monitor_schema.models.analyzer.baseline

Define various baselines.

Attributes

DATASET_ID_DEF

Classes

NoExtrasBaseModel	No extras base model.
TimeRange	Support for a specific time range.
BaselineType	Supported baseline types.
_Baseline	Base class for a baseline.
_SegmentBaseline	Base class for a baseline.
ReferenceProfileId	A baseline based on a static reference profile.
TrailingWindowBaseline	A dynamic trailing window.
TimeRangeBaseline	A static time range.
SingleBatchBaseline	Using current batch.

Module Contents

monitor_schema.models.analyzer.baseline.DATASET_ID_DEF

class monitor_schema.models.analyzer.baseline.NoExtrasBaseModel

Bases: pydantic.BaseModel

No extras base model.

Inherit to prevent accidental extra fields.

class monitor_schema.models.analyzer.baseline.TimeRange

Bases: NoExtrasBaseModel

Support for a specific time range.

start: datetime.datetime

end: datetime.datetime

class monitor_schema.models.analyzer.baseline.BaselineType

Bases: str, enum.Enum

Supported baseline types.

BatchTimestamp = 'BatchTimestamp'

Reference = 'Reference'

TrailingWindow = 'TrailingWindow'

TimeRange = 'TimeRange'

CurrentBatch = 'CurrentBatch'

class monitor_schema.models.analyzer.baseline._Baseline

Bases: monitor_schema.models.commons.NoExtrasBaseModel

Base class for a baseline.

datasetId: str | None

class monitor_schema.models.analyzer.baseline._SegmentBaseline

Bases: _Baseline

Base class for a baseline.

inheritSegment: bool | None

class monitor_schema.models.analyzer.baseline.ReferenceProfileId

Bases: _Baseline

A baseline based on a static reference profile.

A typical use case is to use a “gold” dataset and upload its profile to WhyLabs. This can be a training dataset as well for an ML model.

type: Literal[BaselineType]

profileId: str

class monitor_schema.models.analyzer.baseline.TrailingWindowBaseline

Bases: _SegmentBaseline

A dynamic trailing window.

This is useful if you don’t have a static baseline to monitor against. This is the default mode for most monitors.

type: Literal[BaselineType]

size: int

offset: int | None

exclusionRanges: List[monitor_schema.models.commons.TimeRange] | None

class monitor_schema.models.analyzer.baseline.TimeRangeBaseline

Bases: _SegmentBaseline

A static time range.

Instead of using a single profile or a trailing window, user can lock in a “good” period.

type: Literal[BaselineType]

range: monitor_schema.models.commons.TimeRange

class monitor_schema.models.analyzer.baseline.SingleBatchBaseline

Bases: _SegmentBaseline

Using current batch.

This is used when you want to use one batch to monitor another batch in a different metric entity.

type: Literal[BaselineType]

offset: int | None

datasetId: str