mlm_insights.tests.selectors package¶
Subpackages¶
Submodules¶
mlm_insights.tests.selectors.dataset_metric_selector module¶
- class mlm_insights.tests.selectors.dataset_metric_selector.DatasetMetricSelector(profile_source: ProfileSource, metric_key: str)¶
Bases:
SelectorBase
DatasetMetricSelector is a selection technique which use Insights profile as source. User can query metric data by using metric key.`metric key` is available in json view of Profile.
Configuration¶
profile_source : ProfileSource Specify whether the source is current profile or reference profile
metric_key: str Metric key for given dataset metric, Use Metric key according to Json view of insights profile.
- metric_key: str¶
- profile_source: ProfileSource¶
- query(test_context: TestContext, *args: Any, **kwargs: Any) SelectorResult ¶
This method query the metric data from the Insight Profile.
Parameters¶
- test_contextTestContext
Must be ProfileTestContext.
Returns¶
SelectorResult
- validate(test_context: TestContext, *args: Any, **kwargs: Any) SelectorValidationResult ¶
Validate if all the configuration is valid or not
Parameters¶
- test_contextTestContext
ProfileTestContext
Returns¶
ValidationResult
mlm_insights.tests.selectors.feature_metric_selector module¶
- class mlm_insights.tests.selectors.feature_metric_selector.FeatureMetricSelector(profile_source: ProfileSource, feature_name: str, metric_key: str)¶
Bases:
SelectorBase
FeatureMetricSelector is a selection technique which use Insights profile as source. User can query metric data by using feature_name and metric key.`metric key` is available in json view of Profile.
Configuration¶
profile_source : ProfileSource Specify whether the source is current profile or reference profile
feature_name: str Name of the feature.
metric_key: str Metric key for given feature, Use Metric key according to Json view of insights profile.
- feature_name: str¶
- metric_key: str¶
- profile_source: ProfileSource¶
- query(test_context: TestContext, *args: Any, **kwargs: Any) SelectorResult ¶
This method query the metric data from the Insight Profile.
Parameters¶
- test_contextTestContext
Must be ProfileTestContext.
Returns¶
SelectorResult
- validate(test_context: TestContext, *args: Any, **kwargs: Any) SelectorValidationResult ¶
Validate if all the configuration is valid or nod
Parameters¶
- test_contextTestContext
ProfileTestContext
Returns¶
ValidationResult
mlm_insights.tests.selectors.selector_result module¶
- class mlm_insights.tests.selectors.selector_result.SelectorResult(value: int | str | float | bool | ~typing.List[~typing.Any] | ~typing.Tuple[int, int], description: str = '', tags: ~typing.Dict[str, ~typing.Any] = <factory>)¶
Bases:
object
SelectorResult contains the metric result that is produce by a Selector
- description: str = ''¶
Selector tags
- tags: Dict[str, Any]¶
- value: int | str | float | bool | List[Any] | Tuple[int, int]¶
Description of the selector
mlm_insights.tests.selectors.selector_validation_result module¶
- class mlm_insights.tests.selectors.selector_validation_result.SelectorValidationResult(valid: bool, errors: ~typing.List[str] = <factory>)¶
Bases:
object
ValidationResult tells if a Validation done by a Selector is valid or not. Selector must set valid = True, if validation succeeded. If validation fails, it should set valid = False and additionally it also set the list of errors
- errors: List[str]¶
- valid: bool¶