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Version: 0.15.50

MetricConfiguration

class great_expectations.validator.metric_configuration.MetricConfiguration(metric_name: str, metric_domain_kwargs: dict, metric_value_kwargs: Optional[dict] = None, metric_dependencies: Optional[dict] = None)#

An interface for configuring Metrics.

MetricConfiguration allows the configuration of domain information, dependencies and additional metric-specific configurations. Metrics are computed attributes of data, and are derived from one or more Batches that can then be used to evaluate Expectations or to summarize the result of the Validation.

Parameters

  • metric_name (str) – name of the Metric defined by the current MetricConfiguration.

  • metric_domain_kwargs (dict) – provides information on where the Metric can be calculated. For instance, a MapCondition metric can include the name of the column that the Metric is going to be run on.

  • metric_value_kwargs (optional[dict]) – Optional kwargs that define values specific to each Metric. For instance, a Metric that partitions a column can define the method of partitioning (uniform bins) and the number of bins (n_bins) as metric_value_kwargs.

  • metric_dependencies (optional[dict]) – This is a dict consisting of all Metrics necessary to evaluate the Expectation.

to_json_dict() → dict#

Returns a JSON-serializable dict representation of this MetricConfiguration.

Returns

A JSON-serializable dict representation of this MetricConfiguration.