CfnExperimentPropsMixin

class aws_cdk.mixins_preview.aws_evidently.mixins.CfnExperimentPropsMixin(props, *, strategy=None)

Bases: Mixin

Creates or updates an Evidently experiment .

Before you create an experiment, you must create the feature to use for the experiment.

An experiment helps you make feature design decisions based on evidence and data. An experiment can test as many as five variations at once. Evidently collects experiment data and analyzes it by statistical methods, and provides clear recommendations about which variations perform better.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-evidently-experiment.html
CloudformationResource:: AWS::Evidently::Experiment
Mixin:: true
ExampleMetadata:: fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview import mixins
from aws_cdk.mixins_preview.aws_evidently import mixins as evidently_mixins

cfn_experiment_props_mixin = evidently_mixins.CfnExperimentPropsMixin(evidently_mixins.CfnExperimentMixinProps(
    description="description",
    metric_goals=[evidently_mixins.CfnExperimentPropsMixin.MetricGoalObjectProperty(
        desired_change="desiredChange",
        entity_id_key="entityIdKey",
        event_pattern="eventPattern",
        metric_name="metricName",
        unit_label="unitLabel",
        value_key="valueKey"
    )],
    name="name",
    online_ab_config=evidently_mixins.CfnExperimentPropsMixin.OnlineAbConfigObjectProperty(
        control_treatment_name="controlTreatmentName",
        treatment_weights=[evidently_mixins.CfnExperimentPropsMixin.TreatmentToWeightProperty(
            split_weight=123,
            treatment="treatment"
        )]
    ),
    project="project",
    randomization_salt="randomizationSalt",
    remove_segment=False,
    running_status=evidently_mixins.CfnExperimentPropsMixin.RunningStatusObjectProperty(
        analysis_complete_time="analysisCompleteTime",
        desired_state="desiredState",
        reason="reason",
        status="status"
    ),
    sampling_rate=123,
    segment="segment",
    tags=[CfnTag(
        key="key",
        value="value"
    )],
    treatments=[evidently_mixins.CfnExperimentPropsMixin.TreatmentObjectProperty(
        description="description",
        feature="feature",
        treatment_name="treatmentName",
        variation="variation"
    )]
),
    strategy=mixins.PropertyMergeStrategy.OVERRIDE
)

Create a mixin to apply properties to AWS::Evidently::Experiment.

Parameters:

props (Union[CfnExperimentMixinProps, Dict[str, Any]]) – L1 properties to apply.
strategy (Optional[PropertyMergeStrategy]) – (experimental) Strategy for merging nested properties. Default: - PropertyMergeStrategy.MERGE

Methods

apply_to(construct)

Apply the mixin properties to the construct.

Parameters:: construct (IConstruct)
Return type:: IConstruct

supports(construct)

Check if this mixin supports the given construct.

Parameters:: construct (IConstruct)
Return type:: bool

Attributes

CFN_PROPERTY_KEYS = ['description', 'metricGoals', 'name', 'onlineAbConfig', 'project', 'randomizationSalt', 'removeSegment', 'runningStatus', 'samplingRate', 'segment', 'tags', 'treatments']

Static Methods

classmethod is_mixin(x)

(experimental) Checks if x is a Mixin.

Parameters:: x (Any) – Any object.
Return type:: bool
Returns:: true if x is an object created from a class which extends Mixin.
Stability:: experimental

MetricGoalObjectProperty

class CfnExperimentPropsMixin.MetricGoalObjectProperty(*, desired_change=None, entity_id_key=None, event_pattern=None, metric_name=None, unit_label=None, value_key=None)

Bases: object

Use this structure to tell Evidently whether higher or lower values are desired for a metric that is used in an experiment.

