great_expectations.expectations.metrics.query_metrics

Package Contents

Classes

QueryColumn()

Base class for all Query Metrics.

QueryColumnPair()

Base class for all Query Metrics.

QueryMultipleColumns()

Base class for all Query Metrics.

QueryTable()

Base class for all Query Metrics.

QueryTemplateValues()

Base class for all Query Metrics.
class great_expectations.expectations.metrics.query_metrics.QueryColumn

Bases: great_expectations.expectations.metrics.query_metric_provider.QueryMetricProvider

Base class for all Query Metrics.
Query Metric classes inheriting from QueryMetricProvider must have the following attributes set:

  1. metric_name: the name to use. Metric Name must be globally unique in a great_expectations installation.

  1. domain_keys: a tuple of the keys used to determine the domain of the metric

  2. value_keys: a tuple of the keys used to determine the value of the metric.

In some cases, subclasses of MetricProvider, such as QueryMetricProvider, will already have correct values that may simply be inherited by Metric classes.

metric_name = query.column
value_keys = ['column', 'query']
_sqlalchemy(cls, execution_engine: SqlAlchemyExecutionEngine, metric_domain_kwargs: dict, metric_value_kwargs: dict, metrics: Dict[str, Any], runtime_configuration: dict)
_spark(cls, execution_engine: SparkDFExecutionEngine, metric_domain_kwargs: dict, metric_value_kwargs: dict, metrics: Dict[str, Any], runtime_configuration: dict)
class great_expectations.expectations.metrics.query_metrics.QueryColumnPair

Bases: great_expectations.expectations.metrics.query_metric_provider.QueryMetricProvider

Base class for all Query Metrics.
Query Metric classes inheriting from QueryMetricProvider must have the following attributes set:

  1. metric_name: the name to use. Metric Name must be globally unique in a great_expectations installation.

  1. domain_keys: a tuple of the keys used to determine the domain of the metric

  2. value_keys: a tuple of the keys used to determine the value of the metric.

In some cases, subclasses of MetricProvider, such as QueryMetricProvider, will already have correct values that may simply be inherited by Metric classes.

metric_name = query.column_pair
value_keys = ['column_A', 'column_B', 'query']
_sqlalchemy(cls, execution_engine: SqlAlchemyExecutionEngine, metric_domain_kwargs: dict, metric_value_kwargs: dict, metrics: Dict[str, Any], runtime_configuration: dict)
_spark(cls, execution_engine: SparkDFExecutionEngine, metric_domain_kwargs: dict, metric_value_kwargs: dict, metrics: Dict[str, Any], runtime_configuration: dict)
class great_expectations.expectations.metrics.query_metrics.QueryMultipleColumns

Bases: great_expectations.expectations.metrics.query_metric_provider.QueryMetricProvider

Base class for all Query Metrics.
Query Metric classes inheriting from QueryMetricProvider must have the following attributes set:

  1. metric_name: the name to use. Metric Name must be globally unique in a great_expectations installation.

  1. domain_keys: a tuple of the keys used to determine the domain of the metric

  2. value_keys: a tuple of the keys used to determine the value of the metric.

In some cases, subclasses of MetricProvider, such as QueryMetricProvider, will already have correct values that may simply be inherited by Metric classes.

metric_name = query.multiple_columns
value_keys = ['columns', 'query']
_sqlalchemy(cls, execution_engine: SqlAlchemyExecutionEngine, metric_domain_kwargs: dict, metric_value_kwargs: dict, metrics: Dict[str, Any], runtime_configuration: dict)
_spark(cls, execution_engine: SparkDFExecutionEngine, metric_domain_kwargs: dict, metric_value_kwargs: dict, metrics: Dict[str, Any], runtime_configuration: dict)
class great_expectations.expectations.metrics.query_metrics.QueryTable

Bases: great_expectations.expectations.metrics.query_metric_provider.QueryMetricProvider

Base class for all Query Metrics.
Query Metric classes inheriting from QueryMetricProvider must have the following attributes set:

  1. metric_name: the name to use. Metric Name must be globally unique in a great_expectations installation.

  1. domain_keys: a tuple of the keys used to determine the domain of the metric

  2. value_keys: a tuple of the keys used to determine the value of the metric.

In some cases, subclasses of MetricProvider, such as QueryMetricProvider, will already have correct values that may simply be inherited by Metric classes.

metric_name = query.table
value_keys = ['query']
_sqlalchemy(cls, execution_engine: SqlAlchemyExecutionEngine, metric_domain_kwargs: dict, metric_value_kwargs: dict, metrics: Dict[str, Any], runtime_configuration: dict)
_spark(cls, execution_engine: SparkDFExecutionEngine, metric_domain_kwargs: dict, metric_value_kwargs: dict, metrics: Dict[str, Any], runtime_configuration: dict)
class great_expectations.expectations.metrics.query_metrics.QueryTemplateValues

Bases: great_expectations.expectations.metrics.query_metric_provider.QueryMetricProvider

Base class for all Query Metrics.
Query Metric classes inheriting from QueryMetricProvider must have the following attributes set:

  1. metric_name: the name to use. Metric Name must be globally unique in a great_expectations installation.

  1. domain_keys: a tuple of the keys used to determine the domain of the metric

  2. value_keys: a tuple of the keys used to determine the value of the metric.

In some cases, subclasses of MetricProvider, such as QueryMetricProvider, will already have correct values that may simply be inherited by Metric classes.

metric_name = query.template_values
value_keys = ['template_dict', 'query']
_sqlalchemy(cls, execution_engine: SqlAlchemyExecutionEngine, metric_domain_kwargs: dict, metric_value_kwargs: dict, metrics: Dict[str, Any], runtime_configuration: dict)
_spark(cls, execution_engine: SparkDFExecutionEngine, metric_domain_kwargs: dict, metric_value_kwargs: dict, metrics: Dict[str, Any], runtime_configuration: dict)