Struct StatisticalConstraint 

pub struct StatisticalConstraint { /* private fields */ }

A unified constraint that checks statistical properties of a column.

This constraint replaces the individual statistical constraints and provides a consistent interface for all statistical checks.

Examples

use term_guard::constraints::{StatisticalConstraint, StatisticType, Assertion};
use term_guard::core::Constraint;

// Check that mean is between 25 and 35
let mean_check = StatisticalConstraint::new(
    "age",
    StatisticType::Mean,
    Assertion::Between(25.0, 35.0)
);

// Check that maximum is less than 100
let max_check = StatisticalConstraint::new(
    "score",
    StatisticType::Max,
    Assertion::LessThan(100.0)
);

// Check 95th percentile for SLA
let p95_check = StatisticalConstraint::new(
    "response_time",
    StatisticType::Percentile(0.95),
    Assertion::LessThan(1000.0)
);

Implementations

impl StatisticalConstraint

pub fn new( column: impl Into<String>, statistic: StatisticType, assertion: Assertion, ) -> Result<Self>

Creates a new statistical constraint.

Arguments

• column - The column to check
• statistic - The type of statistic to compute
• assertion - The assertion to evaluate

Errors

Returns error if column name is invalid or if percentile is out of range.

pub fn min(column: impl Into<String>, assertion: Assertion) -> Result<Self>

Creates a minimum value constraint.

pub fn max(column: impl Into<String>, assertion: Assertion) -> Result<Self>

Creates a maximum value constraint.

pub fn mean(column: impl Into<String>, assertion: Assertion) -> Result<Self>

Creates a mean/average constraint.

pub fn sum(column: impl Into<String>, assertion: Assertion) -> Result<Self>

Creates a sum constraint.

pub fn standard_deviation( column: impl Into<String>, assertion: Assertion, ) -> Result<Self>

Creates a standard deviation constraint.

pub fn variance(column: impl Into<String>, assertion: Assertion) -> Result<Self>

Creates a variance constraint.

pub fn median(column: impl Into<String>, assertion: Assertion) -> Result<Self>

Creates a median constraint.

pub fn percentile( column: impl Into<String>, percentile: f64, assertion: Assertion, ) -> Result<Self>

Creates a percentile constraint.

Errors

Returns error if column name is invalid or percentile is not between 0.0 and 1.0

Trait Implementations

impl Clone for StatisticalConstraint

fn clone(&self) -> StatisticalConstraint

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Constraint for StatisticalConstraint

fn evaluate<'life0, 'life1, 'async_trait>( &'life0 self, ctx: &'life1 SessionContext, ) -> Pin<Box<dyn Future<Output = Result<ConstraintResult>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Evaluates the constraint against the data in the session context.

fn name(&self) -> &str

Returns the name of the constraint.

fn column(&self) -> Option<&str>

Returns the column this constraint operates on (if single-column).

fn metadata(&self) -> ConstraintMetadata

Returns the metadata associated with this constraint.

fn description(&self) -> Option<&str>

Returns a description of what this constraint validates.

impl Debug for StatisticalConstraint

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

Formats the value using the given formatter.