Struct MetricSemantics 

#[non_exhaustive]
pub struct MetricSemantics {
    pub text_length_unit: Option<TextLengthUnit>,
    pub null_tokens: Option<NullTokenSet>,
    pub pattern_match_count: Option<PatternMatchCount>,
    pub shape_moments: Option<ShapeMomentEstimator>,
    pub range_rule_count: Option<RangeRuleCount>,
    pub key_uniqueness_units: Option<KeyUniquenessUnits>,
    pub outlier_units: Option<OutlierUnits>,
    pub key_column_source: Option<KeyColumnSource>,
}

How the measurements in a report were defined.

schema_version answers whether a document validates. It cannot answer whether two valid documents measured the same way: text lengths counted UTF-8 bytes through 0.11 and count Unicode scalar values since, with no change to the document’s shape. This records each intentionally changed definition by name, so a comparison can check exactly the ones both reports declare.

Every field is optional. A field missing from a stored report means the release that wrote it did not record that definition: unknown, never the current one. Later releases add fields, which older readers ignore.

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

text_length_unit: Option<TextLengthUnit>

Unit of min_length, max_length and avg_length on text columns.

Absent means not recorded; an explicit null is malformed, so neither the reader nor the schema accepts one.

null_tokens: Option<NullTokenSet>

The text values counted as null, which every null_count and every completeness figure depend on.

Absent means not recorded: the release that wrote the report counted only empty, null and nan, or recorded nothing at all.

pattern_match_count: Option<PatternMatchCount>

What every pattern’s match_count and match_percentage count.

Absent means not recorded: through 0.12 they counted every regular expression match, validated or not.

shape_moments: Option<ShapeMomentEstimator>

The estimator behind every column’s skewness and kurtosis.

Absent means not recorded: through 0.12 both used a form that matches neither the population nor the adjusted estimators.

range_rule_count: Option<RangeRuleCount>

What the range and sign rules behind the accuracy score count.

Absent means not recorded: through 0.12 every rule failure counted, over the numeric values of every column.

key_uniqueness_units: Option<KeyUniquenessUnits>

What key_uniqueness divides the key’s distinct values by.

Absent means not recorded: through 0.12 it divided by every row, nulls included.

outlier_units: Option<OutlierUnits>

What outlier_ratio is measured over.

Absent means not recorded: through 0.12 an untested source read 0 and still assessed accuracy.

key_column_source: Option<KeyColumnSource>

Which column key_uniqueness may measure.

Absent means not recorded: through 0.12 the first column with an id-like name was the key when none was declared.

Implementations

impl MetricSemantics

pub fn current() -> Self

The definitions this build measures with.

Trait Implementations

impl Clone for MetricSemantics

fn clone(&self) -> Self

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for MetricSemantics

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for MetricSemantics

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Eq for MetricSemantics

impl JsonSchema for MetricSemantics

fn schema_name() -> Cow<'static, str>

The name of the generated JSON Schema.

fn schema_id() -> Cow<'static, str>

Returns a string that uniquely identifies the schema produced by this type.

fn json_schema(generator: &mut SchemaGenerator) -> Schema

Generates a JSON Schema for this type.

fn inline_schema() -> bool

Whether JSON Schemas generated for this type should be included directly in parent schemas, rather than being re-used where possible using the $ref keyword.

impl PartialEq for MetricSemantics

fn eq(&self, other: &Self) -> bool

Equality operator ==.

fn ne(&self, other: &Rhs) -> bool

Inequality operator !=.

impl Serialize for MetricSemantics

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for MetricSemantics