invr 0.2.1

Declarative data validation engine using invariants executed on Polars DataFrames.
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use crate::infrastructure::polars::kind::PolarsKind;
use crate::invariant::Invariant;
use crate::scope::Scope;
use polars::prelude::*;

/// Builds the Polars expression counting rows where numeric values
/// are outside a specified inclusive range.
///
/// Required parameters:
/// - `min`: minimum allowed value (inclusive)
/// - `max`: maximum allowed value (inclusive)
///
/// Scope:
/// - Requires `Scope::Column`
///
/// Behavior:
/// - Casts the column to `Float64`
/// - Marks rows where `value < min` OR `value > max`
/// - Returns the total count of out-of-range values
///
/// The resulting metric represents the number of rows violating
/// the value range constraint.
pub fn plan(inv: &Invariant<PolarsKind>) -> Option<Expr> {
    let Scope::Column { name } = inv.scope() else {
        return None;
    };
    let min: f64 = inv.require_param("min").ok()?.parse().ok()?;
    let max: f64 = inv.require_param("max").ok()?.parse().ok()?;

    let col_expr = col(name).cast(DataType::Float64);

    Some(
        col_expr
            .clone()
            .lt(lit(min))
            .or(col_expr.gt(lit(max)))
            .sum(),
    )
}
#[cfg(test)]
mod tests {
    use super::*;
    use crate::domain::invariant::value_object::id::InvariantId;
    use crate::infrastructure::polars::kind::PolarsKind;
    use std::collections::BTreeMap;

    fn make_invariant(column: &str, min: f64, max: f64) -> Invariant<PolarsKind> {
        let id = InvariantId::new("value_between_test").unwrap();
        let mut params = BTreeMap::new();
        params.insert("min".to_string(), min.to_string());
        params.insert("max".to_string(), max.to_string());

        Invariant::new(
            id,
            PolarsKind::ValueBetween,
            Scope::Column {
                name: column.to_string(),
            },
        )
        .with_params(params)
    }

    fn df(values: Vec<i32>) -> DataFrame {
        let series = Series::new("a".into(), values);
        let height = series.len();
        DataFrame::new(height, vec![series.into()]).unwrap()
    }

    #[test]
    fn test_plan_returns_expr() {
        let inv = make_invariant("a", 0.0, 10.0);
        assert!(plan(&inv).is_some());
    }

    #[test]
    fn test_value_between_no_violation() {
        let df = df(vec![1, 2, 3, 4, 5]);
        let inv = make_invariant("a", 0.0, 10.0);

        let result = df.lazy().select([plan(&inv).unwrap()]).collect().unwrap();

        let value = result.columns()[0].get(0).unwrap();
        assert!(value.try_extract::<i64>().unwrap() == 0);
    }

    #[test]
    fn test_value_between_violation() {
        let df = df(vec![1, 2, 99, -5]);
        let inv = make_invariant("a", 0.0, 10.0);

        let result = df.lazy().select([plan(&inv).unwrap()]).collect().unwrap();

        let value = result.columns()[0].get(0).unwrap();

        assert!(value.try_extract::<i64>().unwrap() == 2);
    }

    #[test]
    fn test_wrong_scope_returns_none() {
        let id = InvariantId::new("wrong_scope").unwrap();
        let inv = Invariant::new(id, PolarsKind::ValueBetween, Scope::Dataset);
        assert!(plan(&inv).is_none());
    }
}