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AiConfigsMetricListingRep.md

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AiConfigsMetricListingRep

Properties

Name Type Description Notes
experiment_count int The number of experiments using this metric [optional]
metric_group_count int The number of metric groups using this metric [optional]
guarded_rollout_count int The number of guarded rollouts using this metric [optional]
active_experiment_count int The number of active experiments using this metric [optional]
active_guarded_rollout_count int The number of active guarded rollouts using this metric [optional]
id str The ID of this metric
version_id str The version ID of the metric
version int Version of the metric [optional]
key str A unique key to reference the metric
name str A human-friendly name for the metric
kind str The kind of event the metric tracks
attached_flag_count int The number of feature flags currently attached to this metric [optional]
links Dict[str, AiConfigsLink] The location and content type of related resources
site AiConfigsLink [optional]
access AiConfigsAccess [optional]
tags List[str] Tags for the metric
creation_date int
last_modified AiConfigsModification [optional]
maintainer_id str The ID of the member who maintains this metric [optional]
maintainer AiConfigsMemberSummary [optional]
description str Description of the metric [optional]
category str The category of the metric [optional]
is_numeric bool For custom metrics, whether to track numeric changes in value against a baseline (<code>true</code>) or to track a conversion when an end user takes an action (<code>false</code>). [optional]
success_criteria str For custom metrics, the success criteria [optional]
unit str For numeric custom metrics, the unit of measure [optional]
event_key str For custom metrics, the event key to use in your code [optional]
randomization_units List[str] An array of randomization units allowed for this metric [optional]
filters AiConfigsFilter [optional]
unit_aggregation_type str The method by which multiple unit event values are aggregated [optional]
analysis_type str The method for analyzing metric events [optional]
percentile_value int The percentile for the analysis method. An integer denoting the target percentile between 0 and 100. Required when <code>analysisType</code> is <code>percentile</code>. [optional]
event_default AiConfigsMetricEventDefaultRep [optional]
data_source AiConfigsMetricDataSourceRefRep
archived bool Whether the metric version is archived [optional]
archived_at int [optional]
selector str For click metrics, the CSS selectors [optional]
urls List[Dict[str, object]] [optional]

Example

from launchdarkly_api.models.ai_configs_metric_listing_rep import AiConfigsMetricListingRep

# TODO update the JSON string below
json = "{}"
# create an instance of AiConfigsMetricListingRep from a JSON string
ai_configs_metric_listing_rep_instance = AiConfigsMetricListingRep.from_json(json)
# print the JSON string representation of the object
print(AiConfigsMetricListingRep.to_json())

# convert the object into a dict
ai_configs_metric_listing_rep_dict = ai_configs_metric_listing_rep_instance.to_dict()
# create an instance of AiConfigsMetricListingRep from a dict
ai_configs_metric_listing_rep_from_dict = AiConfigsMetricListingRep.from_dict(ai_configs_metric_listing_rep_dict)

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