSpec

type_alias

BinSpec: Union[BinIdxSpec, SpecialBinSpec]

Resolved type:

StrictInt | Literal['none', 'nan', 'underflow', 'overflow']

A type alias for the bin, either an index [0..100] or a special one [none, nan, underflow, overflow]

ClassifiersSpec

type_alias

ClassifiersSpec: list[Classifier]

A non-empty list of Classifier instances.

ColumnNameSpec

type_alias

ColumnNameSpec: str

A type alias for a single column name, represented as a string.

ColumnNamesWithAltSpec

type_alias

ColumnNamesWithAltSpec: list[ColumnNameWithAltSpec]

Resolved type:

list[str | tuple[str, str | None]]

A list of column references. Each element is a source column name or a (source, destination) tuple; the two forms may be mixed.

ColumnNameWithAltSpec

type_alias

ColumnNameWithAltSpec: Union[ColumnNameSpec, tuple[ColumnNameSpec, Union[ColumnNameSpec, None]]]

Resolved type:

str | tuple[str, str | None]

A single column reference: either the source column name, or a (source, destination) tuple naming the column to store the result in (destination may be None to auto-generate it).

IncludeQualityColumnsSpec

type_alias

IncludeQualityColumnsSpec: Literal['none', 'criteria', 'all']

A type alias for quality columns to included in the Select or Filter target table.

LenSpec

type_alias

LenSpec: StrictInt

A type alias for a non-negative integer, typically used for specifying length.

MAX_BINS

constant

MAX_BINS = 100

The maximum number of bins allowed in a bucketing operation.

OnInvalidColumnSpec

type_alias

OnInvalidColumnSpec: Literal['ignore', 'fail']

A type alias that specifies what to do if a column is invalid for the classifier.

OnInvalidValueSpec

type_alias

OnInvalidValueSpec: Literal['ignore', 'fail']

A type alias that specifies what to do if a classifier value is invalid for column.

OperatorsSpec

type_alias

OperatorsSpec: list[Operator]

A non-empty list of Operator instances.

PercentSpec

type_alias

PercentSpec: Union[StrictInt, StrictFloat]

Resolved type:

StrictInt | StrictFloat

A type alias for a percentage value, which can be an integer or a float between 0 and 100.

PythonDataTypeSpec

type_alias

PythonDataTypeSpec: Union[int, float, bool, str, date, time, datetime, timedelta, bytes, Decimal]

Resolved type:

int | float | bool | str | date | time | datetime | timedelta | bytes | Decimal

A type alias for a union of common Python data types used in data quality checks.

RangeClosedOnSpec

type_alias

RangeClosedOnSpec: Literal['none', 'lower', 'upper', 'both']

A type alias that specifies which side of a range is closed (inclusive).

'none': The range is open on both sides.
'lower': The range is closed on the lower bound.
'upper': The range is closed on the upper bound.
'both': The range is closed on both sides.

RangeValueSpec

type_alias

RangeValueSpec: PythonDataTypeSpec

Resolved type:

int | float | bool | str | date | time | datetime | timedelta | bytes | Decimal

A type alias for a value used in defining a range, based on Python data types.

RowCountSpec

type_alias

RowCountSpec: StrictInt

A type alias for a non-negative row count.

ScaleBaseSpec

type_alias

ScaleBaseSpec: StrictFloat

A type alias for the base of a scale, which must be a float greater than 0.

ScaleIdentityLimitSpec

type_alias

ScaleIdentityLimitSpec: StrictInt

A type alias for a limit in a scale identity, ranging from 0 to 100.

ScaleLimitSpec

type_alias

ScaleLimitSpec: Union[StrictInt, StrictFloat]

Resolved type:

StrictInt | StrictFloat

A type alias for a generic limit in a scale, which can be an integer or a float.

ScalePowerSpec

type_alias

ScalePowerSpec: StrictFloat

A type alias for the power of a scale, which must be a float greater than 0.

SpecialBinSpec

type_alias

SpecialBinSpec: Literal['none', 'nan', 'underflow', 'overflow']

A type alias for the bins for None, NaN, underflow and overflow values.

TagSpec

type_alias

TagSpec: str

A type alias for a single tag, represented as a string.

TagsSpec

type_alias

TagsSpec: list[TagSpec]

Resolved type:

list[str]

A list of tags.

ValuesSpec

type_alias

ValuesSpec: frozenset[Union[PythonDataTypeSpec, None]]

Resolved type:

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

A non-empty set of values to check membership against (None is allowed, to test for null membership). A list passed to the constructor is coerced to a frozenset (deduplicated) by pydantic.