Class AnalyzeDataSourceRiskDetails (2.0.1)

AnalyzeDataSourceRiskDetails(
    mapping=None, *, ignore_unknown_fields=False, **kwargs
)

Result of a risk analysis operation request.

Attributes

Name	Description
requested_privacy_metric	`.dlp.PrivacyMetric` Privacy metric to compute.
requested_source_table	`.storage.BigQueryTable` Input dataset to compute metrics over.
numerical_stats_result	`.dlp.AnalyzeDataSourceRiskDetails.NumericalStatsResult` Numerical stats result
categorical_stats_result	`.dlp.AnalyzeDataSourceRiskDetails.CategoricalStatsResult` Categorical stats result
k_anonymity_result	`.dlp.AnalyzeDataSourceRiskDetails.KAnonymityResult` K-anonymity result
l_diversity_result	`.dlp.AnalyzeDataSourceRiskDetails.LDiversityResult` L-divesity result
k_map_estimation_result	`.dlp.AnalyzeDataSourceRiskDetails.KMapEstimationResult` K-map result
delta_presence_estimation_result	`.dlp.AnalyzeDataSourceRiskDetails.DeltaPresenceEstimationResult` Delta-presence result

builtins.object > proto.message.Message > AnalyzeDataSourceRiskDetails

CategoricalStatsResult(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Result of the categorical stats computation.

DeltaPresenceEstimationResult(
    mapping=None, *, ignore_unknown_fields=False, **kwargs
)

Result of the δ-presence computation. Note that these results are an estimation, not exact values.

KAnonymityResult(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Result of the k-anonymity computation.

KMapEstimationResult(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Result of the reidentifiability analysis. Note that these results are an estimation, not exact values.

LDiversityResult(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Result of the l-diversity computation.

NumericalStatsResult(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Result of the numerical stats computation.