polars

PolarsPredicate(expr)

Bases: Predicate

Predicate for Polars DataFrame.

This predicate allows for two different ways to provide the predicate expression:

1. As a Polars expression. This expression is used directly and must evaluate to a single boolean value. For example, the following expression checks if the values in the "feature_a" column are in the list [1, 2, 3] and if the values in the "feature_b" column are greater than 0:

       import polars as pl
   
       PolarsPredicate(
           pl.col("feature_a").is_in([1, 2, 3]).and_(pl.col("feature_b") > 0),
       )
   

2. As a string. The string is parsed as a Polars expression. Any string identifier are replace with the respective feature during evaluation. The string expression must evaluate to a single boolean value as well. For example, the following expression checks if "feature_a" is always greater than "feature_b":

       import polars as pl
   
       PolarsPredicate(
           "feature_a > feature_b",
       )
   

   Boolean expressions like and, or, and not are not supported by this syntax. See AndPredicate, OrPredicate and NotPredicate for combined predicates or use the polars expression syntax above.

Initialize the predicate from a polars expression or a string.

Source code in src/flowcean/core/tool/testing/predicates/polars.py

def __init__(self, expr: pl.Expr | str) -> None:
    """Initialize the predicate from a polars expression or a string."""
    self.expr = _str_to_pl(expr) if isinstance(expr, str) else expr