MetricDenominatorRep.md

MetricDenominatorRep

Properties

Name	Type	Description	Notes
event_name	str	The warehouse event column for the denominator	[optional]
is_numeric	bool	Whether the denominator aggregates a numeric value	[optional]
unit_aggregation_type	str	How individual unit values are aggregated for the denominator	[optional]
unit_aggregation_field	str	The column to count distinct values of; required when unitAggregationType is count_distinct	[optional]
data_source	MetricDataSourceRefRep		[optional]
filters	Filter		[optional]
window_start_offset	int	Start of the measurement window in milliseconds	[optional]
window_end_offset	int	End of the measurement window in milliseconds	[optional]
winsor_lower_percentile	float	Lower winsorization percentile in the open interval (0, 100)	[optional]
winsor_upper_percentile	float	Upper winsorization percentile in the open interval (0, 100)	[optional]
winsor_exclude_imputed	bool	Deprecated and ignored. Use winsorIncludeImputed instead.	[optional]
winsor_include_imputed	bool	When true, the percentile bound calculation includes imputed zeros	[optional]

Example

from launchdarkly_api.models.metric_denominator_rep import MetricDenominatorRep

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

# convert the object into a dict
metric_denominator_rep_dict = metric_denominator_rep_instance.to_dict()
# create an instance of MetricDenominatorRep from a dict
metric_denominator_rep_from_dict = MetricDenominatorRep.from_dict(metric_denominator_rep_dict)

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