invr 0.2.1

Declarative data validation engine using invariants executed on Polars DataFrames.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98

use crate::infrastructure::polars::kind::PolarsKind;
use crate::invariant::Invariant;
use crate::scope::Scope;
use polars::prelude::*;
use polars::series::ops::NullBehavior;
/// Builds the Polars expression counting gaps in a numeric sequence
/// expected to increment by exactly 1 between consecutive rows.
///
/// Scope:
/// - Requires `Scope::Column`
///
/// Behavior:
/// - Computes the difference between consecutive rows using `diff(1)`
/// - Ignores nulls produced by the first row (`NullBehavior::Ignore`)
/// - Marks rows where the difference is NOT equal to `1`
/// - Sums the boolean mask to count sequence gaps
///
/// The resulting metric represents the number of sequence breaks.
///
/// A result of `0` means the column contains no gaps and
/// follows a strictly incremental sequence (step = 1).
pub fn plan(inv: &Invariant<PolarsKind>) -> Option<Expr> {
    let Scope::Column { name } = inv.scope() else {
        return None;
    };

    Some(
        col(name)
            .diff(Expr::from(1), NullBehavior::Ignore)
            .neq(lit(1))
            .sum(),
    )
}

#[cfg(test)]
mod tests {
    use super::*;
    use crate::domain::invariant::value_object::id::InvariantId;
    use crate::infrastructure::polars::kind::PolarsKind;

    fn make_invariant(column: &str) -> Invariant<PolarsKind> {
        let id = InvariantId::new("no_gaps_test").unwrap();
        Invariant::new(
            id,
            PolarsKind::NoGapsInSequence,
            Scope::Column {
                name: column.to_string(),
            },
        )
    }

    fn df_with_values(values: Vec<i64>) -> DataFrame {
        let series = Series::new("a".into(), values);
        DataFrame::new_infer_height(vec![series.into()]).unwrap()
    }

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

    #[test]
    fn test_no_gaps_no_violation() {
        let df = df_with_values(vec![1, 2, 3, 4]);
        let inv = make_invariant("a");

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

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

        assert_eq!(count, 0);
    }

    #[test]
    fn test_gap_violation() {
        let df = df_with_values(vec![1, 2, 4, 5]);
        let inv = make_invariant("a");

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

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

        assert!(count > 0);
    }

    #[test]
    fn test_wrong_scope_returns_none() {
        let id = InvariantId::new("wrong_scope").unwrap();
        let inv = Invariant::new(id, PolarsKind::NoGapsInSequence, Scope::Dataset);

        let expr = plan(&inv);
        assert!(expr.is_none());
    }
}