Parameters:

desired_change (Optional[str]) – INCREASE means that a variation with a higher number for this metric is performing better. DECREASE means that a variation with a lower number for this metric is performing better.
entity_id_key (Optional[str]) – The entity, such as a user or session, that does an action that causes a metric value to be recorded. An example is userDetails.userID .
event_pattern (Optional[str]) – The EventBridge event pattern that defines how the metric is recorded. For more information about EventBridge event patterns, see Amazon EventBridge event patterns .
metric_name (Optional[str]) – A name for the metric. It can include up to 255 characters.
unit_label (Optional[str]) – A label for the units that the metric is measuring.
value_key (Optional[str]) – The JSON path to reference the numerical metric value in the event.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-metricgoalobject.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_evidently import mixins as evidently_mixins

metric_goal_object_property = evidently_mixins.CfnExperimentPropsMixin.MetricGoalObjectProperty(
    desired_change="desiredChange",
    entity_id_key="entityIdKey",
    event_pattern="eventPattern",
    metric_name="metricName",
    unit_label="unitLabel",
    value_key="valueKey"
)

Attributes

desired_change

INCREASE means that a variation with a higher number for this metric is performing better.

DECREASE means that a variation with a lower number for this metric is performing better.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-metricgoalobject.html#cfn-evidently-experiment-metricgoalobject-desiredchange

entity_id_key

The entity, such as a user or session, that does an action that causes a metric value to be recorded.

An example is userDetails.userID .

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-metricgoalobject.html#cfn-evidently-experiment-metricgoalobject-entityidkey

event_pattern

The EventBridge event pattern that defines how the metric is recorded.

For more information about EventBridge event patterns, see Amazon EventBridge event patterns .

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-metricgoalobject.html#cfn-evidently-experiment-metricgoalobject-eventpattern

metric_name

A name for the metric.

It can include up to 255 characters.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-metricgoalobject.html#cfn-evidently-experiment-metricgoalobject-metricname

unit_label

A label for the units that the metric is measuring.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-metricgoalobject.html#cfn-evidently-experiment-metricgoalobject-unitlabel

value_key

The JSON path to reference the numerical metric value in the event.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-metricgoalobject.html#cfn-evidently-experiment-metricgoalobject-valuekey

OnlineAbConfigObjectProperty

class CfnExperimentPropsMixin.OnlineAbConfigObjectProperty(*, control_treatment_name=None, treatment_weights=None)

Bases: object

A structure that contains the configuration of which variation to use as the “control” version.

The “control” version is used for comparison with other variations. This structure also specifies how much experiment traffic is allocated to each variation.

Parameters:

control_treatment_name (Optional[str]) – The name of the variation that is to be the default variation that the other variations are compared to.
treatment_weights (Union[IResolvable, Sequence[Union[IResolvable, TreatmentToWeightProperty, Dict[str, Any]]], None]) – A set of key-value pairs. The keys are treatment names, and the values are the portion of experiment traffic to be assigned to that treatment. Specify the traffic portion in thousandths of a percent, so 20,000 for a variation would allocate 20% of the experiment traffic to that variation.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-onlineabconfigobject.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_evidently import mixins as evidently_mixins

online_ab_config_object_property = evidently_mixins.CfnExperimentPropsMixin.OnlineAbConfigObjectProperty(
    control_treatment_name="controlTreatmentName",
    treatment_weights=[evidently_mixins.CfnExperimentPropsMixin.TreatmentToWeightProperty(
        split_weight=123,
        treatment="treatment"
    )]
)

Attributes

control_treatment_name

The name of the variation that is to be the default variation that the other variations are compared to.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-onlineabconfigobject.html#cfn-evidently-experiment-onlineabconfigobject-controltreatmentname

treatment_weights

A set of key-value pairs.

The keys are treatment names, and the values are the portion of experiment traffic to be assigned to that treatment. Specify the traffic portion in thousandths of a percent, so 20,000 for a variation would allocate 20% of the experiment traffic to that variation.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-onlineabconfigobject.html#cfn-evidently-experiment-onlineabconfigobject-treatmentweights

RunningStatusObjectProperty

class CfnExperimentPropsMixin.RunningStatusObjectProperty(*, analysis_complete_time=None, desired_state=None, reason=None, status=None)

Bases: object

Use this structure to start and stop the experiment.

Parameters:

analysis_complete_time (Optional[str]) – If you are using CloudFormation to start the experiment, use this field to specify when the experiment is to end. The format is as a UNIX timestamp. For more information about this format, see The Current Epoch Unix Timestamp .
desired_state (Optional[str]) – If you are using CloudFormation to stop this experiment, specify either COMPLETED or CANCELLED here to indicate how to classify this experiment.
reason (Optional[str]) – If you are using CloudFormation to stop this experiment, this is an optional field that you can use to record why the experiment is being stopped or cancelled.
status (Optional[str]) – To start the experiment now, specify START for this parameter. If this experiment is currently running and you want to stop it now, specify STOP .

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-runningstatusobject.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_evidently import mixins as evidently_mixins

running_status_object_property = evidently_mixins.CfnExperimentPropsMixin.RunningStatusObjectProperty(
    analysis_complete_time="analysisCompleteTime",
    desired_state="desiredState",
    reason="reason",
    status="status"
)

Attributes

analysis_complete_time

If you are using CloudFormation to start the experiment, use this field to specify when the experiment is to end.

The format is as a UNIX timestamp. For more information about this format, see The Current Epoch Unix Timestamp .

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-runningstatusobject.html#cfn-evidently-experiment-runningstatusobject-analysiscompletetime

desired_state

If you are using CloudFormation to stop this experiment, specify either COMPLETED or CANCELLED here to indicate how to classify this experiment.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-runningstatusobject.html#cfn-evidently-experiment-runningstatusobject-desiredstate

reason

If you are using CloudFormation to stop this experiment, this is an optional field that you can use to record why the experiment is being stopped or cancelled.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-runningstatusobject.html#cfn-evidently-experiment-runningstatusobject-reason

status

To start the experiment now, specify START for this parameter.

If this experiment is currently running and you want to stop it now, specify STOP .

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-runningstatusobject.html#cfn-evidently-experiment-runningstatusobject-status

TreatmentObjectProperty

class CfnExperimentPropsMixin.TreatmentObjectProperty(*, description=None, feature=None, treatment_name=None, variation=None)

Bases: object

A structure that defines one treatment in an experiment.

A treatment is a variation of the feature that you are including in the experiment.

Parameters:

description (Optional[str]) – The description of the treatment.
feature (Optional[str]) – The name of the feature for this experiment.
treatment_name (Optional[str]) – A name for this treatment. It can include up to 127 characters.
variation (Optional[str]) – The name of the variation to use for this treatment.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-treatmentobject.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_evidently import mixins as evidently_mixins

treatment_object_property = evidently_mixins.CfnExperimentPropsMixin.TreatmentObjectProperty(
    description="description",
    feature="feature",
    treatment_name="treatmentName",
    variation="variation"
)

Attributes

description

The description of the treatment.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-treatmentobject.html#cfn-evidently-experiment-treatmentobject-description

feature

The name of the feature for this experiment.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-treatmentobject.html#cfn-evidently-experiment-treatmentobject-feature

treatment_name

A name for this treatment.

It can include up to 127 characters.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-treatmentobject.html#cfn-evidently-experiment-treatmentobject-treatmentname

variation

The name of the variation to use for this treatment.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-treatmentobject.html#cfn-evidently-experiment-treatmentobject-variation

TreatmentToWeightProperty

class CfnExperimentPropsMixin.TreatmentToWeightProperty(*, split_weight=None, treatment=None)

Bases: object

This structure defines how much experiment traffic to allocate to one treatment used in the experiment.

Parameters:

split_weight (Union[int, float, None]) – The portion of experiment traffic to allocate to this treatment. Specify the traffic portion in thousandths of a percent, so 20,000 allocated to a treatment would allocate 20% of the experiment traffic to that treatment.
treatment (Optional[str]) – The name of the treatment.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-treatmenttoweight.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.mixins_preview.aws_evidently import mixins as evidently_mixins

treatment_to_weight_property = evidently_mixins.CfnExperimentPropsMixin.TreatmentToWeightProperty(
    split_weight=123,
    treatment="treatment"
)

Attributes

split_weight

The portion of experiment traffic to allocate to this treatment.

Specify the traffic portion in thousandths of a percent, so 20,000 allocated to a treatment would allocate 20% of the experiment traffic to that treatment.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-treatmenttoweight.html#cfn-evidently-experiment-treatmenttoweight-splitweight

treatment

The name of the treatment.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-evidently-experiment-treatmenttoweight.html#cfn-evidently-experiment-treatmenttoweight-treatment